Tina Hernandez-Boussard

All Publications

• AI and biosecurity: The need for governance. Science (New York, N.Y.) Bloomfield, D., Pannu, J., Zhu, A. W., Ng, M. Y., Lewis, A., Bendavid, E., Asch, S. M., Hernandez-Boussard, T., Cicero, A., Inglesby, T. 2024; 385 (6711): 831-833

  Abstract

  Governments should evaluate advanced models and if needed impose safety measures.

  View details for DOI 10.1126/science.adq1977

  View details for PubMedID 39172825

• Perceptions of Data Set Experts on Important Characteristics of Health Data Sets Ready for Machine Learning: A Qualitative Study. JAMA network open Ng, M. Y., Youssef, A., Miner, A. S., Sarellano, D., Long, J., Larson, D. B., Hernandez-Boussard, T., Langlotz, C. P. 2023; 6 (12): e2345892

  Abstract

  The lack of data quality frameworks to guide the development of artificial intelligence (AI)-ready data sets limits their usefulness for machine learning (ML) research in health care and hinders the diagnostic excellence of developed clinical AI applications for patient care.To discern what constitutes high-quality and useful data sets for health and biomedical ML research purposes according to subject matter experts.This qualitative study interviewed data set experts, particularly those who are creators and ML researchers. Semistructured interviews were conducted in English and remotely through a secure video conferencing platform between August 23, 2022, and January 5, 2023. A total of 93 experts were invited to participate. Twenty experts were enrolled and interviewed. Using purposive sampling, experts were affiliated with a diverse representation of 16 health data sets/databases across organizational sectors. Content analysis was used to evaluate survey information and thematic analysis was used to analyze interview data.Data set experts' perceptions on what makes data sets AI ready.Participants included 20 data set experts (11 [55%] men; mean [SD] age, 42 [11] years), of whom all were health data set creators, and 18 of the 20 were also ML researchers. Themes (3 main and 11 subthemes) were identified and integrated into an AI-readiness framework to show their association within the health data ecosystem. Participants partially determined the AI readiness of data sets using priority appraisal elements of accuracy, completeness, consistency, and fitness. Ethical acquisition and societal impact emerged as appraisal considerations in that participant samples have not been described to date in prior data quality frameworks. Factors that drive creation of high-quality health data sets and mitigate risks associated with data reuse in ML research were also relevant to AI readiness. The state of data availability, data quality standards, documentation, team science, and incentivization were associated with elements of AI readiness and the overall perception of data set usefulness.In this qualitative study of data set experts, participants contributed to the development of a grounded framework for AI data set quality. Data set AI readiness required the concerted appraisal of many elements and the balancing of transparency and ethical reflection against pragmatic constraints. The movement toward more reliable, relevant, and ethical AI and ML applications for patient care will inevitably require strategic updates to data set creation practices.

  View details for DOI 10.1001/jamanetworkopen.2023.45892

  View details for PubMedID 38039004

• Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care. JAMA network open Chin, M. H., Afsar-Manesh, N., Bierman, A. S., Chang, C., Colon-Rodriguez, C. J., Dullabh, P., Duran, D. G., Fair, M., Hernandez-Boussard, T., Hightower, M., Jain, A., Jordan, W. B., Konya, S., Moore, R. H., Moore, T. T., Rodriguez, R., Shaheen, G., Snyder, L. P., Srinivasan, M., Umscheid, C. A., Ohno-Machado, L. 2023; 6 (12): e2345050

  Abstract

  Importance: Health care algorithms are used for diagnosis, treatment, prognosis, risk stratification, and allocation of resources. Bias in the development and use of algorithms can lead to worse outcomes for racial and ethnic minoritized groups and other historically marginalized populations such as individuals with lower income.Objective: To provide a conceptual framework and guiding principles for mitigating and preventing bias in health care algorithms to promote health and health care equity.Evidence Review: The Agency for Healthcare Research and Quality and the National Institute for Minority Health and Health Disparities convened a diverse panel of experts to review evidence, hear from stakeholders, and receive community feedback.Findings: The panel developed a conceptual framework to apply guiding principles across an algorithm's life cycle, centering health and health care equity for patients and communities as the goal, within the wider context of structural racism and discrimination. Multiple stakeholders can mitigate and prevent bias at each phase of the algorithm life cycle, including problem formulation (phase 1); data selection, assessment, and management (phase 2); algorithm development, training, and validation (phase 3); deployment and integration of algorithms in intended settings (phase 4); and algorithm monitoring, maintenance, updating, or deimplementation (phase 5). Five principles should guide these efforts: (1) promote health and health care equity during all phases of the health care algorithm life cycle; (2) ensure health care algorithms and their use are transparent and explainable; (3) authentically engage patients and communities during all phases of the health care algorithm life cycle and earn trustworthiness; (4) explicitly identify health care algorithmic fairness issues and trade-offs; and (5) establish accountability for equity and fairness in outcomes from health care algorithms.Conclusions and Relevance: Multiple stakeholders must partner to create systems, processes, regulations, incentives, standards, and policies to mitigate and prevent algorithmic bias. Reforms should implement guiding principles that support promotion of health and health care equity in all phases of the algorithm life cycle as well as transparency and explainability, authentic community engagement and ethical partnerships, explicit identification of fairness issues and trade-offs, and accountability for equity and fairness.

  View details for DOI 10.1001/jamanetworkopen.2023.45050

  View details for PubMedID 38100101

• Promoting Equity In Clinical Decision Making: Dismantling Race-Based Medicine. Health affairs (Project Hope) Hernandez-Boussard, T., Siddique, S. M., Bierman, A. S., Hightower, M., Burstin, H. 2023; 42 (10): 1369-1373

  Abstract

  As the use of artificial intelligence has spread rapidly throughout the US health care system, concerns have been raised about racial and ethnic biases built into the algorithms that often guide clinical decision making. Race-based medicine, which relies on algorithms that use race as a proxy for biological differences, has led to treatment patterns that are inappropriate, unjust, and harmful to minoritized racial and ethnic groups. These patterns have contributed to persistent disparities in health and health care. To reduce these disparities, we recommend a race-aware approach to clinical decision support that considers social and environmental factors such as structural racism and social determinants of health. Recent policy changes in medical specialty societies and innovations in algorithm development represent progress on the path to dismantling race-based medicine. Success will require continued commitment and sustained efforts among stakeholders in the health care, research, and technology sectors. Increasing the diversity of clinical trial populations, broadening the focus of precision medicine, improving education about the complex factors shaping health outcomes, and developing new guidelines and policies to enable culturally responsive care are important next steps.

  View details for DOI 10.1377/hlthaff.2023.00545

  View details for PubMedID 37782875

• Scaling equitable artificial intelligence in healthcare with machine learning operations. BMJ health & care informatics Ng, M. Y., Youssef, A., Pillai, M., Shah, V., Hernandez-Boussard, T. 2024; 31 (1)

  View details for DOI 10.1136/bmjhci-2024-101101

  View details for PubMedID 39496359

• Development of Secure Infrastructure for Advancing Generative AI Research in Healthcare at an Academic Medical Center. Research square Ng, M. Y., Helzer, J., Pfeffer, M. A., Seto, T., Hernandez-Boussard, T. 2024

  Abstract

  The increasing interest in leveraging generative AI models in healthcare necessitates secure infrastructure at academic medical centers. Without an all-encompassing secure system, researchers may create their own insecure microprocesses, risking the exposure of protected health information (PHI) to the public internet or its inadvertent incorporation into AI model training. To address these challenges, our institution implemented a secure pathway to the Azure OpenAI Service using our own private OpenAI instance which we fully control to facilitate high-throughput, secure LLM queries. This pathway ensures data privacy while allowing researchers to harness the capabilities of LLMs for diverse healthcare applications. Our approach supports compliant, efficient, and innovative AI research in healthcare. This paper discusses the implementation, advantages, and use cases of this secure infrastructure, underscoring the critical need for centralized, secure AI solutions in academic medical environments.

  View details for DOI 10.21203/rs.3.rs-5095287/v1

  View details for PubMedID 39399679

• Defining and pursuing diversity in human genetic studies. Nature genetics Raven-Adams, M. C., Hernandez-Boussard, T., Joly, Y., Knoppers, B. M., Chandrasekharan, S., Thorogood, A., Kumuthini, J., Ho, C. W., Gonzlez, A., Nelson, S. C., Bombard, Y., Thaldar, D., Liu, H., Costa, A., Muralidharan, V., Henriques, S., Nasir, J., Lumaka, A., Kaiser, B., Jamuar, S. S., Lewis, A. C. 2024

  View details for DOI 10.1038/s41588-024-01903-7

  View details for PubMedID 39251787

  View details for PubMedCentralID 6785182

• Large language models outperform traditional natural language processing methods in extracting patient-reported outcomes in IBD. medRxiv : the preprint server for health sciences Patel, P. V., Davis, C., Ralbovsky, A., Tinoco, D., Williams, C. Y., Slatter, S., Naderalvojoud, B., Rosen, M. J., Hernandez-Boussard, T., Rudrapatna, V. 2024

  Abstract

  Patient-reported outcomes (PROs) are vital in assessing disease activity and treatment outcomes in inflammatory bowel disease (IBD). However, manual extraction of these PROs from the free-text of clinical notes is burdensome. We aimed to improve data curation from free-text information in the electronic health record, making it more available for research and quality improvement. This study aimed to compare traditional natural language processing (tNLP) and large language models (LLMs) in extracting three IBD PROs (abdominal pain, diarrhea, fecal blood) from clinical notes across two institutions.Clinic notes were annotated for each PRO using preset protocols. Models were developed and internally tested at the University of California San Francisco (UCSF), and then externally validated at Stanford University. We compared tNLP and LLM-based models on accuracy, sensitivity, specificity, positive and negative predictive value. Additionally, we conducted fairness and error assessments.Inter-rater reliability between annotators was >90%. On the UCSF test set (n=50), the top-performing tNLP models showcased accuracies of 92% (abdominal pain), 82% (diarrhea) and 80% (fecal blood), comparable to GPT-4, which was 96%, 88%, and 90% accurate, respectively. On external validation at Stanford (n=250), tNLP models failed to generalize (61-62% accuracy) while GPT-4 maintained accuracies >90%. PaLM-2 and GPT-4 showed similar performance. No biases were detected based on demographics or diagnosis.LLMs are accurate and generalizable methods for extracting PROs. They maintain excellent accuracy across institutions, despite heterogeneity in note templates and authors. Widespread adoption of such tools has the potential to enhance IBD research and patient care.

  View details for DOI 10.1101/2024.09.05.24313139

  View details for PubMedID 39281744

  View details for PubMedCentralID PMC11398594

• Applying natural language processing to patient messages to identify depression concerns in cancer patients. Journal of the American Medical Informatics Association : JAMIA van Buchem, M. M., de Hond, A. A., Fanconi, C., Shah, V., Schuessler, M., Kant, I. M., Steyerberg, E. W., Hernandez-Boussard, T. 2024

  Abstract

  This study aims to explore and develop tools for early identification of depression concerns among cancer patients by leveraging the novel data source of messages sent through a secure patient portal.We developed classifiers based on logistic regression (LR), support vector machines (SVMs), and 2 Bidirectional Encoder Representations from Transformers (BERT) models (original and Reddit-pretrained) on 6600 patient messages from a cancer center (2009-2022), annotated by a panel of healthcare professionals. Performance was compared using AUROC scores, and model fairness and explainability were examined. We also examined correlations between model predictions and depression diagnosis and treatment.BERT and RedditBERT attained AUROC scores of 0.88 and 0.86, respectively, compared to 0.79 for LR and 0.83 for SVM. BERT showed bigger differences in performance across sex, race, and ethnicity than RedditBERT. Patients who sent messages classified as concerning had a higher chance of receiving a depression diagnosis, a prescription for antidepressants, or a referral to the psycho-oncologist. Explanations from BERT and RedditBERT differed, with no clear preference from annotators.We show the potential of BERT and RedditBERT in identifying depression concerns in messages from cancer patients. Performance disparities across demographic groups highlight the need for careful consideration of potential biases. Further research is needed to address biases, evaluate real-world impacts, and ensure responsible integration into clinical settings.This work represents a significant methodological advancement in the early identification of depression concerns among cancer patients. Our work contributes to a route to reduce clinical burden while enhancing overall patient care, leveraging BERT-based models.

  View details for DOI 10.1093/jamia/ocae188

  View details for PubMedID 39018490

• Using large language models to assess public perceptions around glucagon-like peptide-1 receptor agonists on social media. Communications medicine Somani, S., Jain, S. S., Sarraju, A., Sandhu, A. T., Hernandez-Boussard, T., Rodriguez, F. 2024; 4 (1): 137

  Abstract

  The prevalence of obesity has been increasing worldwide, with substantial implications for public health. Obesity is independently associated with cardiovascular morbidity and mortality and is estimated to cost the health system over $200 billion dollars annually. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have emerged as a practice-changing therapy for weight loss and cardiovascular risk reduction independent of diabetes.We used large language models to augment our previously reported artificial intelligence-enabled topic modeling pipeline to analyze over 390,000 unique GLP-1 RA-related Reddit discussions.We find high interest around GLP-1 RAs, with a total of 168 topics and 33 groups focused on the GLP-1 RA experience with weight loss, comparison of side effects between differing GLP-1 RAs and alternate therapies, issues with GLP-1 RA access and supply, and the positive psychological benefits of GLP-1 RAs and associated weight loss. Notably, public sentiment in these discussions was mostly neutral-to-positive.These findings have important implications for monitoring new side effects not captured in randomized control trials and understanding the public health challenge of drug shortages.

  View details for DOI 10.1038/s43856-024-00566-z

  View details for PubMedID 38987347

  View details for PubMedCentralID PMC11237093

• Improving postsurgical fall detection for older Americans using LLM-driven analysis of clinical narratives. medRxiv : the preprint server for health sciences Pillai, M., Blumke, T. L., Studnia, J., Wang, Y., Veigulis, Z. P., Ware, A. D., Hoover, P. J., Carroll, I. R., Humphreys, K., Osborne, T. F., Asch, S. M., Hernandez-Boussard, T., Curtin, C. M. 2024

  Abstract

  Postsurgical falls have significant patient and societal implications but remain challenging to identify and track. Detecting postsurgical falls is crucial to improve patient care for older adults and reduce healthcare costs. Large language models (LLMs) offer a promising solution for reliable and automated fall detection using unstructured data in clinical notes. We tested several LLM prompting approaches to postsurgical fall detection in two different healthcare systems with three open-source LLMs. The Mixtral-8*7B zero-shot had the best performance at Stanford Health Care (PPV = 0.81, recall = 0.67) and the Veterans Health Administration (PPV = 0.93, recall = 0.94). These results demonstrate that LLMs can detect falls with little to no guidance and lay groundwork for applications of LLMs in fall prediction and prevention across many different settings.

  View details for DOI 10.1101/2024.06.25.24309480

  View details for PubMedID 38978655

• Long-Term Epidural Patching Outcomes and Predictors of Benefit in Patients With Suspected CSF Leak Nonconforming to ICHD-3 Criteria. Neurology Carroll, I., Han, L., Zhang, N., Cowan, R. P., Lanzman, B., Hashmi, S., Barad, M. J., Peretz, A., Moskatel, L., Ogunlaja, O., Hah, J. M., Hindiyeh, N., Barch, C., Bozkurt, S., Hernandez-Boussard, T., Callen, A. L. 2024; 102 (12): e209449

  Abstract

  Spinal CSF leaks lead to spontaneous intracranial hypotension (SIH). While International Classification of Headache Disorders, Third Edition (ICHD-3) criteria necessitate imaging confirmation or low opening pressure (OP) for SIH diagnosis, their sensitivity may be limited. We offered epidural blood patches (EBPs) to patients with symptoms suggestive of SIH, with and without a documented low OP or confirmed leak on imaging. This study evaluates the efficacy of this strategy.We conducted a prospective cohort study with a nested case-control design including all patients who presented to a tertiary headache clinic with clinical symptoms of SIH who completed study measures both before and after receiving an EBP between August 2016 and November 2018.The mean duration of symptoms was 8.7 ± 8.1 years. Of 85 patients assessed, 69 did not meet ICHD-3 criteria for SIH. At an average of 521 days after the initial EBP, this ICHD-3-negative subgroup experienced significant improvements in Patient-Reported Outcomes Measurement Information System (PROMIS) Global Physical Health score of +3.3 (95% CI 1.5-5.1), PROMIS Global Mental Health score of +1.8 (95% CI 0.0-3.5), Headache Impact Test (HIT)-6 head pain score of -3.8 (95% CI -5.7 to -1.8), Neck Disability Index of -4.8 (95% CI -9.0 to -0.6) and PROMIS Fatigue of -2.3 (95% CI -4.1 to -0.6). Fifty-four percent of ICHD-3-negative patients achieved clinically meaningful improvements in PROMIS Global Physical Health and 45% in HIT-6 scores. Pain relief following lying flat prior to treatment was strongly associated with sustained clinically meaningful improvement in global physical health at an average of 521 days (odds ratio 1.39, 95% CI 1.1-1.79; p < 0.003). ICHD-3-positive patients showed high rates of response and previously unreported, treatable levels of fatigue and cognitive deficits.Patients who did not conform to the ICHD-3 criteria for SIH showed moderate rates of sustained, clinically meaningful improvements in global physical health, global mental health, neck pain, fatigue, and head pain after EBP therapy. Pre-treatment improvement in head pain when flat was associated with later, sustained improvement after EBP therapy among patients who did not meet the ICHD-3 criteria.This study provides Class IV evidence that epidural blood patch is an effective treatment of suspected CSF leak not conforming to ICHD-3 criteria for SIH.

  View details for DOI 10.1212/WNL.0000000000209449

  View details for PubMedID 38820488

• Predictability of buprenorphine-naloxone treatment retention: A multi-site analysis combining electronic health records and machine learning. Addiction (Abingdon, England) Nateghi Haredasht, F., Fouladvand, S., Tate, S., Chan, M. M., Yeow, J. J., Griffiths, K., Lopez, I., Bertz, J. W., Miner, A. S., Hernandez-Boussard, T., Chen, C. A., Deng, H., Humphreys, K., Lembke, A., Vance, L. A., Chen, J. H. 2024

  Abstract

  Opioid use disorder (OUD) and opioid dependence lead to significant morbidity and mortality, yet treatment retention, crucial for the effectiveness of medications like buprenorphine-naloxone, remains unpredictable. Our objective was to determine the predictability of 6-month retention in buprenorphine-naloxone treatment using electronic health record (EHR) data from diverse clinical settings and to identify key predictors.This retrospective observational study developed and validated machine learning-based clinical risk prediction models using EHR data.Data were sourced from Stanford University's healthcare system and Holmusk's NeuroBlu database, reflecting a wide range of healthcare settings. The study analyzed 1800 Stanford and 7957 NeuroBlu treatment encounters from 2008 to 2023 and from 2003 to 2023, respectively.Predict continuous prescription of buprenorphine-naloxone for at least 6 months, without a gap of more than 30 days. The performance of machine learning prediction models was assessed by area under receiver operating characteristic (ROC-AUC) analysis as well as precision, recall and calibration. To further validate our approach's clinical applicability, we conducted two secondary analyses: a time-to-event analysis on a single site to estimate the duration of buprenorphine-naloxone treatment continuity evaluated by the C-index and a comparative evaluation against predictions made by three human clinical experts.Attrition rates at 6 months were 58% (NeuroBlu) and 61% (Stanford). Prediction models trained and internally validated on NeuroBlu data achieved ROC-AUCs up to 75.8 (95% confidence interval [CI] = 73.6-78.0). Addiction medicine specialists' predictions show a ROC-AUC of 67.8 (95% CI = 50.4-85.2). Time-to-event analysis on Stanford data indicated a median treatment retention time of 65 days, with random survival forest model achieving an average C-index of 65.9. The top predictor of treatment retention identified included the diagnosis of opioid dependence.US patients with opioid use disorder or opioid dependence treated with buprenorphine-naloxone prescriptions appear to have a high (∼60%) treatment attrition by 6 months. Machine learning models trained on diverse electronic health record datasets appear to be able to predict treatment continuity with accuracy comparable to that of clinical experts.

  View details for DOI 10.1111/add.16587

  View details for PubMedID 38923168

• Equity in the Setting of Heart Failure Diagnosis: An Analysis of Differences Between and Within Clinician Practices. Circulation. Heart failure Gupta, A., Tisdale, R. L., Calma, J., Stafford, R. S., Maron, D. J., Hernandez-Boussard, T., Ambrosy, A. P., Heidenreich, P. A., Sandhu, A. T. 2024: e010718

  Abstract

  BACKGROUND: Timely heart failure (HF) diagnosis can lead to earlier intervention and reduced morbidity. Among historically marginalized patients, new-onset HF diagnosis is more likely to occur in acute care settings (emergency department or inpatient hospitalization) than outpatient settings. Whether inequity within outpatient clinician practices affects diagnosis settings is unknown.METHODS: We determined the setting of incident HF diagnosis among Medicare fee-for-service beneficiaries between 2013 and 2017. We identified sociodemographic and medical characteristics associated with HF diagnosis in the acute care setting. Within each outpatient clinician practice, we compared acute care diagnosis rates across sociodemographic characteristics: female versus male sex, non-Hispanic White versus other racial and ethnic groups, and dual Medicare-Medicaid eligible (a surrogate for low income) versus nondual-eligible patients. Based on within-practice differences in acute diagnosis rates, we stratified clinician practices by equity (high, intermediate, and low) and compared clinician practice characteristics.RESULTS: Among 315 439 Medicare patients with incident HF, 173 121 (54.9%) were first diagnosed in acute care settings. Higher adjusted acute care diagnosis rates were associated with female sex (6.4% [95% CI, 6.1%-6.8%]), American Indian (3.6% [95% CI, 1.1%-6.1%]) race, and dual eligibility (4.1% [95% CI, 3.7%-4.5%]). These differences persisted within clinician practices. With clinician practice adjustment, dual-eligible patients had a 4.9% (95% CI, 4.5%-5.4%) greater acute care diagnosis rate than nondual-eligible patients. Clinician practices with greater equity across dual eligibility also had greater equity across sex and race and ethnicity and were more likely to be composed of predominantly primary care clinicians.CONCLUSIONS: Differences in HF diagnosis rates in the acute care setting between and within clinician practices highlight an opportunity to improve equity in diagnosing historically marginalized patients.

  View details for DOI 10.1161/CIRCHEARTFAILURE.123.010718

  View details for PubMedID 38847082

• DEVELOPMENT AND VALIDATION OF RISK PREDICTION TOOLS FOR PRESSURE INJURY OCCURRENCE: AN UMBRELLA REVIEW Hillier, B., Scandrett, K., Coombe, A., Hernandez-Boussard, T., Steyerberg, E., Takwoingi, Y., Velickovic, V., Dinnes, J. ELSEVIER SCIENCE INC. 2024: S272

  View details for Web of Science ID 001277006602343

• Contemporary attitudes and beliefs on coronary artery calcium from social media using artificial intelligence. NPJ digital medicine Somani, S., Balla, S., Peng, A. W., Dudum, R., Jain, S., Nasir, K., Maron, D. J., Hernandez-Boussard, T., Rodriguez, F. 2024; 7 (1): 83

  Abstract

  Coronary artery calcium (CAC) is a powerful tool to refine atherosclerotic cardiovascular disease (ASCVD) risk assessment. Despite its growing interest, contemporary public attitudes around CAC are not well-described in literature and have important implications for shared decision-making around cardiovascular prevention. We used an artificial intelligence (AI) pipeline consisting of a semi-supervised natural language processing model and unsupervised machine learning techniques to analyze 5,606 CAC-related discussions on Reddit. A total of 91 discussion topics were identified and were classified into 14 overarching thematic groups. These included the strong impact of CAC on therapeutic decision-making, ongoing non-evidence-based use of CAC testing, and the patient perceived downsides of CAC testing (e.g., radiation risk). Sentiment analysis also revealed that most discussions had a neutral (49.5%) or negative (48.4%) sentiment. The results of this study demonstrate the potential of an AI-based approach to analyze large, publicly available social media data to generate insights into public perceptions about CAC, which may help guide strategies to improve shared decision-making around ASCVD management and public health interventions.

  View details for DOI 10.1038/s41746-024-01077-w

  View details for PubMedID 38555387

  View details for PubMedCentralID PMC10981728

• Towards global model generalizability: independent cross-site feature evaluation for patient-level risk prediction models using the OHDSI network. Journal of the American Medical Informatics Association : JAMIA Naderalvojoud, B., Curtin, C. M., Yanover, C., El-Hay, T., Choi, B., Park, R. W., Tabuenca, J. G., Reeve, M. P., Falconer, T., Humphreys, K., Asch, S. M., Hernandez-Boussard, T. 2024

  Abstract

  Predictive models show promise in healthcare, but their successful deployment is challenging due to limited generalizability. Current external validation often focuses on model performance with restricted feature use from the original training data, lacking insights into their suitability at external sites. Our study introduces an innovative methodology for evaluating features during both the development phase and the validation, focusing on creating and validating predictive models for post-surgery patient outcomes with improved generalizability.Electronic health records (EHRs) from 4 countries (United States, United Kingdom, Finland, and Korea) were mapped to the OMOP Common Data Model (CDM), 2008-2019. Machine learning (ML) models were developed to predict post-surgery prolonged opioid use (POU) risks using data collected 6 months before surgery. Both local and cross-site feature selection methods were applied in the development and external validation datasets. Models were developed using Observational Health Data Sciences and Informatics (OHDSI) tools and validated on separate patient cohorts.Model development included 41 929 patients, 14.6% with POU. The external validation included 31 932 (UK), 23 100 (US), 7295 (Korea), and 3934 (Finland) patients with POU of 44.2%, 22.0%, 15.8%, and 21.8%, respectively. The top-performing model, Lasso logistic regression, achieved an area under the receiver operating characteristic curve (AUROC) of 0.75 during local validation and 0.69 (SD = 0.02) (averaged) in external validation. Models trained with cross-site feature selection significantly outperformed those using only features from the development site through external validation (P < .05).Using EHRs across four countries mapped to the OMOP CDM, we developed generalizable predictive models for POU. Our approach demonstrates the significant impact of cross-site feature selection in improving model performance, underscoring the importance of incorporating diverse feature sets from various clinical settings to enhance the generalizability and utility of predictive healthcare models.

  View details for DOI 10.1093/jamia/ocae028

  View details for PubMedID 38412331

• Measuring quality-of-care in treatment of young children with attention-deficit/hyperactivity disorder using pre-trained language models. Journal of the American Medical Informatics Association : JAMIA Pillai, M., Posada, J., Gardner, R. M., Hernandez-Boussard, T., Bannett, Y. 2024

  Abstract

  To measure pediatrician adherence to evidence-based guidelines in the treatment of young children with attention-deficit/hyperactivity disorder (ADHD) in a diverse healthcare system using natural language processing (NLP) techniques.We extracted structured and free-text data from electronic health records (EHRs) of all office visits (2015-2019) of children aged 4-6 years in a community-based primary healthcare network in California, who had ≥1 visits with an ICD-10 diagnosis of ADHD. Two pediatricians annotated clinical notes of the first ADHD visit for 423 patients. Inter-annotator agreement (IAA) was assessed for the recommendation for the first-line behavioral treatment (F-measure = 0.89). Four pre-trained language models, including BioClinical Bidirectional Encoder Representations from Transformers (BioClinicalBERT), were used to identify behavioral treatment recommendations using a 70/30 train/test split. For temporal validation, we deployed BioClinicalBERT on 1,020 unannotated notes from other ADHD visits and well-care visits; all positively classified notes (n = 53) and 5% of negatively classified notes (n = 50) were manually reviewed.Of 423 patients, 313 (74%) were male; 298 (70%) were privately insured; 138 (33%) were White; 61 (14%) were Hispanic. The BioClinicalBERT model trained on the first ADHD visits achieved F1 = 0.76, precision = 0.81, recall = 0.72, and AUC = 0.81 [0.72-0.89]. Temporal validation achieved F1 = 0.77, precision = 0.68, and recall = 0.88. Fairness analysis revealed low model performance in publicly insured patients (F1 = 0.53).Deploying pre-trained language models on a variable set of clinical notes accurately captured pediatrician adherence to guidelines in the treatment of children with ADHD. Validating this approach in other patient populations is needed to achieve equitable measurement of quality of care at scale and improve clinical care for mental health conditions.

  View details for DOI 10.1093/jamia/ocae001

  View details for PubMedID 38244997

• Predicting Depression Risk in Patients With Cancer Using Multimodal Data: Algorithm Development Study. JMIR medical informatics de Hond, A., van Buchem, M., Fanconi, C., Roy, M., Blayney, D., Kant, I., Steyerberg, E., Hernandez-Boussard, T. 2024; 12: e51925

  Abstract

  BACKGROUND: Patients with cancer starting systemic treatment programs, such as chemotherapy, often develop depression. A prediction model may assist physicians and health care workers in the early identification of these vulnerable patients.OBJECTIVE: This study aimed to develop a prediction model for depression risk within the first month of cancer treatment.METHODS: We included 16,159 patients diagnosed with cancer starting chemo- or radiotherapy treatment between 2008 and 2021. Machine learning models (eg, least absolute shrinkage and selection operator [LASSO] logistic regression) and natural language processing models (Bidirectional Encoder Representations from Transformers [BERT]) were used to develop multimodal prediction models using both electronic health record data and unstructured text (patient emails and clinician notes). Model performance was assessed in an independent test set (n=5387, 33%) using area under the receiver operating characteristic curve (AUROC), calibration curves, and decision curve analysis to assess initial clinical impact use.RESULTS: Among 16,159 patients, 437 (2.7%) received a depression diagnosis within the first month of treatment. The LASSO logistic regression models based on the structured data (AUROC 0.74, 95% CI 0.71-0.78) and structured data with email classification scores (AUROC 0.74, 95% CI 0.71-0.78) had the best discriminative performance. The BERT models based on clinician notes and structured data with email classification scores had AUROCs around 0.71. The logistic regression model based on email classification scores alone performed poorly (AUROC 0.54, 95% CI 0.52-0.56), and the model based solely on clinician notes had the worst performance (AUROC 0.50, 95% CI 0.49-0.52). Calibration was good for the logistic regression models, whereas the BERT models produced overly extreme risk estimates even after recalibration. There was a small range of decision thresholds for which the best-performing model showed promising clinical effectiveness use. The risks were underestimated for female and Black patients.CONCLUSIONS: The results demonstrated the potential and limitations of machine learning and multimodal models for predicting depression risk in patients with cancer. Future research is needed to further validate these models, refine the outcome label and predictors related to mental health, and address biases across subgroups.

  View details for DOI 10.2196/51925

  View details for PubMedID 38236635

• The Next Era of Assessment: Building a Trustworthy Assessment System. Perspectives on medical education Caretta-Weyer, H. A., Smirnova, A., Barone, M. A., Frank, J. R., Hernandez-Boussard, T., Levinson, D., Lombarts, K. M., Lomis, K. D., Martini, A., Schumacher, D. J., Turner, D. A., Schuh, A. 2024; 13 (1): 12-23

  Abstract

  Assessment in medical education has evolved through a sequence of eras each centering on distinct views and values. These eras include measurement (e.g., knowledge exams, objective structured clinical examinations), then judgments (e.g., workplace-based assessments, entrustable professional activities), and most recently systems or programmatic assessment, where over time multiple types and sources of data are collected and combined by competency committees to ensure individual learners are ready to progress to the next stage in their training. Significantly less attention has been paid to the social context of assessment, which has led to an overall erosion of trust in assessment by a variety of stakeholders including learners and frontline assessors. To meaningfully move forward, the authors assert that the reestablishment of trust should be foundational to the next era of assessment. In our actions and interventions, it is imperative that medical education leaders address and build trust in assessment at a systems level. To that end, the authors first review tenets on the social contextualization of assessment and its linkage to trust and discuss consequences should the current state of low trust continue. The authors then posit that trusting and trustworthy relationships can exist at individual as well as organizational and systems levels. Finally, the authors propose a framework to build trust at multiple levels in a future assessment system; one that invites and supports professional and human growth and has the potential to position assessment as a fundamental component of renegotiating the social contract between medical education and the health of the public.

  View details for DOI 10.5334/pme.1110

  View details for PubMedID 38274558

• Organizational Factors in Clinical Data Sharing for Artificial Intelligence in Health Care. JAMA network open Youssef, A., Ng, M. Y., Long, J., Hernandez-Boussard, T., Shah, N., Miner, A., Larson, D., Langlotz, C. P. 2023; 6 (12): e2348422

  Abstract

  Limited sharing of data sets that accurately represent disease and patient diversity limits the generalizability of artificial intelligence (AI) algorithms in health care.To explore the factors associated with organizational motivation to share health data for AI development.This qualitative study investigated organizational readiness for sharing health data across the academic, governmental, nonprofit, and private sectors. Using a multiple case studies approach, 27 semistructured interviews were conducted with leaders in data-sharing roles from August 29, 2022, to January 9, 2023. The interviews were conducted in the English language using a video conferencing platform. Using a purposive and nonprobabilistic sampling strategy, 78 individuals across 52 unique organizations were identified. Of these, 35 participants were enrolled. Participant recruitment concluded after 27 interviews, as theoretical saturation was reached and no additional themes emerged.Concepts defining organizational readiness for data sharing and the association between data-sharing factors and organizational behavior were mapped through iterative qualitative analysis to establish a framework defining organizational readiness for sharing clinical data for AI development.Interviews included 27 leaders from 18 organizations (academia: 10, government: 7, nonprofit: 8, and private: 2). Organizational readiness for data sharing centered around 2 main constructs: motivation and capabilities. Motivation related to the alignment of an organization's values with data-sharing priorities and was associated with its engagement in data-sharing efforts. However, organizational motivation could be modulated by extrinsic incentives for financial or reputational gains. Organizational capabilities comprised infrastructure, people, expertise, and access to data. Cross-sector collaboration was a key strategy to mitigate barriers to access health data.This qualitative study identified sector-specific factors that may affect the data-sharing behaviors of health organizations. External incentives may bolster cross-sector collaborations by helping overcome barriers to accessing health data for AI development. The findings suggest that tailored incentives may boost organizational motivation and facilitate sustainable flow of health data for AI development.

  View details for DOI 10.1001/jamanetworkopen.2023.48422

  View details for PubMedID 38113040

• Trends in Influenza Vaccination Rates among a Medicaid Population from 2016 to 2021. Vaccines Naderalvojoud, B., Shah, N. D., Mutanga, J. N., Belov, A., Staiger, R., Chen, J. H., Whitaker, B., Hernandez-Boussard, T. 2023; 11 (11)

  Abstract

  Seasonal influenza is a leading cause of death in the U.S., causing significant morbidity, mortality, and economic burden. Despite the proven efficacy of vaccinations, rates remain notably low, especially among Medicaid enrollees. Leveraging Medicaid claims data, this study characterizes influenza vaccination rates among Medicaid enrollees and aims to elucidate factors influencing vaccine uptake, providing insights that might also be applicable to other vaccine-preventable diseases, including COVID-19. This study used Medicaid claims data from nine U.S. states (2016-2021], encompassing three types of claims: fee-for-service, major Medicaid managed care plan, and combined. We included Medicaid enrollees who had an in-person healthcare encounter during an influenza season in this period, excluding those under 6 months of age, over 65 years, or having telehealth-only encounters. Vaccination was the primary outcome, with secondary outcomes involving in-person healthcare encounters. Chi-square tests, multivariable logistic regression, and Fisher's exact test were utilized for statistical analysis. A total of 20,868,910 enrollees with at least one healthcare encounter in at least one influenza season were included in the study population between 2016 and 2021. Overall, 15% (N = 3,050,471) of enrollees received an influenza vaccine between 2016 and 2021. During peri-COVID periods, there was an increase in vaccination rates among enrollees compared to pre-COVID periods, from 14% to 16%. Children had the highest influenza vaccination rates among all age groups at 29%, whereas only 17% were of 5-17 years, and 10% were of the 18-64 years were vaccinated. We observed differences in the likelihood of receiving the influenza vaccine among enrollees based on their health conditions and medical encounters. In a study of Medicaid enrollees across nine states, 15% received an influenza vaccine from July 2016 to June 2021. Vaccination rates rose annually, peaking during peri-COVID seasons. The highest uptake was among children (6 months-4 years), and the lowest was in adults (18-64 years). Female gender, urban residency, and Medicaid-managed care affiliation positively influenced uptake. However, mental health and substance abuse disorders decreased the likelihood. This study, reliant on Medicaid claims data, underscores the need for outreach services.

  View details for DOI 10.3390/vaccines11111712

  View details for PubMedID 38006044

• Postoperative opioid prescribing patients with diabetes: Opportunities for personalized pain management. PloS one Zammit, A., Coquet, J., Hah, J., El Hajouji, O., Asch, S. M., Carroll, I., Curtin, C. M., Hernandez-Boussard, T. 2023; 18 (8): e0287697

  Abstract

  Opioids are commonly prescribed for postoperative pain, but may lead to prolonged use and addiction. Diabetes impairs nerve function, complicates pain management, and makes opioid prescribing particularly challenging.This retrospective observational study included a cohort of postoperative patients from a multisite academic health system to assess the relationship between diabetes, pain, and prolonged opioid use (POU), 2008-2019. POU was defined as a new opioid prescription 3-6 months after discharge. The odds that a patient had POU was assessed using multivariate logistic regression controlling for patient factors (e.g., demographic and clinical factors, as well as prior pain and opiate use).A total of 43,654 patients were included, 12.4% with diabetes. Patients with diabetes had higher preoperative pain scores (2.1 vs 1.9, p<0.001) and lower opioid naïve rates (58.7% vs 68.6%, p<0.001). Following surgery, patients with diabetes had higher rates of POU (17.7% vs 12.7%, p<0.001) despite receiving similar opioid prescriptions at discharge. Patients with Type I diabetes were more likely to have POU compared to other patients (Odds Ratio [OR]: 2.22; 95% Confidence Interval [CI]:1.69-2.90 and OR:1.44, CI: 1.33-1.56, respectively).In conclusion, surgical patients with diabetes are at increased risk for POU even after controlling for likely covariates, yet they receive similar postoperative opiate therapy. The results suggest a more tailored approach to diabetic postoperative pain management is warranted.

  View details for DOI 10.1371/journal.pone.0287697

  View details for PubMedID 37616195

  View details for PubMedCentralID PMC10449216

• Prediction of opioid-related outcomes in a medicaid surgical population: Evidence to guide postoperative opiate therapy and monitoring. PLoS computational biology El Hajouji, O., Sun, R. S., Zammit, A., Humphreys, K., Asch, S. M., Carroll, I., Curtin, C. M., Hernandez-Boussard, T. 2023; 19 (8): e1011376

  Abstract

  BACKGROUND: Treatment of surgical pain is a common reason for opioid prescriptions. Being able to predict which patients are at risk for opioid abuse, dependence, and overdose (opioid-related adverse outcomes [OR-AE]) could help physicians make safer prescription decisions. We aimed to develop a machine-learning algorithm to predict the risk of OR-AE following surgery using Medicaid data with external validation across states.METHODS: Five machine learning models were developed and validated across seven US states (90-10 data split). The model output was the risk of OR-AE 6-months following surgery. The models were evaluated using standard metrics and area under the receiver operating characteristic curve (AUC) was used for model comparison. We assessed calibration for the top performing model and generated bootstrap estimations for standard deviations. Decision curves were generated for the top-performing model and logistic regression.RESULTS: We evaluated 96,974 surgical patients aged 15 and 64. During the 6-month period following surgery, 10,464 (10.8%) patients had an OR-AE. Outcome rates were significantly higher for patients with depression (17.5%), diabetes (13.1%) or obesity (11.1%). The random forest model achieved the best predictive performance (AUC: 0.877; F1-score: 0.57; recall: 0.69; precision:0.48). An opioid disorder diagnosis prior to surgery was the most important feature for the model, which was well calibrated and had good discrimination.CONCLUSIONS: A machine learning models to predict risk of OR-AE following surgery performed well in external validation. This work could be used to assist pain management following surgery for Medicaid beneficiaries and supports a precision medicine approach to opioid prescribing.

  View details for DOI 10.1371/journal.pcbi.1011376

  View details for PubMedID 37578969

• Preoperative Versus Perioperative Risk Factors for Delayed Pain and Opioid Cessation After Total Joint Arthroplasty: A Prospective Cohort Study. Pain and therapy Hah, J. M., Vialard, J. D., Efron, B., Mackey, S. C., Carroll, I. R., Amanatullah, D. F., Narasimhan, B., Hernandez-Boussard, T. 2023

  Abstract

  The evolution of pre- versus postoperative risk factors remains unknown in the development of persistent postoperative pain and opioid use. We identified preoperative versus comprehensive perioperative models of delayed pain and opioid cessation after total joint arthroplasty including time-varying postoperative changes in emotional distress. We hypothesized that time-varying longitudinal measures of postoperative psychological distress, as well as pre- and postoperative use of opioids would be the most significant risk factors for both outcomes.A prospective cohort of 188 patients undergoing total hip or knee arthroplasty at Stanford Hospital completed baseline pain, opioid use, and emotional distress assessments. After surgery, a modified Brief Pain Inventory was assessed daily for 3 months, weekly thereafter up to 6 months, and monthly thereafter up to 1 year. Emotional distress and pain catastrophizing were assessed weekly to 6 months, then monthly thereafter. Stepwise multivariate time-varying Cox regression modeled preoperative variables alone, followed by all perioperative variables (before and after surgery) with time to postoperative opioid and pain cessation.The median time to opioid and pain cessation was 54 and 152 days, respectively. Preoperative total daily oral morphine equivalent use (hazard ratio-HR 0.97; 95% confidence interval-CI 0.96-0.98) was significantly associated with delayed postoperative opioid cessation in the perioperative model. In contrast, time-varying postoperative factors: elevated PROMIS (Patient-Reported Outcomes Measurement Information System) depression scores (HR 0.92; 95% CI 0.87-0.98), and higher Pain Catastrophizing Scale scores (HR 0.85; 95% CI 0.75-0.97) were independently associated with delayed postoperative pain resolution in the perioperative model.These findings highlight preoperative opioid use as a key determinant of delayed postoperative opioid cessation, while postoperative elevations in depressive symptoms and pain catastrophizing are associated with persistent pain after total joint arthroplasty providing the rationale for continued risk stratification before and after surgery to identify patients at highest risk for these distinct outcomes. Interventions targeting these perioperative risk factors may prevent prolonged postoperative pain and opioid use.

  View details for DOI 10.1007/s40122-023-00543-9

  View details for PubMedID 37556071

  View details for PubMedCentralID 7317603

• Patient-reported distress at a cancer center during the COVID-19 pandemic. Scientific reports Shah, M. P., Rosenthal, S. W., Roy, M., Khaki, A. R., Hernandez-Boussard, T., Ramchandran, K. 2023; 13 (1): 9581

  Abstract

  Assessments of health-related quality of life (HRQOL) are conducted by health systems to improve patient-centered care. Studies have shown that the COVID-19 pandemic poses unique stressors for patients with cancer. This study investigates change in self-reported global health scores in patients with cancer before and during the COVID-19 pandemic. In this single-institution retrospective cohort study, patients who completed the Patient-Reported Outcomes Measurement Information System (PROMIS) at a comprehensive cancer center before and during the COVID-19 pandemic were identified. Surveys were analyzed to assess change in the global mental health (GMH) and global physical health (GPH) scores at different time periods (pre-COVID: 3/1/5/2019-3/15/2020, surge1: 6/17/2020-9/7/2020, valley1: 9/8/2020-11/16/2020, surge2: 11/17/2020-3/2/2021, and valley2: 3/3/2021-6/15/2021). A total of 25,192 surveys among 7209 patients were included in the study. Mean GMH score for patients before the COVID-19 pandemic (50.57) was similar to those during various periods during the pandemic: surge1 (48.82), valley1 (48.93), surge2 (48.68), valley2 (49.19). Mean GPH score was significantly higher pre-COVID (42.46) than during surge1 (36.88), valley1 (36.90), surge2 (37.33) and valley2 (37.14). During the pandemic, mean GMH (49.00) and GPH (37.37) scores obtained through in-person were similar to mean GMH (48.53) and GPH (36.94) scores obtained through telehealth. At this comprehensive cancer center, patients with cancer reported stable mental health and deteriorating physical health during the COVID-19 pandemic as indicated by the PROMIS survey. Modality of the survey (in-person versus telehealth) did not affect scores.

  View details for DOI 10.1038/s41598-023-36025-3

  View details for PubMedID 37311790

  View details for PubMedCentralID 7450263

• Natural language processing to identify reasons for sex disparity in statin prescriptions. American journal of preventive cardiology Witting, C., Azizi, Z., Gomez, S. E., Zammit, A., Sarraju, A., Ngo, S., Hernandez-Boussard, T., Rodriguez, F. 2023; 14: 100496

  Abstract

  Background: Statins are the cornerstone of treatment of patients with atherosclerotic cardiovascular disease (ASCVD). Despite this, multiple studies have shown that women with ASCVD are less likely to be prescribed statins than men. The objective of this study was to use Natural Language Processing (NLP) to elucidate factors contributing to this disparity.Methods: Our cohort included adult patients with two or more encounters between 2014 and 2021 with an ASCVD diagnosis within a multisite electronic health record (EHR) in Northern California. After reviewing structured EHR prescription data, we used a benchmark deep learning NLP approach, Clinical Bidirectional Encoder Representations from Transformers (BERT), to identify and interpret discussions of statin prescriptions documented in clinical notes. Clinical BERT was evaluated against expert clinician review in 20% test sets.Results: There were 88,913 patients with ASCVD (mean age 67.8±13.1 years) and 35,901 (40.4%) were women. Women with ASCVD were less likely to be prescribed statins compared with men (56.6%vs 67.6%, p <0.001), and, when prescribed, less likely to be prescribed guideline-directed high-intensity dosing (41.4%vs 49.8%, p <0.001). These disparities were more pronounced among younger patients, patients with private insurance, and those for whom English is their preferred language. Among those not prescribed statins, women were less likely than men to have statins mentioned in their clinical notes (16.9%vs 19.1%, p <0.001). Women were less likely than men to have statin use reported in clinical notes despite absence of recorded prescription (32.8%vs 42.6%, p <0.001). Women were slightly more likely than men to have statin intolerance documented in structured data or clinical notes (6.0%vs 5.3%, p=0.003).Conclusions: Women with ASCVD were less likely to be prescribed guideline-directed statins compared with men. NLP identified additional sex-based statin disparities and reasons for statin non-prescription in clinical notes of patients with ASCVD.

  View details for DOI 10.1016/j.ajpc.2023.100496

  View details for PubMedID 37128554

• A Bayesian approach to predictive uncertainty in chemotherapy patients at risk of acute care utilization. EBioMedicine Fanconi, C., de Hond, A., Peterson, D., Capodici, A., Hernandez-Boussard, T. 2023; 92: 104632

  Abstract

  BACKGROUND: Machine learning (ML) predictions are becoming increasingly integrated into medical practice. One commonly used method, ℓ1-penalised logistic regression (LASSO), can estimate patient risk for disease outcomes but is limited by only providing point estimates. Instead, Bayesian logistic LASSO regression (BLLR) models provide distributions for risk predictions, giving clinicians a better understanding of predictive uncertainty, but they are not commonly implemented.METHODS: This study evaluates the predictive performance of different BLLRs compared to standard logistic LASSO regression, using real-world, high-dimensional, structured electronic health record (EHR) data from cancer patients initiating chemotherapy at a comprehensive cancer centre. Multiple BLLR models were compared against a LASSO model using an 80-20 random split using 10-fold cross-validation to predict the risk of acute care utilization (ACU) after starting chemotherapy.FINDINGS: This study included 8439 patients. The LASSO model predicted ACU with an area under the receiver operating characteristic curve (AUROC) of 0.806 (95% CI: 0.775-0.834). BLLR with a Horseshoe+prior and a posterior approximated by Metropolis-Hastings sampling showed similar performance: 0.807 (95% CI: 0.780-0.834) and offers the advantage of uncertainty estimation for each prediction. In addition, BLLR could identify predictions too uncertain to be automatically classified. BLLR uncertainties were stratified by different patient subgroups, demonstrating that predictive uncertainties significantly differ across race, cancer type, and stage.INTERPRETATION: BLLRs are a promising yet underutilised tool that increases explainability by providing risk estimates while offering a similar level of performance to standard LASSO-based models. Additionally, these models can identify patient subgroups with higher uncertainty, which can augment clinical decision-making.FUNDING: This work was supported in part by the National Library Of Medicine of the National Institutes of Health under Award Number R01LM013362. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

  View details for DOI 10.1016/j.ebiom.2023.104632

  View details for PubMedID 37269570

• Predicting Depression Risk in Patients with Cancer Using Multimodal Data. Studies in health technology and informatics de Hond, A., van Buchem, M., Fanconi, C., Roy, M., Blayney, D., Kant, I., Steyerberg, E., Hernandez-Boussard, T. 2023; 302: 817-818

  Abstract

  When patients with cancer develop depression, it is often left untreated. We developed a prediction model for depression risk within the first month after starting cancer treatment using machine learning and Natural Language Processing (NLP) models. The LASSO logistic regression model based on structured data performed well, whereas the NLP model based on only clinician notes did poorly. After further validation, prediction models for depression risk could lead to earlier identification and treatment of vulnerable patients, ultimately improving cancer care and treatment adherence.

  View details for DOI 10.3233/SHTI230274

  View details for PubMedID 37203503

• Perspectives on validation of clinical predictive algorithms. NPJ digital medicine de Hond, A. A., Shah, V. B., Kant, I. M., Van Calster, B., Steyerberg, E. W., Hernandez-Boussard, T. 2023; 6 (1): 86

  View details for DOI 10.1038/s41746-023-00832-9

  View details for PubMedID 37149704

• Multimodal data fusion for cancer biomarker discovery with deep learning NATURE MACHINE INTELLIGENCE Steyaert, S., Pizurica, M., Nagaraj, D., Khandelwal, P., Hernandez-Boussard, T., Gentles, A. J., Gevaert, O. 2023

  View details for DOI 10.1038/s42256-023-00633-5

  View details for Web of Science ID 000963904900003

• Artificial Intelligence-Enabled Analysis of Statin-Related Topics and Sentiments on Social Media. JAMA network open Somani, S., van Buchem, M. M., Sarraju, A., Hernandez-Boussard, T., Rodriguez, F. 2023; 6 (4): e239747

  Abstract

  Despite compelling evidence that statins are safe, are generally well tolerated, and reduce cardiovascular events, statins are underused even in patients with the highest risk. Social media may provide contemporary insights into public perceptions about statins.To characterize and classify public perceptions about statins that were gleaned from more than a decade of statin-related discussions on Reddit, a widely used social media platform.This qualitative study analyzed all statin-related discussions on the social media platform that were dated between January 1, 2009, and July 12, 2022. Statin- and cholesterol-focused communities, were identified to create a list of statin-related discussions. An artificial intelligence (AI) pipeline was developed to cluster these discussions into specific topics and overarching thematic groups. The pipeline consisted of a semisupervised natural language processing model (BERT [Bidirectional Encoder Representations from Transformers]), a dimensionality reduction technique, and a clustering algorithm. The sentiment for each discussion was labeled as positive, neutral, or negative using a pretrained BERT model.Statin-related posts and comments containing the terms statin and cholesterol.Statin-related topics and thematic groups.A total of 10 233 unique statin-related discussions (961 posts and 9272 comments) from 5188 unique authors were identified. The number of statin-related discussions increased by a mean (SD) of 32.9% (41.1%) per year. A total of 100 discussion topics were identified and were classified into 6 overarching thematic groups: (1) ketogenic diets, diabetes, supplements, and statins; (2) statin adverse effects; (3) statin hesitancy; (4) clinical trial appraisals; (5) pharmaceutical industry bias and statins; and (6) red yeast rice and statins. The sentiment analysis revealed that most discussions had a neutral (66.6%) or negative (30.8%) sentiment.Results of this study demonstrated the potential of an AI approach to analyze large, contemporary, publicly available social media data and generate insights into public perceptions about statins. This information may help guide strategies for addressing barriers to statin use and adherence.

  View details for DOI 10.1001/jamanetworkopen.2023.9747

  View details for PubMedID 37093597

• Multimodal data fusion for cancer biomarker discovery with deep learning. Nature machine intelligence Steyaert, S., Pizurica, M., Nagaraj, D., Khandelwal, P., Hernandez-Boussard, T., Gentles, A. J., Gevaert, O. 2023; 5 (4): 351-362

  Abstract

  Technological advances now make it possible to study a patient from multiple angles with high-dimensional, high-throughput multi-scale biomedical data. In oncology, massive amounts of data are being generated ranging from molecular, histopathology, radiology to clinical records. The introduction of deep learning has significantly advanced the analysis of biomedical data. However, most approaches focus on single data modalities leading to slow progress in methods to integrate complementary data types. Development of effective multimodal fusion approaches is becoming increasingly important as a single modality might not be consistent and sufficient to capture the heterogeneity of complex diseases to tailor medical care and improve personalised medicine. Many initiatives now focus on integrating these disparate modalities to unravel the biological processes involved in multifactorial diseases such as cancer. However, many obstacles remain, including lack of usable data as well as methods for clinical validation and interpretation. Here, we cover these current challenges and reflect on opportunities through deep learning to tackle data sparsity and scarcity, multimodal interpretability, and standardisation of datasets.

  View details for DOI 10.1038/s42256-023-00633-5

  View details for PubMedID 37693852

  View details for PubMedCentralID PMC10484010

• Identifying Reasons for Statin Nonuse in Patients With Diabetes Using Deep Learning of Electronic Health Records. Journal of the American Heart Association Sarraju, A., Zammit, A., Ngo, S., Witting, C., Hernandez-Boussard, T., Rodriguez, F. 2023: e028120

  Abstract

  Background Statins are guideline-recommended medications that reduce cardiovascular events in patients with diabetes. Yet, statin use is concerningly low in this high-risk population. Identifying reasons for statin nonuse, which are typically described in unstructured electronic health record data, can inform targeted system interventions to improve statin use. We aimed to leverage a deep learning approach to identify reasons for statin nonuse in patients with diabetes. Methods and Results Adults with diabetes and no statin prescriptions were identified from a multiethnic, multisite Northern California electronic health record cohort from 2014 to 2020. We used a benchmark deep learning natural language processing approach (Clinical Bidirectional Encoder Representations from Transformers) to identify statin nonuse and reasons for statin nonuse from unstructured electronic health record data. Performance was evaluated against expert clinician review from manual annotation of clinical notes and compared with other natural language processing approaches. Of 33 461 patients with diabetes (mean age 59±15 years, 49% women, 36% White patients, 24% Asian patients, and 15% Hispanic patients), 47% (15 580) had no statin prescriptions. From unstructured data, Clinical Bidirectional Encoder Representations from Transformers accurately identified statin nonuse (area under receiver operating characteristic curve [AUC] 0.99 [0.98-1.0]) and key patient (eg, side effects/contraindications), clinician (eg, guideline-discordant practice), and system reasons (eg, clinical inertia) for statin nonuse (AUC 0.90 [0.86-0.93]) and outperformed other natural language processing approaches. Reasons for nonuse varied by clinical and demographic characteristics, including race and ethnicity. Conclusions A deep learning algorithm identified statin nonuse and actionable reasons for statin nonuse in patients with diabetes. Findings may enable targeted interventions to improve guideline-directed statin use and be scaled to other evidence-based therapies.

  View details for DOI 10.1161/JAHA.122.028120

  View details for PubMedID 36974740

• TOPICS AND SENTIMENTS AROUND STATINS ON REDDIT USING ARTIFICIAL INTELLIGENCE Somani, S., Van Buchem, M., Sarraju, A., Hernandez-Boussard, T., Rodriguez, F. ELSEVIER SCIENCE INC. 2023: 1637

  View details for Web of Science ID 000990866101649

• Correction to: Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review. Journal of nephrology Sanmarchi, F., Fanconi, C., Golinelli, D., Gori, D., Hernandez-Boussard, T., Capodici, A. 2023

  View details for DOI 10.1007/s40620-023-01609-9

  View details for PubMedID 36877370

• A deep-learning algorithm to classify skin lesions from mpox virus infection. Nature medicine Thieme, A. H., Zheng, Y., Machiraju, G., Sadee, C., Mittermaier, M., Gertler, M., Salinas, J. L., Srinivasan, K., Gyawali, P., Carrillo-Perez, F., Capodici, A., Uhlig, M., Habenicht, D., Loser, A., Kohler, M., Schuessler, M., Kaul, D., Gollrad, J., Ma, J., Lippert, C., Billick, K., Bogoch, I., Hernandez-Boussard, T., Geldsetzer, P., Gevaert, O. 2023

  Abstract

  Undetected infection and delayed isolation of infected individuals are key factors driving the monkeypox virus (now termed mpox virus or MPXV) outbreak. To enable earlier detection of MPXV infection, we developed an image-based deep convolutional neural network (named MPXV-CNN) for the identification of the characteristic skin lesions caused by MPXV. We assembled a dataset of 139,198 skin lesion images, split into training/validation and testing cohorts, comprising non-MPXV images (n=138,522) from eight dermatological repositories and MPXV images (n=676) from the scientific literature, news articles, social media and a prospective cohort of the Stanford University Medical Center (n=63 images from 12 patients, all male). In the validation and testing cohorts, the sensitivity of the MPXV-CNN was 0.83 and 0.91, the specificity was 0.965 and 0.898 and the area under the curve was 0.967 and 0.966, respectively. In the prospective cohort, the sensitivity was 0.89. The classification performance of the MPXV-CNN was robust across various skin tones and body regions. To facilitate the usage of the algorithm, we developed a web-based app by which the MPXV-CNN can be accessed for patient guidance. The capability of the MPXV-CNN for identifying MPXV lesions has the potential to aid in MPXV outbreak mitigation.

  View details for DOI 10.1038/s41591-023-02225-7

  View details for PubMedID 36864252

• Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review. Journal of nephrology Sanmarchi, F., Fanconi, C., Golinelli, D., Gori, D., Hernandez-Boussard, T., Capodici, A. 2023

  Abstract

  OBJECTIVES: In this systematic review we aimed at assessing how artificial intelligence (AI), including machine learning (ML) techniques have been deployed to predict, diagnose, and treat chronic kidney disease (CKD). We systematically reviewed the available evidence on theseinnovative techniques to improve CKD diagnosis and patient management.METHODS: We included English language studies retrieved from PubMed.The review istherefore to be classified as a "rapid review", since it includes one database only, and has language restrictions; the novelty and importanceof the issue make missing relevant papers unlikely. We extracted 16 variables, including: main aim, studied population, data source, sample size, problem type (regression, classification), predictors used, and performance metrics.We followedthe Preferred Reporting Items for Systematic Reviews (PRISMA) approach; all main steps were done in duplicate.The review was registered on PROSPERO.RESULTS: From a total of 648 studies initially retrieved, 68 articles met the inclusioncriteria. Models, as reported by authors, performed well, but the reported metrics were not homogeneous across articles and therefore direct comparison was not feasible. The most common aim was prediction of prognosis, followed by diagnosis of CKD. Algorithm generalizability, and testing on diverse populations was rarely taken into account. Furthermore, the clinical evaluation and validation of the models/algorithms was perused; only a fraction of the included studies, 6 out of 68, were performed in a clinical context.CONCLUSIONS: Machine learning is apromising toolfor the prediction of risk, diagnosis, and therapy management for CKDpatients. Nonetheless, future work is needed to address the interpretability, generalizability, and fairness of the models to ensure the safe application of such technologies in routine clinical practice.

  View details for DOI 10.1007/s40620-023-01573-4

  View details for PubMedID 36786976

• Predicting premature discontinuation of medication for opioid use disorder from electronic medical records. AMIA ... Annual Symposium proceedings. AMIA Symposium Lopez, I., Fouladvand, S., Kollins, S., Chen, C. A., Bertz, J., Hernandez-Boussard, T., Lembke, A., Humphreys, K., Miner, A. S., Chen, J. H. 2023; 2023: 1067-1076

  Abstract

  Medications such as buprenorphine-naloxone are among the most effective treatments for opioid use disorder, but limited retention in treatment limits long-term outcomes. In this study, we assess the feasibility of a machine learning model to predict retention vs. attrition in medication for opioid use disorder (MOUD) treatment using electronic medical record data including concepts extracted from clinical notes. A logistic regression classifier was trained on 374 MOUD treatments with 68% resulting in potential attrition. On a held-out test set of 157 events, the full model achieved an area under the receiver operating characteristic curve (AUROC) of 0.77 (95% CI: 0.64-0.90) and AUROC of 0.74 (95% CI: 0.62-0.87) with a limited model using only structured EMR data. Risk prediction for opioid MOUD retention vs. attrition is feasible given electronic medical record data, even without necessarily incorporating concepts extracted from clinical notes.

  View details for PubMedID 38222349

  View details for PubMedCentralID PMC10785878

• Improving machine learning with ensemble learning on observational healthcare data. AMIA ... Annual Symposium proceedings. AMIA Symposium Naderalvojoud, B., Hernandez-Boussard, T. 2023; 2023: 521-529

  Abstract

  Ensemble learning is a powerful technique for improving the accuracy and reliability of prediction models, especially in scenarios where individual models may not perform well. However, combining models with varying accuracies may not always improve the final prediction results, as models with lower accuracies may obscure the results of models with higher accuracies. This paper addresses this issue and answers the question of when an ensemble approach outperforms individual models for prediction. As a result, we propose an ensemble model for predicting patients at risk of postoperative prolonged opioid. The model incorporates two machine learning models that are trained using different covariates, resulting in high precision and recall. Our study, which employs five different machine learning algorithms, shows that the proposed approach significantly improves the final prediction results in terms of AUROC and AUPRC.

  View details for PubMedID 38222353

  View details for PubMedCentralID PMC10785929

• Natural Language Processing Methods to Identify Oncology Patients at High Risk for Acute Care with Clinical Notes. AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Fanconi, C., van Buchem, M., Hernandez-Boussard, T. 2023; 2023: 138-147

  Abstract

  Clinical notes are an essential component of a health record. This paper evaluates how natural language processing (NLP) can be used to identify the risk of acute care use (ACU) in oncology patients, once chemotherapy starts. Risk prediction using structured health data (SHD) is now standard, but predictions using free-text formats are complex. This paper explores the use of free-text notes for the prediction of ACU in leu of SHD. Deep Learning models were compared to manually engineered language features. Results show that SHD models minimally outperform NLP models; an ℓ1-penalised logistic regression with SHD achieved a C-statistic of 0.748 (95%-CI: 0.735, 0.762), while the same model with language features achieved 0.730 (95%-CI: 0.717, 0.745) and a transformer-based model achieved 0.702 (95%-CI: 0.688, 0.717). This paper shows how language models can be used in clinical applications and underlines how risk bias is different for diverse patient groups, even using only free-text data.

  View details for PubMedID 37350895

• Censored Fairness through Awareness Zhang, W., Hernandez-Boussard, T., Weiss, J., Williams, B., Chen, Y., Neville, J. ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. 2023: 14611-14619

  View details for Web of Science ID 001243755000061

• Changes in Medicaid enrollment during the COVID-19 pandemic across 6 states. Medicine Sun, R., Staiger, B., Chan, A., Baker, L. C., Hernandez-Boussard, T. 2022; 101 (52): e32487

  Abstract

  The coronavirus disease 2019 public health emergency (PHE) caused extensive job loss and loss of employer-sponsored insurance. State Medicaid programs experienced a related increase in enrollment during the PHE. However, the composition of enrollment and enrollee changes during the pandemic is unknown. This study examined changes in Medicaid enrollment and population characteristics during the PHE. A retrospective study documenting changes in Medicaid new enrollment and disenrollment, and enrollee characteristics between March and October 2020 compared to the same time in 2019 using full-state Medicaid populations from 6 states of a wide geographical region. The primary outcomes were Medicaid enrollment and disenrollment during the PHE. New enrollment included persons enrolled in Medicaid between March and October 2020 who were not enrolled in January or February, 2020. Disenrollment included persons who were enrolled in March of 2020 but not enrolled in October 2020. The study included 8.50 million Medicaid enrollees in 2020 and 8.46 million in 2019. Overall, enrollment increased by 13.0% (1.19 million) in the selected states during the PHE compared to 2019. New enrollment accounted for 24.9% of the relative increase, while the remaining 75.1% was due to disenrollment. A larger proportion of new enrollment in 2020 was among adults aged 27 to 44 (28.3% vs 23.6%), Hispanics (34.3% vs 32.5%) and in the financial needy (44.0% vs 39.0%) category compared to 2019. Disenrollment included a larger proportion of older adults (26.1% vs 8.1%) and non-Hispanics (70.3% vs 66.4%) than in 2019. Medicaid enrollment grew considerably during the PHE, and most enrollment growth was attributed to decreases in disenrollment rather than increases in new enrollment. Our results highlight the impact of coronavirus disease 2019 on state health programs and can guide federal and state budgetary planning once the PHE ends.

  View details for DOI 10.1097/MD.0000000000032487

  View details for PubMedID 36596028

• Predictors of Incident HeartFailure Diagnosis Setting: Insights From the Veterans Affairs Healthcare System. JACC. Heart failure Tisdale, R. L., Fan, J., Calma, J., Cyr, K., Podchiyska, T., Stafford, R. S., Maron, D. J., Hernandez-Boussard, T., Ambrosy, A., Heidenreich, P. A., Sandhu, A. T. 2022

  Abstract

  BACKGROUND: Early recognition of heart failure (HF) can reduce morbidity, yet HF is often diagnosed only after symptoms require urgent treatment.OBJECTIVES: The authors sought to describe predictors of HF diagnosis in the acute care vs outpatient setting within the Veterans Health Administration (VHA).METHODS: The authors estimated whether incident HF diagnoses occurred in acute care (inpatient hospital or emergency department) vs outpatient settings within the VHA between 2014 and 2019. After excluding new-onset HF potentially caused by acute concurrent conditions, they identified sociodemographic and clinical variables associated with diagnosis setting and assessed variation across 130 VHA facilities using multivariable regression analysis.RESULTS: The authors identified 303,632 patients with new HF, with 160,454 (52.8%) diagnosed in acute care settings. In the prior year, 44% had HF symptoms and 11% had a natriuretic peptide tested, 88% of which were elevated. Patients with housing insecurity and high neighborhood social vulnerability had higher odds of acute care diagnosis (adjusted odds ratio: 1.22 [95%CI: 1.17-1.27] and 1.17 [95%CI: 1.14-1.21], respectively) adjusting for medical comorbidities. Better outpatient quality of care (blood pressure control and cholesterol and diabetes monitoring within the prior 2 years) predicted a lower odds of acute care diagnosis. Likelihood of acute care HF diagnosis varied from 41% to 68% across facilities after adjusting for patient-level risk factors.CONCLUSIONS: Many first HF diagnoses occur in the acute care setting, especially among socioeconomically vulnerable populations. Better outpatient care was associated with lower rates of an acute care diagnosis. These findings highlight opportunities for timelier HF diagnosis that may improve patient outcomes.

  View details for DOI 10.1016/j.jchf.2022.11.013

  View details for PubMedID 36881392

• The AI life cycle: a holistic approach to creating ethical AI for health decisions. Nature medicine Ng, M. Y., Kapur, S., Blizinsky, K. D., Hernandez-Boussard, T. 2022

  View details for DOI 10.1038/s41591-022-01993-y

  View details for PubMedID 36163298

• Leveraging weak supervision to perform named entity recognition in electronic health records progress notes to identify the ophthalmology exam. International journal of medical informatics Wang, S. Y., Huang, J., Hwang, H., Hu, W., Tao, S., Hernandez-Boussard, T. 2022; 167: 104864

  Abstract

  To develop deep learning models to recognize ophthalmic examination components from clinical notes in electronic health records (EHR) using a weak supervision approach.A corpus of 39,099 ophthalmology notes weakly labeled for 24 examination entities was assembled from the EHR of one academic center. Four pre-trained transformer-based language models (DistilBert, BioBert, BlueBert, and ClinicalBert) were fine-tuned to this named entity recognition task and compared to a baseline regular expression model. Models were evaluated on the weakly labeled test dataset, a human-labeled sample of that set, and a human-labeled independent dataset.On the weakly labeled test set, all transformer-based models had recall > 0.93, with precision varying from 0.815 to 0.843. The baseline model had lower recall (0.769) and precision (0.682). On the human-annotated sample, the baseline model had high recall (0.962, 95 % CI 0.955-0.067) with variable precision across entities (0.081-0.999). Bert models had recall ranging from 0.771 to 0.831, and precision >=0.973. On the independent dataset, precision was 0.926 and recall 0.458 for BlueBert. The baseline model had better recall (0.708, 95 % CI 0.674-0.738) but worse precision (0.399, 95 % CI -0.352-0.451).We developed the first deep learning system to recognize eye examination components from clinical notes, leveraging a novel opportunity for weak supervision. Transformer-based models had high precision on human-annotated labels, whereas the baseline model had poor precision but higher recall. This system may be used to improve cohort and feature identification using free-text notes.Our weakly supervised approach may help amass large datasets of domain-specific entities from EHRs in many fields.

  View details for DOI 10.1016/j.ijmedinf.2022.104864

  View details for PubMedID 36179600

• Picture a data scientist: a call to action for increasing diversity, equity, and inclusion in the age of AI. Journal of the American Medical Informatics Association : JAMIA de Hond, A. A., van Buchem, M. M., Hernandez-Boussard, T. 2022

  Abstract

  The lack of diversity, equity, and inclusion continues to hamper the artificial intelligence (AI) field and is especially problematic for healthcare applications. In this article, we expand on the need for diversity, equity, and inclusion, specifically focusing on the composition of AI teams. We call to action leaders at all levels to make team inclusivity and diversity the centerpieces of AI development, not the afterthought. These recommendations take into consideration mitigation at several levels, including outreach programs at the local level, diversity statements at the academic level, and regulatory steps at the federal level.

  View details for DOI 10.1093/jamia/ocac156

  View details for PubMedID 36048021

• Named entity recognition in ophthalmology clinical progress notes: What's in the eye exam? Wang, S. Y., Huang, J., Hwang, H., Hu, W., Hernandez-Boussard, T. ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2022

  View details for Web of Science ID 000844401302060

• Patient-reported distress at a cancer center during the COVID-19 pandemic. Shah, M. P., Rosenthal, S., Roy, M., Khaki, A., Hernandez-Boussard, T., Ramchandran, K. LIPPINCOTT WILLIAMS & WILKINS. 2022: E18644

  View details for Web of Science ID 000863680303793

• A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams. JCO clinical cancer informatics Huang, R. J., Kwon, N. S., Tomizawa, Y., Choi, A. Y., Hernandez-Boussard, T., Hwang, J. H. 2022; 6: e2200039

  Abstract

  Noncardia gastric cancer (NCGC) is a leading cause of global cancer mortality, and is often diagnosed at advanced stages. Development of NCGC risk models within electronic health records (EHR) may allow for improved cancer prevention. There has been much recent interest in use of machine learning (ML) for cancer prediction, but few studies comparing ML with classical statistical models for NCGC risk prediction.We trained models using logistic regression (LR) and four commonly used ML algorithms to predict NCGC from age-/sex-matched controls in two EHR systems: Stanford University and the University of Washington (UW). The LR model contained well-established NCGC risk factors (intestinal metaplasia histology, prior Helicobacter pylori infection, race, ethnicity, nativity status, smoking history, anemia), whereas ML models agnostically selected variables from the EHR. Models were developed and internally validated in the Stanford data, and externally validated in the UW data. Hyperparameter tuning of models was achieved using cross-validation. Model performance was compared by accuracy, sensitivity, and specificity.In internal validation, LR performed with comparable accuracy (0.732; 95% CI, 0.698 to 0.764), sensitivity (0.697; 95% CI, 0.647 to 0.744), and specificity (0.767; 95% CI, 0.720 to 0.809) to penalized lasso, support vector machine, K-nearest neighbor, and random forest models. In external validation, LR continued to demonstrate high accuracy, sensitivity, and specificity. Although K-nearest neighbor demonstrated higher accuracy and specificity, this was offset by significantly lower sensitivity. No ML model consistently outperformed LR across evaluation criteria.Drawing data from two independent EHRs, we find LR on the basis of established risk factors demonstrated comparable performance to optimized ML algorithms. This study demonstrates that classical models built on robust, hand-chosen predictor variables may not be inferior to data-driven models for NCGC risk prediction.

  View details for DOI 10.1200/CCI.22.00039

  View details for PubMedID 35763703

• Deep Learning Approaches for Predicting Glaucoma Progression Using Electronic Health Records and Natural Language Processing. Ophthalmology science Wang, S. Y., Tseng, B., Hernandez-Boussard, T. 2022; 2 (2): 100127

  Abstract

  Purpose: Advances in artificial intelligence have produced a few predictive models in glaucoma, including a logistic regression model predicting glaucoma progression to surgery. However, uncertainty exists regarding how to integrate the wealth of information in free-text clinical notes. The purpose of this study was to predict glaucoma progression requiring surgery using deep learning (DL) approaches on data from electronic health records (EHRs), including features from structured clinical data and from natural language processing of clinical free-text notes.Design: Development of DL predictive model in an observational cohort.Participants: Adult patients with glaucoma at a single center treated from 2008 through2020.Methods: Ophthalmology clinical notes of patients with glaucoma were identified from EHRs. Available structured data included patient demographic information, diagnosis codes, prior surgeries, and clinical information including intraocular pressure, visual acuity, and central corneal thickness. In addition, words from patients' first 120 days of notes were mapped to ophthalmology domain-specific neural word embeddings trained on PubMed ophthalmology abstracts. Word embeddings and structured clinical data were used as inputs to DL models to predict subsequent glaucoma surgery.Main Outcome Measures: Evaluation metrics included area under the receiver operating characteristic curve (AUC) and F1 score, the harmonic mean of positive predictive value, and sensitivity on a held-out test set.Results: Seven hundred forty-eight of 4512 patients with glaucoma underwent surgery. The model that incorporated both structured clinical features as well as input features from clinical notes achieved an AUC of 73% and F1 of 40%, compared with only structured clinical features, (AUC, 66%; F1, 34%) and only clinical free-text features (AUC, 70%; F1, 42%). All models outperformed predictions from a glaucoma specialist's review of clinical notes (F1, 29.5%).Conclusions: We can successfully predict which patients with glaucoma will need surgery using DL models on EHRs unstructured text. Models incorporating free-text data outperformed those using only structured inputs. Future predictive models using EHRs should make use of information from within clinical free-text notes to improve predictive performance. Additional research is needed to investigate optimal methods of incorporating imaging data into future predictive models as well.

  View details for DOI 10.1016/j.xops.2022.100127

  View details for PubMedID 36249690

• Analyzing real world data of blood transfusion adverse events: Opportunities and challenges. Transfusion Jhaveri, P., Bozkurt, S., Moyal, A., Belov, A., Anderson, S., Shan, H., Whitaker, B., Hernandez-Boussard, T. 2022

  Abstract

  BACKGROUND: Blood transfusions are a vital component of modern healthcare, yet adverse reactions to blood product transfusions can cause morbidity, and rarely result in mortality. Therefore, accurate reporting of transfusion related adverse events (TRAEs) is paramount to improved transfusion practice. This study aims to investigate real-world data (RWD) on TRAEs by evaluating differences between ICD 9/10-based electronic health records (EHR) and blood bank-specific reporting.STUDY DESIGN AND METHODS: TRAE data were retrospectively collected from a blood bank-specific database between Jan 2015 and June 2019 as the reference data source and compared it to ICD 9/10 diagnostic codes corresponding to various TRAEs. Seven reactions that have corresponding ICD 9/10 diagnostic codes were evaluated: Transfusion related circulatory overload (TACO), transfusion related acute lung injury (TRALI), febrile non-hemolytic reaction (FNHTR), transfusion-related anaphylactic reaction (TRA), acute hemolytic transfusion reaction (AHTR), delayed hemolytic transfusion reaction (DHTR), and delayed serologic reaction (DSTR). These accounted for 33% of the TRAEs at an academic institution during the study period.RESULTS: Among 18637 adult blood transfusion recipients, there were 229 unique patients with 263 TRAE related ICD codes in the EHR, while there were 191 unique patients with 287 TRAEs identified in the blood bank database. None of the categories of reaction we investigated had perfect alignment between ICD 9/10 codes and blood bank specific diagnoses.DISCUSSION: Multiple systemic challenges were identified that hinder effective reporting of TRAEs. Identifying factors causing inconsistent reporting between blood banks and EHRs is paramount to developing effective workability between these electronic systems, as well as across clinical and laboratory teams.

  View details for DOI 10.1111/trf.16880

  View details for PubMedID 35437749

• Outcomes of Primary Trabeculectomy versus Combined Phacoemulsification-Trabeculectomy Using Automated Electronic Health Record Data Extraction. Current eye research Davila, J. R., Singh, K., Hernandez-Boussard, T., Wang, S. 2022: 1-7

  Abstract

  PURPOSE: Cataract is a known effect of trabeculectomy (TE), but some surgeons are hesitant to perform combined phacoemulsification-TE (PTE) due to a risk of increased TE failure. Herein, we compare intraocular pressure (IOP) lowering between trabeculectomy (TE) and phacoemulsification-TE (PTE) and investigate factors that impact patient outcomes.METHODS: We performed a retrospective study of adults undergoing primary TE or PTE at our institution from 2010 to 2017. We used Kaplan-Meier survival analysis to investigate time to TE failure, and Cox proportional hazards modeling to investigate predictors of TE failure, defined as undergoing a second glaucoma surgery or using more IOP-lowering medications than pre-operatively.RESULTS: 318 surgeries (218 TE; 100 PTE) from 268 patients were included. Median follow-up time was 753days. Mean baseline IOP was 21.1mmHg. There were no significant differences in IOP between TE and PTE groups beyond postoperative year 1, with 28.9-46.5% of TE and 35.5-44.4% of PTE groups achieving IOP ≤10. Final IOP was similar in both groups (p=0.22): 12.41 (SD 4.18) mmHg in the TE group and 14.05 (SD 5.45) in the PTE group. 84 (26.4%) surgeries met failure criteria. After adjusting for surgery type, sex, age, race, surgeon, and glaucoma diagnosis there were no significant differences in TE failure.CONCLUSION: This study suggests there is no significant difference in the risk of TE failure in patients receiving TE versus those receiving PTE.

  View details for DOI 10.1080/02713683.2022.2045611

  View details for PubMedID 35317681

• Opioid2MME: Standardizing opioid prescriptions to morphine milligram equivalents from electronic health records. International journal of medical informatics Lossio-Ventura, J. A., Song, W., Sainlaire, M., Dykes, P. C., Hernandez-Boussard, T. 2022; 162: 104739

  Abstract

  The national increase in opioid use and misuse has become a public health crisis in the U.S. To tackle this crisis, the systematic evaluation and monitoring of opioid prescribing patterns is necessary. Thus, opioid prescriptions from electronic health records (EHRs) must be standardized to morphine milligram equivalent (MME) to facilitate monitoring and surveillance. While most studies report MMEs to describe opioid prescribing patterns, there is a lack of transparency regarding their data pre-processing and conversion processes for replication or comparison purposes.In this work, we developed Opioid2MME, a SQL-based open-source framework, to convert opioid prescriptions to MMEs using EHR prescription data. The MME conversions were validated internally using F-measures through manual chart review; were compared with two existing tools, as MedEx and MedXN; and the framework was tested in an external academic EHR system.We identified 232,913 prescriptions for 49,060 unique patients in the EHRs, 2008-2019. We manually annotated a sample of prescriptions to assess the performance of the framework. The internal evaluation for medication information extraction achieved F-measures from 0.98 to 1.00 for each piece of the extracted information, outperforming MedEx and MedXN (F-Scores 0.98 and 0.94, respectively). MME values in the internal EHR system obtained a F-measure of 0.97 and identified 3% of the data as outliers and 7% missing values. The MME conversion in the external EHR system obtained 78.3% agreement between the MME values obtained with the development site.The results demonstrated that the framework is replicable and capable of converting opioid prescriptions to MMEs across different medical institutions. In summary, this work sets the groundwork for the systematic evaluation and monitoring of opioid prescribing patterns across healthcare systems.

  View details for DOI 10.1016/j.ijmedinf.2022.104739

  View details for PubMedID 35325663

• Cost-Effectiveness Analysis and Microsimulation of Serial Multiparametric Magnetic Resonance Imaging in Active Surveillance of Localized Prostate Cancer. The Journal of urology Magnani, C. J., Hernandez-Boussard, T., Baker, L. C., Goldhaber-Fiebert, J. D., Brooks, J. D. 2022: 101097JU0000000000002490

  Abstract

  PURPOSE: Many localized prostate cancers will follow an indolent course. Management has shifted towards active surveillance (AS), yet an optimal regimen remains controversial especially regarding expensive multiparametric magnetic resonance imaging (MRI). We aimed to assess cost-effectiveness of MRI in AS protocols.MATERIALS AND METHODS: A probabilistic microsimulation modeled individual patient trajectories for men diagnosed with low-risk cancer. We assessed no surveillance, up-front treatment (surgery or radiation), and scheduled AS protocols incorporating transrectal ultrasound-guided (TRUS) biopsy or MRI-based regimens at serial intervals. Lifetime quality-adjusted life years (QALYs) and costs adjusted to 2020-US$ were used to calculate expected net monetary benefit (NMB) at $50,000/QALY and incremental cost-effectiveness ratios (ICERs). Uncertainty was assessed with probabilistic sensitivity analysis and linear regression metamodeling.RESULTS: Conservative management with AS outperformed up-front definitive treatment in a modeled cohort reflecting characteristics from a multi-institutional trial. Biopsy decision conditional on positive imaging (MRI triage) at 2-year intervals provided the highest expected NMB (ICER $44,576). Biopsy after both positive and negative imaging (MRI pathway) and TRUS-based regimens were not cost-effective. MRI triage resulted in fewer biopsies while reducing metastatic disease or cancer death. Results were sensitive to test performance and cost. MRI triage was the most likely cost-effective strategy on probabilistic sensitivity analysis.CONCLUSIONS: For men with low-risk prostate cancer, our modeling demonstrated that AS with sequential MRI triage is more cost-effective than biopsy regardless of imaging, TRUS biopsy alone, or immediate treatment. AS-guidelines should specify the role of imaging, and prospective studies should be encouraged.

  View details for DOI 10.1097/JU.0000000000002490

  View details for PubMedID 35212570

• Peeking into a black box, the fairness and generalizability of a MIMIC-III benchmarking model SCIENTIFIC DATA Roosli, E., Bozkurt, S., Hernandez-Boussard, T. 2022; 9 (1): 24

  Abstract

  As artificial intelligence (AI) makes continuous progress to improve quality of care for some patients by leveraging ever increasing amounts of digital health data, others are left behind. Empirical evaluation studies are required to keep biased AI models from reinforcing systemic health disparities faced by minority populations through dangerous feedback loops. The aim of this study is to raise broad awareness of the pervasive challenges around bias and fairness in risk prediction models. We performed a case study on a MIMIC-trained benchmarking model using a broadly applicable fairness and generalizability assessment framework. While open-science benchmarks are crucial to overcome many study limitations today, this case study revealed a strong class imbalance problem as well as fairness concerns for Black and publicly insured ICU patients. Therefore, we advocate for the widespread use of comprehensive fairness and performance assessment frameworks to effectively monitor and validate benchmark pipelines built on open data resources.

  View details for DOI 10.1038/s41597-021-01110-7

  View details for Web of Science ID 000746595100001

  View details for PubMedID 35075160

• Prescription quantity and duration predict progression from acute to chronic opioid use in opioid-naive Medicaid patients. PLOS digital health Johnson, D. G., Ho, V. T., Hah, J. M., Humphreys, K., Carroll, I., Curtin, C., Asch, S. M., Hernandez-Boussard, T. 2022; 1 (8)

  Abstract

  Opiates used for acute pain are an established risk factor for chronic opioid use (COU). Patient characteristics contribute to progression from acute opioid use to COU, but most are not clinically modifiable. To develop and validate machine-learning algorithms that use claims data to predict progression from acute to COU in the Medicaid population, Adult opioid naive Medicaid patients from 6 anonymized states who received an opioid prescription between 2015 and 2019 were included. Five machine learning (ML) Models were developed, and model performance assessed by area under the receiver operating characteristic curve (auROC), precision and recall. In the study, 29.9% (53820/180000) of patients transitioned from acute opioid use to COU. Initial opioid prescriptions in COU patients had increased morphine milligram equivalents (MME) (33.2 vs. 23.2), tablets per prescription (45.6 vs. 36.54), longer prescriptions (26.63 vs 24.69 days), and higher proportions of tramadol (16.06% vs. 13.44%) and long acting oxycodone (0.24% vs 0.04%) compared to non- COU patients. The top performing model was XGBoost that achieved average precision of 0.87 and auROC of 0.63 in testing and 0.55 and 0.69 in validation, respectively. Top-ranking prescription-related features in the model included quantity of tablets per prescription, prescription length, and emergency department claims. In this study, the Medicaid population, opioid prescriptions with increased tablet quantity and days supply predict increased risk of progression from acute to COU in opioid-naive patients. Future research should evaluate the effects of modifying these risk factors on COU incidence.

  View details for DOI 10.1371/journal.pdig.0000075

  View details for PubMedID 36203857

• Clinical concept recognition: Evaluation of existing systems on EHRs. Frontiers in artificial intelligence Lossio-Ventura, J. A., Sun, R., Boussard, S., Hernandez-Boussard, T. 2022; 5: 1051724

  Abstract

  Objective: The adoption of electronic health records (EHRs) has produced enormous amounts of data, creating research opportunities in clinical data sciences. Several concept recognition systems have been developed to facilitate clinical information extraction from these data. While studies exist that compare the performance of many concept recognition systems, they are typically developed internally and may be biased due to different internal implementations, parameters used, and limited number of systems included in the evaluations. The goal of this research is to evaluate the performance of existing systems to retrieve relevant clinical concepts from EHRs.Methods: We investigated six concept recognition systems, including CLAMP, cTAKES, MetaMap, NCBO Annotator, QuickUMLS, and ScispaCy. Clinical concepts extracted included procedures, disorders, medications, and anatomical location. The system performance was evaluated on two datasets: the 2010 i2b2 and the MIMIC-III. Additionally, we assessed the performance of these systems in five challenging situations, including negation, severity, abbreviation, ambiguity, and misspelling.Results: For clinical concept extraction, CLAMP achieved the best performance on exact and inexact matching, with an F-score of 0.70 and 0.94, respectively, on i2b2; and 0.39 and 0.50, respectively, on MIMIC-III. Across the five challenging situations, ScispaCy excelled in extracting abbreviation information (F-score: 0.86) followed by NCBO Annotator (F-score: 0.79). CLAMP outperformed in extracting severity terms (F-score 0.73) followed by NCBO Annotator (F-score: 0.68). CLAMP outperformed other systems in extracting negated concepts (F-score 0.63).Conclusions: Several concept recognition systems exist to extract clinical information from unstructured data. This study provides an external evaluation by end-users of six commonly used systems across different extraction tasks. Our findings suggest that CLAMP provides the most comprehensive set of annotations for clinical concept extraction tasks and associated challenges. Comparing standard extraction tasks across systems provides guidance to other clinical researchers when selecting a concept recognition system relevant to their clinical information extraction task.

  View details for DOI 10.3389/frai.2022.1051724

  View details for PubMedID 36714202

• Changes in postoperative opioid prescribing across three diverse healthcare systems, 2010-2020. Frontiers in digital health Coquet, J., Zammit, A., Hajouji, O. E., Humphreys, K., Asch, S. M., Osborne, T. F., Curtin, C. M., Hernandez-Boussard, T. 2022; 4: 995497

  Abstract

  Objective: The opioid crisis brought scrutiny to opioid prescribing. Understanding how opioid prescribing patterns and corresponding patient outcomes changed during the epidemic is essential for future targeted policies. Many studies attempt to model trends in opioid prescriptions therefore understanding the temporal shift in opioid prescribing patterns across populations is necessary. This study characterized postoperative opioid prescribing patterns across different populations, 2010-2020.Data Source: Administrative data from Veteran Health Administration (VHA), six Medicaid state programs and an Academic Medical Center (AMC).Data extraction: Surgeries were identified using the Clinical Classifications Software.Study Design: Trends in average daily discharge Morphine Milligram Equivalent (MME), postoperative pain and subsequent opioid prescription were compared using regression and likelihood ratio test statistics.Principal Findings: The cohorts included 595,106 patients, with populations that varied considerably in demographics. Over the study period, MME decreased significantly at VHA (37.5-30.1; p=0.002) and Medicaid (41.6-31.3; p=0.019), and increased at AMC (36.9-41.7; p<0.001). Persistent opioid users decreased after 2015 in VHA (p<0.001) and Medicaid (p=0.002) and increase at the AMC (p=0.003), although a low rate was maintained. Average postoperative pain scores remained constant over the study period.Conclusions: VHA and Medicaid programs decreased opioid prescribing over the past decade, with differing response times and rates. In 2020, these systems achieved comparable opioid prescribing patterns and outcomes despite having very different populations. Acknowledging and incorporating these temporal distribution shifts into data learning models is essential for robust and generalizable models.

  View details for DOI 10.3389/fdgth.2022.995497

  View details for PubMedID 36561925

• Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation. Frontiers in digital health Stahlberg, E. A., Abdel-Rahman, M., Aguilar, B., Asadpoure, A., Beckman, R. A., Borkon, L. L., Bryan, J. N., Cebulla, C. M., Chang, Y. H., Chatterjee, A., Deng, J., Dolatshahi, S., Gevaert, O., Greenspan, E. J., Hao, W., Hernandez-Boussard, T., Jackson, P. R., Kuijjer, M., Lee, A., Macklin, P., Madhavan, S., McCoy, M. D., Mohammad Mirzaei, N., Razzaghi, T., Rocha, H. L., Shahriyari, L., Shmulevich, I., Stover, D. G., Sun, Y., Syeda-Mahmood, T., Wang, J., Wang, Q., Zervantonakis, I. 2022; 4: 1007784

  Abstract

  We are rapidly approaching a future in which cancer patient digital twins will reach their potential to predict cancer prevention, diagnosis, and treatment in individual patients. This will be realized based on advances in high performance computing, computational modeling, and an expanding repertoire of observational data across multiple scales and modalities. In 2020, the US National Cancer Institute, and the US Department of Energy, through a trans-disciplinary research community at the intersection of advanced computing and cancer research, initiated team science collaborative projects to explore the development and implementation of predictive Cancer Patient Digital Twins. Several diverse pilot projects were launched to provide key insights into important features of this emerging landscape and to determine the requirements for the development and adoption of cancer patient digital twins. Projects included exploring approaches to using a large cohort of digital twins to perform deep phenotyping and plan treatments at the individual level, prototyping self-learning digital twin platforms, using adaptive digital twin approaches to monitor treatment response and resistance, developing methods to integrate and fuse data and observations across multiple scales, and personalizing treatment based on cancer type. Collectively these efforts have yielded increased insights into the opportunities and challenges facing cancer patient digital twin approaches and helped define a path forward. Given the rapidly growing interest in patient digital twins, this manuscript provides a valuable early progress report of several CPDT pilot projects commenced in common, their overall aims, early progress, lessons learned and future directions that will increasingly involve the broader research community.

  View details for DOI 10.3389/fdgth.2022.1007784

  View details for PubMedID 36274654

• Using deep learning-based natural language processing to identify reasons for statin nonuse in patients with atherosclerotic cardiovascular disease. Communications medicine Sarraju, A., Coquet, J., Zammit, A., Chan, A., Ngo, S., Hernandez-Boussard, T., Rodriguez, F. 2022; 2: 88

  Abstract

  Background: Statins conclusively decrease mortality in atherosclerotic cardiovascular disease (ASCVD), the leading cause of death worldwide, and are strongly recommended by guidelines. However, real-world statin utilization and persistence are low, resulting in excess mortality. Identifying reasons for statin nonuse at scale across health systems is crucial to developing targeted interventions to improve statin use.Methods: We developed and validated deep learning-based natural language processing (NLP) approaches (Clinical Bidirectional Encoder Representations from Transformers [BERT]) to classify statin nonuse and reasons for statin nonuse using unstructured electronic health records (EHRs) from a diverse healthcare system.Results: We present data from a cohort of 56,530 ASCVD patients, among whom 21,508 (38%) lack guideline-directed statin prescriptions and statins listed as allergies in structured EHR portions. Of these 21,508 patients without prescriptions, only 3,929 (18%) have any discussion of statin use or nonuse in EHR documentation. The NLP classifiers identify statin nonuse with an area under the curve (AUC) of 0.94 (95% CI 0.93-0.96) and reasons for nonuse with a weighted-average AUC of 0.88 (95% CI 0.86-0.91) when evaluated against manual expert chart review in a held-out test set. Clinical BERT identifies key patient-level reasons (side-effects, patient preference) and clinician-level reasons (guideline-discordant practices) for statin nonuse, including differences by type of ASCVD and patient race/ethnicity.Conclusions: Our deep learning NLP classifiers can identify crucial gaps in statin nonuse and reasons for nonuse in high-risk populations to support education, clinical decision support, and potential pathways for health systems to address ASCVD treatment gaps.

  View details for DOI 10.1038/s43856-022-00157-w

  View details for PubMedID 35856080

• Expanding the Secondary Use of Prostate Cancer Real World Data: Automated Classifiers for Clinical and Pathological Stage. Frontiers in digital health Bozkurt, S., Magnani, C. J., Seneviratne, M. G., Brooks, J. D., Hernandez-Boussard, T. 2022; 4: 793316

  Abstract

  Background: Explicit documentation of stage is an endorsed quality metric by the National Quality Forum. Clinical and pathological cancer staging is inconsistently recorded within clinical narratives but can be derived from text in the Electronic Health Record (EHR). To address this need, we developed a Natural Language Processing (NLP) solution for extraction of clinical and pathological TNM stages from the clinical notes in prostate cancer patients.Methods: Data for patients diagnosed with prostate cancer between 2010 and 2018 were collected from a tertiary care academic healthcare system's EHR records in the United States. This system is linked to the California Cancer Registry, and contains data on diagnosis, histology, cancer stage, treatment and outcomes. A randomly selected sample of patients were manually annotated for stage to establish the ground truth for training and validating the NLP methods. For each patient, a vector representation of clinical text (written in English) was used to train a machine learning model alongside a rule-based model and compared with the ground truth.Results: A total of 5,461 prostate cancer patients were identified in the clinical data warehouse and over 30% were missing stage information. Thirty-three to thirty-six percent of patients were missing a clinical stage and the models accurately imputed the stage in 21-32% of cases. Twenty-one percent had a missing pathological stage and using NLP 71% of missing T stages and 56% of missing N stages were imputed. For both clinical and pathological T and N stages, the rule-based NLP approach out-performed the ML approach with a minimum F1 score of 0.71 and 0.40, respectively. For clinical M stage the ML approach out-performed the rule-based model with a minimum F1 score of 0.79 and 0.88, respectively.Conclusions: We developed an NLP pipeline to successfully extract clinical and pathological staging information from clinical narratives. Our results can serve as a proof of concept for using NLP to augment clinical and pathological stage reporting in cancer registries and EHRs to enhance the secondary use of these data.

  View details for DOI 10.3389/fdgth.2022.793316

  View details for PubMedID 35721793

• Digital twins for predictive oncology will be a paradigm shift for precision cancer care. Nature medicine Hernandez-Boussard, T., Macklin, P., Greenspan, E. J., Gryshuk, A. L., Stahlberg, E., Syeda-Mahmood, T., Shmulevich, I. 2021

  View details for DOI 10.1038/s41591-021-01558-5

  View details for PubMedID 34824458

• Major disparities in COVID-19 test positivity for patients with non-English preferred language even after accounting for race and social factors in the United States in 2020. BMC public health Cohen-Cline, H., Li, H., Gill, M., Rodriguez, F., Hernandez-Boussard, T., Wolberg, H., Lippa, J., Vartanian, K. 2021; 21 (1): 2121

  Abstract

  BACKGROUND: The COVID-19 pandemic has further exposed inequities in our society, demonstrated by disproportionate COVID-19 infection rate and mortality in communities of color and low-income communities. One key area of inequity that has yet to be explored is disparities based on preferred language.METHODS: We conducted a retrospective cohort study of 164,368 adults tested for COVID-19 in a large healthcare system across Washington, Oregon, and California from March - July 2020. Using electronic health records, we constructed multi-level models that estimated the odds of testing positive for COVID-19 by preferred language, adjusting for age, race/ethnicity, and social factors. We further investigated interaction between preferred language and both race/ethnicity and state. Analysis was performed from October-December 2020.RESULTS: Those whose preferred language was not English had higher odds of having a COVID-19 positive test (OR 3.07, p<0.001); this association remained significant after adjusting for age, race/ethnicity, and social factors. We found significant interaction between language and race/ethnicity and language and state, but the odds of COVID-19 test positivity remained greater for those whose preferred language was not English compared to those whose preferred language was English within each race/ethnicity and state.CONCLUSIONS: People whose preferred language is not English are at greater risk of testing positive for COVID-19 regardless of age, race/ethnicity, geography, or social factors - demonstrating a significant inequity. Research demonstrates that our public health and healthcare systems are centered on English speakers, creating structural and systemic barriers to health. Addressing these barriers are long overdue and urgent for COVID-19 prevention.

  View details for DOI 10.1186/s12889-021-12171-z

  View details for PubMedID 34794421

• Characterizing patient flow after an academic hospital merger and acquisition. The American journal of managed care Sun, R., Bozkurt, S., Winget, M., Cullen, M. R., Seto, T., Hernandez-Boussard, T. 2021; 27 (10): e343-e348

  Abstract

  OBJECTIVES: Hospital mergers and acquisitions are increasingly used as a strategy to facilitate value-based care. However, no studies have assessed health care utilization (HCU) and patient flow across merged institutions. We aim to evaluate patient population distribution, HCU, and patient flow across a recent hospital merger of an academic medical center (AMC), a primary and specialty care alliance (PSC), and a community-based medical center (CMC).STUDY DESIGN: This was a retrospective observational study.METHODS: The study used 2018 adult demographic and encounter data from electronic health records. Patients' parent health care institution was determined by the most frequently visited site of face-to-face visits. Differences in patient demographics and HCU (ie, emergency department [ED] visits, hospitalizations, primary care visits) were compared. Independent factors associated with utilization were identified using adjusted logistic regression models.RESULTS: A total of 406,303 adult patients were identified in the cohort. The PSC setting, compared with the AMC and the CMC, had significantly more female (62.7% vs 54.4% and 58.5%, respectively), older (mean [SD] age, 52.0 [18.1] vs 51.1 [17.8] and 49.2 [17.8] years), and privately insured (63.6% vs 51.3% and 56.0%) patients. A higher proportion of patients at the CMC (27.5%) visited the ED compared with patients at the AMC (10.8%). Approximately 1645 primary care patients (7%) at the CMC setting went to the AMC for specialized care such as oncology, surgery, and neurology.CONCLUSIONS: Hospital mergers are increasing across the United States, allowing AMCs to expand their reach. These findings suggest that patients mainly sought care at their parent health care institution, yet appropriately received specialized care at the AMC. These results provide insights for future mergers and guide resource allocation and opportunities for improving care delivery.

  View details for DOI 10.37765/ajmc.2021.88764

  View details for PubMedID 34668676

• Patients' perception of meaning of life and needed support before and after cancer treatment initiation Roy, M., Rosenthal, S., Shah, M., Khaki, A., Hernandez-Boussard, T., Ramchandran, K. SPRINGER. 2021: S156-S157

  View details for Web of Science ID 000712224700339

• Association of treatment type with patient-reported quality of life in cancer distress screening Roy, M., Rosenthal, S., Shah, M. P., Khaki, A., Bozkurt, S., Seto, T., Blayney, D. W., Hernandez-Boussard, T., Ramchandran, K. LIPPINCOTT WILLIAMS & WILKINS. 2021

  View details for DOI 10.1200/JCO.2020.39.28_suppl.178

  View details for Web of Science ID 000707130200177

• Gaps in standardized postoperative pain management quality measures: A systematic review. Surgery Joseph, J. M., Gori, D., Curtin, C., Hah, J., Ho, V. T., Asch, S. M., Hernandez-Boussard, T. 2021

  Abstract

  BACKGROUND: The goal of this study was an assessment of availability postoperative pain management quality measures and National Quality Forum-endorsed measures. Postoperative pain is an important clinical timepoint because poor pain control can lead to patient suffering, chronic opiate use, and/or chronic pain. Quality measures can guide best practices, but it is unclear whether there are measures for managing pain after surgery.METHODS: The National Quality Forum Quality Positioning System, Agency for Healthcare Research and Quality Indicators, and Centers for Medicare and Medicaid Services Measures Inventory Tool databases were searched in November 2019. We conducted a systematic literature review to further identify quality measures in research publications, clinical practice guidelines, and gray literature for the period between March 11, 2015 and March 11,2020.RESULTS: Our systematic review yielded 1,328 publications, of which 206 were pertinent. Nineteen pain management quality measures were identified from the quality measure databases, and 5 were endorsed by National Quality Forum. The National Quality Forum measures were not specific to postoperative pain management. Three of the non-endorsed measures were specific to postoperative pain.CONCLUSION: The dearth of published postoperative pain management quality measures, especially National Quality Forum-endorsed measures, highlights the need for more rigorous evidence and widely endorsed postoperative pain quality measures to guide best practices.

  View details for DOI 10.1016/j.surg.2021.08.004

  View details for PubMedID 34538340

• REAL-WORLD VALIDATION AND GENERALIZABILITY OF A PSAK PREDICTION TOOL FOR ACTIVE SURVEILLANCE RECLASSIFICATION Magnani, C. J., Moyal, A., Erdogdu, B., Peterson, D. J., Bozkurt, S., Hernandez-Boussard, T., Brooks, J. D. LIPPINCOTT WILLIAMS & WILKINS. 2021: E1094-E1095

  View details for Web of Science ID 000693689000678

• Health management via telemedicine: Learning from the COVID-19 experience. Journal of the American Medical Informatics Association : JAMIA Sun, R., Blayney, D. W., Hernandez-Boussard, T. 2021

  Abstract

  At the onset of the COVID-19 (coronavirus disease 2019) pandemic, telemedicine was rapidly implemented to protect patients and healthcare providers from infection. It is unlikely that care delivery will fully return to the pre-COVID form. Telemedicine offers many opportunities to improve care efficiency, accessibility, and patient outcomes, but many challenges exist related to technology interoperability, the digital divide, and usability. We propose that telemedicine evolve to support continuity of care throughout the patient journey, including multidisciplinary care teams and the seamless integration of data into the clinical workflow to support a learning healthcare system. Importantly, evidence is needed to support this paradigm shift in care delivery to ensure the quality and efficacy of care delivered via telemedicine. Here, we highlight gaps and opportunities that need to be addressed by the biomedical informatics community to move forward with safe and effective healthcare delivery via telemedicine.

  View details for DOI 10.1093/jamia/ocab145

  View details for PubMedID 34459475

• Disparity in the Setting of Incident Heart Failure Diagnosis. Circulation. Heart failure Sandhu, A. T., Tisdale, R. L., Rodriguez, F., Stafford, R. S., Maron, D. J., Hernandez-Boussard, T., Lewis, E., Heidenreich, P. A. 2021: CIRCHEARTFAILURE121008538

  Abstract

  BACKGROUND: Early heart failure (HF) recognition can reduce morbidity, yet HF is often initially diagnosed only after a patient clinically worsens. We sought to identify characteristics that predict diagnosis in the acute care setting versus the outpatient setting.METHODS: We estimated the proportion of incident HF diagnosed in the acute care setting (inpatient hospital or emergency department) versus outpatient setting based on diagnostic codes from a claims database covering commercial insurance and Medicare Advantage between 2003 and 2019. After excluding new-onset HF potentially caused by a concurrent acute cause (eg, acute myocardial infarction), we identified demographic, clinical, and socioeconomic predictors of diagnosis setting. Patients were linked to their primary care clinicians to evaluate diagnosis setting variation across clinicians.RESULTS: Of 959 438 patients with new HF, 38% were diagnosed in acute care. Of these, 46% had potential HF symptoms in the prior 6 months. Over time, the relative odds of acute care diagnosis increased by 3.2% annually after adjustment for patient characteristics (95% CI, 3.1%-3.3%). Acute care diagnosis setting was more likely for women compared with men (adjusted odds ratio, 1.11 [95% CI, 1.10-1.12]) and for Black patients compared with White patients (adjusted odds ratio, 1.18 [95% CI, 1.16-1.19]). The proportion of acute care diagnosis varied substantially (interquartile range: 24%-39%) among clinicians after adjusting for patient-level risk factors.CONCLUSIONS: A large proportion of first HF diagnoses occur in the acute care setting, particularly among women and Black patients, yet many had potential HF symptoms in the months before acute care visits. These results raise concerns that many HF diagnoses are missed in the outpatient setting. Earlier diagnosis could allow for timelier high-value interventions, addressing disparities and reducing the progression of HF.

  View details for DOI 10.1161/CIRCHEARTFAILURE.121.008538

  View details for PubMedID 34311559

• Diverse patient trajectories during cytotoxic chemotherapy: Capturing longitudinal patient-reported outcomes. Cancer medicine Azad, A. D., Yilmaz, M., Bozkurt, S., Brooks, J. D., Blayney, D. W., Hernandez-Boussard, T. 2021

  Abstract

  BACKGROUND: High-value cancer care balances effective treatment with preservation of quality of life. Chemotherapy is known to affect patients' physical and psychological well-being negatively. Patient-reported outcomes (PROs) provide a means to monitor declines in a patients' well-being during treatment.METHODS: We identified 741 oncology patients undergoing chemotherapy in our electronic health record (EHR) system who completed Patient-Reported Outcomes Measurement Information System (PROMIS) surveys during treatment at a comprehensive cancer center, 2013-2018. PROMIS surveys were collected before, during, and after chemotherapy treatment. Linear mixed-effects models were performed to identify predictors of physical and mental health scores over time. A k-mean cluster analysis was used to group patient PROMIS score trajectories.RESULTS: Mean global physical health (GPH) scores were 48.7 (SD 9.3), 47.7 (8.8), and 48.6 (8.9) and global mental health (GMH) scores were 50.4 (8.6), 49.5 (8.8), and 50.6 (9.1) before, during, and after chemotherapy, respectively. Asian race, Hispanic ethnicity, public insurance, anxiety/depression, stage III cancer, and palliative care were predictors of GPH and GMH decline. The treatment time period was also a predictor of both GPH and GMH decline relative to pre-treatment. Trajectory clustering identified four distinct PRO clusters associated with chemotherapy treatment.CONCLUSIONS: Patient-reported outcomes are increasingly used to help monitor cancer treatment and are now a part of care reimbursement. This study leveraged routinely collected PROMIS surveys linked to EHRs to identify novel patient trajectories of physical and mental well-being in oncology patients undergoing chemotherapy and potential predictors. Supportive care interventions in high-risk populations identified by our study may optimize resource deployment.NOVELTY AND IMPACT: This study leveraged routinely collected patient-reported outcome (PROMIS) surveys linked to electronic health records to characterize oncology patients' quality of life during chemotherapy. Important clinical and demographic predictors of declines in quality of life were identified and four novel trajectories to guide personalized interventions and support. This work highlights the utility of monitoring patient-reported outcomes not only before and after, but during chemotherapy to help advert adverse patient outcomes and improve treatment adherence.

  View details for DOI 10.1002/cam4.4124

  View details for PubMedID 34254459

• Evaluation of clustering and topic modeling methods over health-related tweets and emails. Artificial intelligence in medicine Lossio-Ventura, J. A., Gonzales, S., Morzan, J., Alatrista-Salas, H., Hernandez-Boussard, T., Bian, J. 2021; 117: 102096

  Abstract

  BACKGROUND: Internet provides different tools for communicating with patients, such as social media (e.g., Twitter) and email platforms. These platforms provided new data sources to shed lights on patient experiences with health care and improve our understanding of patient-provider communication. Several existing topic modeling and document clustering methods have been adapted to analyze these new free-text data automatically. However, both tweets and emails are often composed of short texts; and existing topic modeling and clustering approaches have suboptimal performance on these short texts. Moreover, research over health-related short texts using these methods has become difficult to reproduce and benchmark, partially due to the absence of a detailed comparison of state-of-the-art topic modeling and clustering methods on these short texts.METHODS: We trained eight state-of- the-art topic modeling and clustering algorithms on short texts from two health-related datasets (tweets and emails): Latent Semantic Indexing (LSI), Latent Dirichlet Allocation (LDA), LDA with Gibbs Sampling (GibbsLDA), Online LDA, Biterm Model (BTM), Online Twitter LDA, and Gibbs Sampling for Dirichlet Multinomial Mixture (GSDMM), as well as the k-means clustering algorithm with two different feature representations: TF-IDF and Doc2Vec. We used cluster validity indices to evaluate the performance of topic modeling and clustering: two internal indices (i.e. assessing the goodness of a clustering structure without external information) and five external indices (i.e. comparing the results of a cluster analysis to an externally known provided class labels).RESULTS: In overall, for number of clusters (k) from 2 to 50, Online Twitter LDA and GSDMM achieved the best performance in terms of internal indices, while LSI and k-means with TF-IDF had the highest external indices. Also, of all tweets (N = 286, 971; HPV represents 94.6% of tweets and lynch syndrome represents 5.4%), for k = 2, most of the methods could respect this initial clustering distribution. However, we found model performance varies with the source of data and hyper-parameters such as the number of topics and the number of iterations used to train the models. We also conducted an error analysis using the Hamming loss metric, for which the poorest value was obtained by GSDMM on both datasets.CONCLUSIONS: Researchers hoping to group or classify health related short-text data can expect to select the most suitable topic modeling and clustering methods for their specific research questions. Therefore, we presented a comparison of the most common used topic modeling and clustering algorithms over two health-related, short-text datasets using both internal and external clustering validation indices. Internal indices suggested Online Twitter LDA and GSDMM as the best, while external indices suggested LSI and k-means with TF-IDF as the best. In summary, our work suggested researchers can improve their analysis of model performance by using a variety of metrics, since there is not a single best metric.

  View details for DOI 10.1016/j.artmed.2021.102096

  View details for PubMedID 34127235

• Type 1 Diabetes Management With Technology: Patterns of Utilization and Effects on Glucose Control Using Real-World Evidence. Clinical diabetes : a publication of the American Diabetes Association Sun, R., Banerjee, I., Sang, S., Joseph, J., Schneider, J., Hernandez-Boussard, T. 2021; 39 (3): 284-292

  Abstract

  This retrospective cohort study evaluated diabetes device utilization and the effectiveness of these devices for newly diagnosed type 1 diabetes. Investigators examined the use of continuous glucose monitoring (CGM) systems, self-monitoring of blood glucose (SMBG), continuous subcutaneous insulin infusion (CSII), and multiple daily injection (MDI) insulin regimens and their effects on A1C. The researchers identified 6,250 patients with type 1 diabetes, of whom 32% used CGM and 37.1% used CSII. A higher adoption rate of either CGM or CSII in newly diagnosed type 1 diabetes was noted among White patients and those with private health insurance. CGM users had lower A1C levels than nonusers (P = 0.039), whereas no difference was noted between CSII users and nonusers (P = 0.057). Furthermore, CGM use combined with CSII yielded lower A1C than MDI regimens plus SMBG (P <0.001).

  View details for DOI 10.2337/cd20-0098

  View details for PubMedID 34421204

• Increases in SARS-CoV-2 Test Positivity Rates Among Hispanic People in a Northern California Health System. Public health reports (Washington, D.C. : 1974) Rodriguez, F., Coquet, J., Harrington, R., Hernandez-Boussard, T. 2021: 333549211026778

  Abstract

  Racial/ethnic minority groups are disproportionately affected by the COVID-19 pandemic. We examined ethnic differences in SARS-CoV-2 testing patterns and positivity rates in a large health care system in Northern California. The study population included patients tested for SARS-CoV-2 from March 4, 2020, through January 12, 2021, at Stanford Health Care. We used adjusted hierarchical logistic regression models to identify factors associated with receiving a positive test result. During the study period, 282 916 SARS-CoV-2 tests were administered to 179 032 unique patients, 32 766 (18.3%) of whom were Hispanic. Hispanic patients were 3 times more likely to receive a positive test result than patients in other racial/ethnic groups (odds ratio = 3.16; 95% CI, 3.00-3.32). The rate of receiving a positive test result for SARS-CoV-2 among Hispanic patients increased from 5.4% in mid-March to 15.7% in mid-July, decreased to 3.9% in mid-October, and increased to 21.2% toward the end of December. Hispanic patients were more likely than non-Hispanic patients to receive a positive test result for SARS-CoV-2, with increasing trends during regional surges. The disproportionate and growing overrepresentation of Hispanic people receiving a positive test result for SARS-CoV-2 demonstrates the need to focus public health prevention efforts on these communities.

  View details for DOI 10.1177/00333549211026778

  View details for PubMedID 34161176

• Identification of patients at high risk for preventable emergency department visits and inpatient admissions after starting chemotherapy: Machine learning applied to comprehensive electronic health record data. Peterson, D. J., Ostberg, N. P., Blayney, D. W., Brooks, J. D., Hernandez-Boussard, T. LIPPINCOTT WILLIAMS & WILKINS. 2021

  View details for DOI 10.1200/JCO.2021.39.15_suppl.1511

  View details for Web of Science ID 000708120600211

• PREDICTORS OF SETTING OF HEART FAILURE DIAGNOSIS Tisdale, R., Stafford, R., Maron, D., Hernandez-Boussard, T., Rodriguez, F., Heidenreich, P., Sandhu, A. ELSEVIER SCIENCE INC. 2021: 676

  View details for Web of Science ID 000647487500675

• IDENTIFYING REASONS FOR STATIN NONADHERENCE IN A DIVERSE, REAL-WORLD POPULATION USING ELECTRONIC HEALTH RECORDS AND NATURAL LANGUAGE PROCESSING Sarraju, A., Coquet, J., Chan, A., Ngo, S., Lossio-Ventura, J., Hernandez-Boussard, T., Rodriguez, F. ELSEVIER SCIENCE INC. 2021: 1665

  View details for Web of Science ID 000647487501671

• Learning from Past Respiratory Failure Patients to Triage COVID-19 Patient Ventilator Needs: A Multi-Institutional Study. Journal of biomedical informatics Carmichael, H., Coquet, J., Sun, R., Sang, S., Groat, D., Asch, S. M., Bledsoe, J., Peltan, I. D., Jacobs, J. R., Hernandez-Boussard, T. 2021: 103802

  Abstract

  BACKGROUND: Unlike well-established diseases that base clinical care on randomized trials, past experiences, and training, prognosis in COVID19 relies on a weaker foundation. Knowledge from other respiratory failure diseases may inform clinical decisions in this novel disease. The objective was to predict 48-hour invasive mechanical ventilation (IMV) within 48 hours in patients hospitalized with COVID-19 using COVID-like diseases (CLD).METHODS: This retrospective multicenter study trained machine learning (ML) models on patients hospitalized with CLD to predict IMV within 48 hours in COVID-19 patients. CLD patients were identified using diagnosis codes for bacterial pneumonia, viral pneumonia, influenza, unspecified pneumonia and acute respiratory distress syndrome (ARDS), 2008-2019. A total of 16 cohorts were constructed, including any combinations of the four diseases plus an exploratory ARDS cohort, to determine the most appropriate cohort to use. Candidate predictors included demographic and clinical parameters that were previously associated with poor COVID-19 outcomes. Model development included the implementation of logistic regression and three ensemble tree-based algorithms: decision tree, AdaBoost, and XGBoost. Models were validated in hospitalized COVID-19 patients at two healthcare systems, March 2020-July 2020. ML models were trained on CLD patients at Stanford Hospital Alliance (SHA). Models were validated on hospitalized COVID-19 patients at both SHA and Intermountain Healthcare.RESULTS: CLD training data were obtained from SHA (n=14,030), and validation data included 444 adult COVID-19 hospitalized patients from SHA (n=185) and Intermountain (n=259). XGBoost was the top-performing ML model, and among the 16 CLD training cohorts, the best model achieved an area under curve (AUC) of 0.883 in the validation set. In COVID-19 patients, the prediction models exhibited moderate discrimination performance, with the best models achieving an AUC of 0.77 at SHA and 0.65 at Intermountain. The model trained on all pneumonia and influenza cohorts had the best overall performance (SHA: positive predictive value (PPV) 0.29, negative predictive value (NPV) 0.97, positive likelihood ratio (PLR) 10.7; Intermountain: PPV, 0.23, NPV 0.97, PLR 10.3). We identified important factors associated with IMV that are not traditionally considered for respiratory diseases.CONCLUSIONS: The performance of prediction models derived from CLD for 48-hour IMV in patients hospitalized with COVID-19 demonstrate high specificity and can be used as a triage tool at point of care. Novel predictors of IMV identified in COVID-19 are often overlooked in clinical practice. Lessons learned from our approach may assist other research institutes seeking to build artificial intelligence technologies for novel or rare diseases with limited data for training and validation.

  View details for DOI 10.1016/j.jbi.2021.103802

  View details for PubMedID 33965640

• Development and evaluation of novel ophthalmology domain-specific neural word embeddings to predict visual prognosis. International journal of medical informatics Wang, S., Tseng, B., Hernandez-Boussard, T. 2021; 150: 104464

  Abstract

  OBJECTIVE: To develop and evaluate novel word embeddings (WEs) specific to ophthalmology, using text corpora from published literature and electronic health records (EHR).MATERIALS AND METHODS: We trained ophthalmology-specific WEs using 121,740 PubMed abstracts and 89,282 EHR notes using word2vec continuous bag-of-words architecture. PubMed and EHR WEs were compared to general domain GloVe WEs and general biomedical domain BioWordVec embeddings using a novel ophthalmology-domain-specific 200-question analogy test and prediction of prognosis in 5547 low vision patients using EHR notes as inputs to a deep learning model.RESULTS: We found that many words representing important ophthalmic concepts in the EHR were missing from the general domain GloVe vocabulary, but covered in the ophthalmology abstract corpus. On ophthalmology analogy testing, PubMed WEs scored 95.0 %, outperforming EHR (86.0 %) and GloVe (91.0 %) but less than BioWordVec (99.5 %). On predicting low vision prognosis, PubMed and EHR WEs resulted in similar AUROC (0.830; 0.826), outperforming GloVe (0.778) and BioWordVec (0.784).CONCLUSION: We found that using ophthalmology domain-specific WEs improved performance in ophthalmology-related clinical prediction compared to general WEs. Deep learning models using clinical notes as inputs can predict the prognosis of visually impaired patients. This work provides a framework to improve predictive models using domain-specific WEs.

  View details for DOI 10.1016/j.ijmedinf.2021.104464

  View details for PubMedID 33892445

• Prevalence of Postprostatectomy Incontinence Requiring Anti-incontinence Surgery After Radical Prostatectomy for Prostate Cancer: A Retrospective Population-Based Analysis. International neurourology journal Kim, J. H., Jeong, I. G., Khandwala, Y. S., Hernandez-Boussard, T., Brooks, J. D., Chung, B. I. 2021

  Abstract

  Purpose: The aim of this study was to examine the prevalence of surgery for post-prostatectomy incontinence (PI) following minimally invasive surgery compared to conventional open surgery for prostate cancer.Methods: This retrospective cohort study used the Florida State Ambulatory Surgery and State Inpatient Databases, 2008 to 2010, RP patients were identified using ICD-9/10 procedure codes and among this cohort PI was identified also using ICD-9/10 codes. Surgical approaches included Minimally invasive (robotic or laparoscopic) vs. open (retropubic or perineal) RP. The primary outcome was the overall prevalence of surgery for PI. The secondary outcome was the association of PI requiring anti-incontinence surgery with the surgical approach for RP.Results: Among the 13535 patients initially included in the study (mean age, 63.3 years), 6932 (51.2%) underwent open RP and 6603 (49.8%) underwent minimally invasive RP. The overall prevalence of surgical procedures for PI during the observation period among the all patients who had received RP was 3.3%. The rate of PI surgery for patients receiving minimally invasive surgery was higher than that for patients receiving open surgery (4.8% vs. 3.0%; risk difference, 1.8%; 95% CI, 0.3% to 3.4%). The adjusted prevalence of PI surgery for patients who had undergone laparoscopic RP was higher than that for those with retropubic RP (8.6% vs. 3.7%).Conclusions: Among patients undergoing RP for prostate cancer, the prevalence of PI surgery is not negligible. Patients undergoing minimally invasive RP had higher adjusted rates for PI surgery compared to open approaches, which was attributed to high rate of PI surgery following laparoscopic approach and low rate of PI surgery following perineal approach. More studies are needed to establish strategies to reduce the rate of PI surgery after RP.

  View details for DOI 10.5213/inj.2040296.148

  View details for PubMedID 33705635

• Conflicting information from the Food and Drug Administration: Missed opportunity to lead standards for safe and effective medical artificial intelligence solutions. Journal of the American Medical Informatics Association : JAMIA Hernandez-Boussard, T., Lundgren, M. P., Shah, N. 2021

  Abstract

  The Food & Drug Administration (FDA) is considering the permanent exemption of premarket notification requirements for several Class I and II medical device products, including several artificial Intelligence (AI)-driven devices. The exemption is based on the need to rapidly more quickly disseminate devices to the public, estimated cost-savings, a lack of documented adverse events reported to the FDA's database. However, this ignores emerging issues related to AI-based devices, including utility, reproducibility and bias that may not only affect an individual but entire populations. We urge the FDA to reinforce the messaging on safety and effectiveness regulations of AI-based Software as a Medical Device products to better promote fair AI-driven clinical decision tools and for preventing harm to the patients we serve.

  View details for DOI 10.1093/jamia/ocab035

  View details for PubMedID 33674865

• Understanding the impact of the COVID-19 pandemic on physical and mental health Cao, S., Din, H., Warren, C., Fitzpatrick, J., Hernandez-Boussard, T., Desai, M., Chinthrajah, S., Nadeau, K. MOSBY-ELSEVIER. 2021: AB115

  View details for Web of Science ID 000629158000365

• Real-world Evidence to Estimate Prostate Cancer Costs for First-line Treatment or Active Surveillance. European urology open science Magnani, C. J., Bievre, N., Baker, L. C., Brooks, J. D., Blayney, D. W., Hernandez-Boussard, T. 2021; 23: 20–29

  Abstract

  Background: Prostate cancer is the most common cancer in men and second leading cause of cancer-related deaths. Changes in screening guidelines, adoption of active surveillance (AS), and implementation of high-cost technologies have changed treatment costs. Traditional cost-effectiveness studies rely on clinical trial protocols unlikely to capture actual practice behavior, and existing studies use data predating new technologies. Real-world evidence reflecting these changes is lacking.Objective: To assess real-world costs of first-line prostate cancer management.Design setting and participants: We used clinical electronic health records for 2008-2018 linked with the California Cancer Registry and the Medicare Fee Schedule to assess costs over 24 or 60 mo following diagnosis. We identified surgery or radiation treatments with structured methods, while we used both structured data and natural language processing to identify AS.Outcome measurements and statistical analysis: Our results are risk-stratified calculated cost per day (CCPD) for first-line management, which are independent of treatment duration. We used the Kruskal-Wallis test to compare unadjusted CCPD while analysis of covariance log-linear models adjusted estimates for age and Charlson comorbidity.Results and limitations: In 3433 patients, surgery (54.6%) was more common than radiation (22.3%) or AS (23.0%). Two years following diagnosis, AS ($2.97/d) was cheaper than surgery ($5.67/d) or radiation ($9.34/d) in favorable disease, while surgery ($7.17/d) was cheaper than radiation ($16.34/d) for unfavorable disease. At 5 yr, AS ($2.71/d) remained slightly cheaper than surgery ($2.87/d) and radiation ($4.36/d) in favorable disease, while for unfavorable disease surgery ($4.15/d) remained cheaper than radiation ($10.32/d). Study limitations include information derived from a single healthcare system and costs based on benchmark Medicare estimates rather than actual payment exchanges.Patient summary: Active surveillance was cheaper than surgery (-47.6%) and radiation (-68.2%) at 2 yr for favorable-risk disease, which decreased by 5 yr (-5.6% and -37.8%, respectively). Surgery was less costly than radiation for unfavorable risk for both intervals (-56.1% and -59.8%, respectively).

  View details for DOI 10.1016/j.euros.2020.11.004

  View details for PubMedID 33367287

• Machine Learning Applied to Electronic Health Records: Identification of Chemotherapy Patients at High Risk for Preventable Emergency Department Visits and Hospital Admissions. JCO clinical cancer informatics Peterson, D. J., Ostberg, N. P., Blayney, D. W., Brooks, J. D., Hernandez-Boussard, T. 2021; 5: 1106-1126

  Abstract

  Acute care use (ACU) is a major driver of oncologic costs and is penalized by a Centers for Medicare & Medicaid Services quality measure, OP-35. Targeted interventions reduce preventable ACU; however, identifying which patients might benefit remains challenging. Prior predictive models have made use of a limited subset of the data in the electronic health record (EHR). We aimed to predict risk of preventable ACU after starting chemotherapy using machine learning (ML) algorithms trained on comprehensive EHR data.Chemotherapy patients treated at an academic institution and affiliated community care sites between January 2013 and July 2019 who met inclusion criteria for OP-35 were identified. Preventable ACU was defined using OP-35 criteria. Structured EHR data generated before chemotherapy treatment were obtained. ML models were trained to predict risk for ACU after starting chemotherapy using 80% of the cohort. The remaining 20% were used to test model performance by the area under the receiver operator curve.Eight thousand four hundred thirty-nine patients were included, of whom 35% had preventable ACU within 180 days of starting chemotherapy. Our primary model classified patients at risk for preventable ACU with an area under the receiver operator curve of 0.783 (95% CI, 0.761 to 0.806). Performance was better for identifying admissions than emergency department visits. Key variables included prior hospitalizations, cancer stage, race, laboratory values, and a diagnosis of depression. Analyses showed limited benefit from including patient-reported outcome data and indicated inequities in outcomes and risk modeling for Black and Medicaid patients.Dense EHR data can identify patients at risk for ACU using ML with promising accuracy. These models have potential to improve cancer care outcomes, patient experience, and costs by allowing for targeted, preventative interventions.

  View details for DOI 10.1200/CCI.21.00116

  View details for PubMedID 34752139

• Learning from past respiratory infections to predict COVID-19 Outcomes: A retrospective study. Journal of medical Internet research Sang, S. n., Sun, R. n., Coquet, J. n., Carmichael, H. n., Seto, T. n., Hernandez-Boussard, T. n. 2021

  Abstract

  In the clinical care of well-established diseases, randomized trials, literature and research are supplemented by clinical judgment to understand disease prognosis and inform treatment choices. In the void created by a lack of clinical experience with COVID-19, Artificial Intelligence (AI) may be an important tool to bolster clinical judgment and decision making. However, lack of clinical data restricts the design and development of such AI tools, particularly in preparation of an impending crisis or pandemic.This study aimed to develop and test the feasibility of a 'patients-like-me' framework to predict COVID-19 patient deterioration using a retrospective cohort of similar respiratory diseases.Our framework used COVID-like cohorts to design and train AI models that were then validated on the COVID-19 population. The COVID-like cohorts included patients diagnosed with bacterial pneumonia, viral pneumonia, unspecified pneumonia, influenza, and acute respiratory distress syndrome (ARDS) from an academic medical center, 2008-2019. Fifteen training cohorts were created using different combinations of the COVID-like cohorts with the ARDS cohort for exploratory purpose. Two machine learning (ML) models were developed, one to predict invasive mechanical ventilation (IMV) within 48 hours for each hospitalized day, and one to predict all-cause mortality at the time of admission. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We established model interpretability by calculating SHapley Additive exPlanations (SHAP) scores to identify important features.Compared to the COVID-like cohorts (n=16,509), the COVID-19 hospitalized patients (n=159) were significantly younger, with a higher proportion of Hispanic ethnicity, lower proportion of smoking history and fewer comorbidities (P <0.001). COVID-19 patients had a lower IMV rate (15.1 vs 23.2, P=0.016) and shorter time to IMV (2.9 vs 4.1, P <0.001) compared to the COVID-like patients. In the COVID-like training data, the top models achieved excellent performance (AUV > 0.90). Validating in the COVID-19 cohort, the best performing model of predicting IMV was the XGBoost model (AUC: 0.826) trained on the viral pneumonia cohort. Similarly, the XGBoost model trained on all four COVID-like cohorts without ARDS achieved the best performance (AUC: 0.928) in predicting mortality. Important predictors included demographic information (age), vital signs (oxygen saturation), and laboratory values (white blood count, cardiac troponin, albumin, etc.). Our models suffered from class imbalance, that resulted in high negative predictive values and low positive predictive values.We provided a feasible framework for modeling patient deterioration using existing data and AI technology to address data limitations during the onset of a novel, rapidly changing pandemic.

  View details for DOI 10.2196/23026

  View details for PubMedID 33534724

• Assessment of a Clinical Trial-Derived Survival Model in Patients With Metastatic Castration-Resistant Prostate Cancer. JAMA network open Coquet, J. n., Bievre, N. n., Billaut, V. n., Seneviratne, M. n., Magnani, C. J., Bozkurt, S. n., Brooks, J. D., Hernandez-Boussard, T. n. 2021; 4 (1): e2031730

  Abstract

  Randomized clinical trials (RCTs) are considered the criterion standard for clinical evidence. Despite their many benefits, RCTs have limitations, such as costliness, that may reduce the generalizability of their findings among diverse populations and routine care settings.To assess the performance of an RCT-derived prognostic model that predicts survival among patients with metastatic castration-resistant prostate cancer (CRPC) when the model is applied to real-world data from electronic health records (EHRs).The RCT-trained model and patient data from the RCTs were obtained from the Dialogue for Reverse Engineering Assessments and Methods (DREAM) challenge for prostate cancer, which occurred from March 16 to July 27, 2015. This challenge included 4 phase 3 clinical trials of patients with metastatic CRPC. Real-world data were obtained from the EHRs of a tertiary care academic medical center that includes a comprehensive cancer center. In this study, the DREAM challenge RCT-trained model was applied to real-world data from January 1, 2008, to December 31, 2019; the model was then retrained using EHR data with optimized feature selection. Patients with metastatic CRPC were divided into RCT and EHR cohorts based on data source. Data were analyzed from March 23, 2018, to October 22, 2020.Patients who received treatment for metastatic CRPC.The primary outcome was the performance of an RCT-derived prognostic model that predicts survival among patients with metastatic CRPC when the model is applied to real-world data. Model performance was compared using 10-fold cross-validation according to time-dependent integrated area under the curve (iAUC) statistics.Among 2113 participants with metastatic CRPC, 1600 participants were included in the RCT cohort, and 513 participants were included in the EHR cohort. The RCT cohort comprised a larger proportion of White participants (1390 patients [86.9%] vs 337 patients [65.7%]) and a smaller proportion of Hispanic participants (14 patients [0.9%] vs 42 patients [8.2%]), Asian participants (41 patients [2.6%] vs 88 patients [17.2%]), and participants older than 75 years (388 patients [24.3%] vs 191 patients [37.2%]) compared with the EHR cohort. Participants in the RCT cohort also had fewer comorbidities (mean [SD], 1.6 [1.8] comorbidities vs 2.5 [2.6] comorbidities, respectively) compared with those in the EHR cohort. Of the 101 variables used in the RCT-derived model, 10 were not available in the EHR data set, 3 of which were among the top 10 features in the DREAM challenge RCT model. The best-performing EHR-trained model included only 25 of the 101 variables included in the RCT-trained model. The performance of the RCT-trained and EHR-trained models was adequate in the EHR cohort (mean [SD] iAUC, 0.722 [0.118] and 0.762 [0.106], respectively); model optimization was associated with improved performance of the best-performing EHR model (mean [SD] iAUC, 0.792 [0.097]). The EHR-trained model classified 256 patients as having a high risk of mortality and 256 patients as having a low risk of mortality (hazard ratio, 2.7; 95% CI, 2.0-3.7; log-rank P < .001).In this study, although the RCT-trained models did not perform well when applied to real-world EHR data, retraining the models using real-world EHR data and optimizing variable selection was beneficial for model performance. As clinical evidence evolves to include more real-world data, both industry and academia will likely search for ways to balance model optimization with generalizability. This study provides a pragmatic approach to applying RCT-trained models to real-world data.

  View details for DOI 10.1001/jamanetworkopen.2020.31730

  View details for PubMedID 33481032

• Phenotyping severity of patient-centered outcomes using clinical notes: A prostate cancer use case. Learning health systems Bozkurt, S., Paul, R., Coquet, J., Sun, R., Banerjee, I., Brooks, J. D., Hernandez-Boussard, T. 2020; 4 (4): e10237

  Abstract

  A learning health system (LHS) must improve care in ways that are meaningful to patients, integrating patient-centered outcomes (PCOs) into core infrastructure. PCOs are common following cancer treatment, such as urinary incontinence (UI) following prostatectomy. However, PCOs are not systematically recorded because they can only be described by the patient, are subjective and captured as unstructured text in the electronic health record (EHR). Therefore, PCOs pose significant challenges for phenotyping patients. Here, we present a natural language processing (NLP) approach for phenotyping patients with UI to classify their disease into severity subtypes, which can increase opportunities to provide precision-based therapy and promote a value-based delivery system.Patients undergoing prostate cancer treatment from 2008 to 2018 were identified at an academic medical center. Using a hybrid NLP pipeline that combines rule-based and deep learning methodologies, we classified positive UI cases as mild, moderate, and severe by mining clinical notes.The rule-based model accurately classified UI into disease severity categories (accuracy: 0.86), which outperformed the deep learning model (accuracy: 0.73). In the deep learning model, the recall rates for mild and moderate group were higher than the precision rate (0.78 and 0.79, respectively). A hybrid model that combined both methods did not improve the accuracy of the rule-based model but did outperform the deep learning model (accuracy: 0.75).Phenotyping patients based on indication and severity of PCOs is essential to advance a patient centered LHS. EHRs contain valuable information on PCOs and by using NLP methods, it is feasible to accurately and efficiently phenotype PCO severity. Phenotyping must extend beyond the identification of disease to provide classification of disease severity that can be used to guide treatment and inform shared decision-making. Our methods demonstrate a path to a patient centered LHS that could advance precision medicine.

  View details for DOI 10.1002/lrh2.10237

  View details for PubMedID 33083539

  View details for PubMedCentralID PMC7556418

• Linking heterogeneous data to enable knowledge discovery in health care. Hernandez-Boussard, T. AMER ASSOC CANCER RESEARCH. 2020: 19

  View details for Web of Science ID 000567797600013

• Is the firearm epidemic in the US getting worse? Tedesco, D., Adja, K. C., Rallo, F., Reno, C., Fantini, M. P., Hernandez-Boussard, T. OXFORD UNIV PRESS. 2020: V411

  View details for Web of Science ID 000605268700231

• Bias at Warp Speed: How AI may Contribute to the Disparities Gap in the Time of COVID-19. Journal of the American Medical Informatics Association : JAMIA Roosli, E., Rice, B., Hernandez-Boussard, T. 2020

  Abstract

  The COVID-19 pandemic is presenting a disproportionate impact on minorities in terms of infection rate, hospitalizations and mortality. Many believe Artificial Intelligence (AI) is a solution to guide clinical decision making for this novel disease, resulting in the rapid dissemination of under-developed and potentially biased models, which may exacerbate the disparities gap. We believe there is an urgent need to enforce the systematic use of reporting standards and develop regulatory frameworks for a shared COVID-19 data source to address the challenges of bias in AI during this pandemic. There is hope that AI can help guide treatment decisions within this crisis yet given the pervasiveness of biases, a failure to proactively develop comprehensive mitigation strategies during the COVID-19 pandemic risks exacerbating existing health disparities.

  View details for DOI 10.1093/jamia/ocaa210

  View details for PubMedID 32805004

• Phenotyping severity of patient-centered outcomes using clinical notes: A prostate cancer use case LEARNING HEALTH SYSTEMS Bozkurt, S., Paul, R., Coquet, J., Sun, R., Banerjee, I., Brooks, J. D., Hernandez-Boussard, T. 2020

  View details for DOI 10.1002/lrh2.10237

  View details for Web of Science ID 000548944700001

• MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care. Journal of the American Medical Informatics Association : JAMIA Hernandez-Boussard, T., Bozkurt, S., Ioannidis, J. P., Shah, N. H. 2020

  Abstract

  The rise of digital data and computing power have contributed to significant advancements in artificial intelligence (AI), leading to the use of classification and prediction models in health care to enhance clinical decision-making for diagnosis, treatment and prognosis. However, such advances are limited by the lack of reporting standards for the data used to develop those models, the model architecture, and the model evaluation and validation processes. Here, we present MINIMAR (MINimum Information for Medical AI Reporting), a proposal describing the minimum information necessary to understand intended predictions, target populations, and hidden biases, and the ability to generalize these emerging technologies. We call for a standard to accurately and responsibly report on AI in health care. This will facilitate the design and implementation of these models and promote the development and use of associated clinical decision support tools, as well as manage concerns regarding accuracy and bias.

  View details for DOI 10.1093/jamia/ocaa088

  View details for PubMedID 32594179

• Intraocular Pressure Changes after Cataract Surgery in Patients with and without Glaucoma: An Informatics-Based Approach. Ophthalmology. Glaucoma Wang, S. Y., Azad, A. D., Lin, S. C., Hernandez-Boussard, T., Pershing, S. 2020

  Abstract

  PURPOSE: To evaluate changes in intraocular pressure (IOP) after cataract surgery among patients with or without glaucoma using automated extraction of data from electronic health records (EHRs).DESIGN: Retrospective cohort study.PARTICIPANTS: Adults who underwent standalone cataract surgery at a single academic center from 2009-2018.METHODS: Patient information was identified from procedure and billing codes, demographic tables, medication orders, clinical notes, and eye examination fields in the EHR. A previously validated natural language processing pipeline was used to identify laterality of cataract surgery from operative notes and laterality of eye medications from medication orders. Cox proportional hazards modeling evaluated factors associated with the main outcome of sustained postoperative IOP reduction.MAIN OUTCOME MEASURES: Sustained post-cataract surgery IOP reduction, measured at 14 months or the last follow-up while using equal or fewer glaucoma medications compared with baseline and without additional glaucoma laser or surgery on the operative eye.RESULTS: The median follow-up for 7574 eyes of 4883 patients who underwent cataract surgery was 244 days. The mean preoperative IOP for all patients was 15.2 mmHg (standard deviation [SD], 3.4 mmHg), which decreased to 14.2 mmHg (SD, 3.0 mmHg) at 12 months after surgery. Patients with IOP of 21.0 mmHg or more showed mean postoperative IOP reduction ranging from -6.2 to -6.9 mmHg. Cataract surgery was more likely to yield sustained IOP reduction for patients with primary open-angle glaucoma (hazard ratio [HR], 1.19; 95% confidence interval, 1.05-1.36) or narrow angles or angle closure (HR, 1.21; 95% confidence interval, 1.08-1.34) compared with patients without glaucoma. Those with a higher baseline IOP were more likely to achieve postoperative IOP reduction (HR, 1.06 per 1-mmHg increase in baseline IOP; 95% confidence interval, 1.05-1.07).CONCLUSIONS: Our results suggest that patients with primary open-angle glaucoma or with narrow angles or chronic angle closure were more likely to achieve sustained IOP reduction after cataract surgery. Patients with higher baseline IOP had increasingly higher odds of achieving reduction in IOP. This evidence demonstrates the potential usefulness of a pipeline for automated extraction of ophthalmic surgical outcomes from EHR to answer key clinical questions on a large scale.

  View details for DOI 10.1016/j.ogla.2020.06.002

  View details for PubMedID 32703703

• Four distinct patient-reported outcome (PRO) trajectories in longitudinal responses collected before, during, and after chemotherapy. Blayney, D. W., Azad, A., Yilmaz, M., Bozkurt, S., Brooks, J. D., Hernandez-Boussard, T. AMER SOC CLINICAL ONCOLOGY. 2020

  View details for Web of Science ID 000560368301127

• MULTIPARAMETRIC MAGNETIC RESONANCE IMAGING AND RECLASSIFICATION FROM ACTIVE SURVEILLANCE Magnani, C. J., Bievre, N., Erdogdu, B., Baker, L. C., Brooks, J. D., Hernandez-Boussard, T. LIPPINCOTT WILLIAMS & WILKINS. 2020: E342–E343

  View details for Web of Science ID 000527010301653

• Leveraging Digital Data to Inform and Improve Quality Cancer Care. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology Hernandez-Boussard, T., Blayney, D. W., Brooks, J. D. 2020

  Abstract

  BACKGROUND: Efficient capture of routine clinical care and patient outcomes are needed at a population-level, as is evidence on important treatment-related side effects and their effect on well-being and clinical outcomes. The increasing availability of electronic health records (EHRs) offers new opportunities to generate population-level patient-centered evidence on oncological care that can better guide treatment decisions and patient-valued care.METHODS: This study includes patients seeking care at an academic medical center, 2008-2018. Digital data sources are combined to address missingness, inaccuracy, and noise common to EHR data. Clinical concepts were identified and extracted from EHR unstructured data using natural language processing (NLP) and machine/deep learning techniques. All models are trained, tested, and validated on independent data samples using standard metrics.RESULTS: We provide use cases for using EHR data to assess guideline adherence and quality measurements among cancer patients. Pretreatment assessment was evaluated by guideline adherence and quality metrics for cancer staging metrics. Patient outcomes included treatment-related side-effects and patient-reported outcomes.CONCLUSIONS: Advanced technologies applied to EHRs present opportunities to advance population-level quality assessment, to learn from routinely collected clinical data for personalized treatment, and to augment epidemiological and population health studies. The effective use of digital data can inform patient-valued care, quality initiatives and policy guidelines.IMPACT: A comprehensive set of health data analyzed with advanced technologies results in a unique resource that facilitates wide-ranging, innovative, and impactful research on prostate cancer. This work demonstrates novel use of EHRs and technology to advance epidemiological studies and benefit oncological care.

  View details for DOI 10.1158/1055-9965.EPI-19-0873

  View details for PubMedID 32066619

• The rise of non-traumatic extremity compartment syndrome in light of the opioid epidemic. The American journal of emergency medicine Sheckter, C. C., Cebron, U., Suarez, P., Rochlin, D., Tedesco, D., Hernandez-Boussard, T., Curtin, C. 2020

  View details for DOI 10.1016/j.ajem.2020.01.020

  View details for PubMedID 32005410

• Preoperative Factors Associated with Remote Postoperative Pain Resolution and Opioid Cessation in a Mixed Surgical Cohort: Post Hoc Analysis of a Perioperative Gabapentin Trial. Journal of pain research Hah, J. M., Hilmoe, H. n., Schmidt, P. n., McCue, R. n., Trafton, J. n., Clay, D. n., Sharifzadeh, Y. n., Ruchelli, G. n., Hernandez Boussard, T. n., Goodman, S. n., Huddleston, J. n., Maloney, W. J., Dirbas, F. M., Shrager, J. n., Costouros, J. G., Curtin, C. n., Mackey, S. C., Carroll, I. n. 2020; 13: 2959–70

  Abstract

  Preoperative patient-specific risk factors may elucidate the mechanisms leading to the persistence of pain and opioid use after surgery. This study aimed to determine whether similar or discordant preoperative factors were associated with the duration of postoperative pain and opioid use.In this post hoc analysis of a randomized, double-blind, placebo-controlled trial of perioperative gabapentin vs active placebo, 410 patients aged 18-75 years, undergoing diverse operations underwent preoperative assessments of pain, opioid use, substance use, and psychosocial variables. After surgery, a modified Brief Pain Inventory was administered over the phone daily up to 3 months, weekly up to 6 months, and monthly up to 2 years after surgery. Pain and opioid cessation were defined as the first of 5 consecutive days of 0 out of 10 pain or no opioid use, respectively.Overall, 36.1%, 19.8%, and 9.5% of patients continued to report pain, and 9.5%, 2.4%, and 1.7% reported continued opioid use at 3, 6, and 12 months after surgery. Preoperative pain at the future surgical site (every 1-point increase in the Numeric Pain Rating Scale; HR 0.93; 95% CI 0.87-1.00; P=0.034), trait anxiety (every 10-point increase in the Trait Anxiety Inventory; HR 0.79; 95% CI 0.68-0.92; P=0.002), and a history of delayed recovery after injury (HR 0.62; 95% CI 0.40-0.96; P=0.034) were associated with delayed pain cessation. Preoperative opioid use (HR 0.60; 95% CI 0.39-0.92; P=0.020), elevated depressive symptoms (every 5-point increase in the Beck Depression Inventory-II score; HR 0.88; 95% CI 0.80-0.98; P=0.017), and preoperative pain outside of the surgical site (HR 0.94; 95% CI 0.89-1.00; P=0.046) were associated with delayed opioid cessation, while perioperative gabapentin promoted opioid cessation (HR 1.37; 95% CI 1.06-1.77; P=0.016).Separate risk factors for prolonged post-surgical pain and opioid use indicate that preoperative risk stratification for each outcome may identify patients needing personalized care to augment universal protocols for perioperative pain management and conservative opioid prescribing to improve long-term outcomes.

  View details for DOI 10.2147/JPR.S269370

  View details for PubMedID 33239904

  View details for PubMedCentralID PMC7680674

• Contemporary Practices and Complications of Surgery for Thoracic Outlet Syndrome in the United States. Annals of vascular surgery George, E. L., Arya, S. n., Rothenberg, K. A., Hernandez-Broussard, T. n., Ho, V. T., Stern, J. R., Gelabert, H. A., Lee, J. T. 2020

  Abstract

  Thoracic outlet syndrome (TOS) surgery is relatively rare and controversial given the challenges in diagnosis as well as wide variation in symptomatic and functional recovery. Our aims were to measure trends in utilization of TOS surgery, complications, and mortality rates in a nationally representative cohort and compare higher- versus lower-volume centers.The National Inpatient Sample was queried using ICD-9 codes for rib resection and scalenectomy paired with axillo-subclavian aneurysm [arterial (aTOS)], subclavian DVT [venous (vTOS)], or brachial plexus lesions [neurogenic (nTOS)]. Basic descriptive statistics, non-parametric tests for trend, and multivariable hierarchical regression models with random intercept for center were used to compare outcomes for TOS types, trends over time, and higher- and lower-volume hospitals, respectively.There were 3,547 TOS operations (for an estimated 18,210 TOS operations nationally) performed between 2010-2015 (89.2% nTOS, 9.9% vTOS, 0.9% aTOS) with annual case volume increasing significantly over time (p=0.03). Higher-volume centers (≥10 cases/year) represented 5.2% of hospitals and 37.0% of cases, and these centers achieved significantly lower overall major complication (defined as neurologic injury, arterial or venous injury, vascular graft complication, pneumothorax, hemorrhage/hematoma or lymphatic leak) rates [adjusted Odds Ratio (OR) 0.71 (95% confidence interval 0.52-0.98); p=0.04], but no difference in neurologic complications such as brachial plexus injury (aOR 0.69 (0.20-2.43); p=0.56) or vascular injuries/graft complications [aOR 0.71 (0.0.33=1.54); p=0.39]. Overall mortality was 0.6%, neurologic injury was rare (0.3%), and the proportion of patients experiencing complications decreased over time (p=0.03). However, vTOS & aTOS had >2.5 times the odds of major complication compared to nTOS [OR 2.68 (1.88-3.82) & aOR 4.26 (1.78-10.17); p<0.001], and ∼10 times the odds of a vascular complication [aOR 10.37 (5.33-20.19) & aOR 12.93 (3.54-47.37); p<0.001], respectively. As the number of complications decreased, average hospital charges also significantly decreased over time (p<0.001). Total hospital charges were on average higher when surgery was performed in lower-volume centers (< 10 cases/year) compared to higher-volume centers [mean $65,634 (standard deviation 98,796) vs. $45,850 (59,285), p<0.001].The annual number of TOS operations have increased in the United States from 2010-2015, while complications and average hospital charges have decreased. Mortality and neurologic injury remain rare. Higher-volume centers delivered higher-value care: less or similar operative morbidity with lower total hospital charges.

  View details for DOI 10.1016/j.avsg.2020.10.046

  View details for PubMedID 33340669

• Patient Electronic Health Records Score for Preoperative Risk Assessment Before Total Knee Arthroplasty. JB & JS open access Osborne, T. F., Suarez, P. n., Edwards, D. n., Hernandez-Boussard, T. n., Curtin, C. n. 2020; 5 (2): e0061

  Abstract

  Current preoperative risk assessment tools are often cumbersome, have limited accuracy, and are poorly adopted. The Care Assessment Need (CAN) score, an existing tool developed for primary care providers in the U.S. Veterans Administration health-care system (VA), is automatically calculated for individual patients using electronic health record data. Therefore, it could present an efficient preoperative risk assessment tool. The aim of this project was to determine if the CAN score can be repurposed as a preoperative risk assessment tool for patients undergoing total knee arthroplasty (TKA).A multicenter retrospective observational study was conducted using national VA data from 2013 to 2016. The cohort included veterans who underwent TKA identified through ICD-9 (International Classification of Diseases, Ninth Revision), ICD-10, and CPT (Current Procedural Terminology) codes. The focus of the study was the preoperative patient CAN score, a single numerical value ranging from 0 to 99 (with a higher score representing greater risk) that is automatically calculated each week using multiple data points in the VA electronic health record. Study outcomes of interest were 90-day readmission, prolonged hospital stay (>5 days), 1-year mortality, and non-routine patient discharge.The study included 17,210 veterans. Their median preoperative CAN score was 75, although there was substantial variability in patient CAN scores among different facilities. A preoperative CAN score of >75 was significantly associated with mortality (odds ratio [OR] = 3.54), prolonged length of stay (OR = 1.97), 90-day readmission (OR = 1.65), and non-routine discharge (OR = 1.57). The CAN score had good accuracy with a receiver operating characteristic (ROC) curve value of >0.7 for all outcomes except 90-day readmission.The CAN score can be leveraged as an extremely efficient way to risk-stratify patients before TKA, with results that surpass other commonly available and labor-intensive alternatives. As a result, this simple and efficient solution is well positioned for broad adoption as a standardized decision support tool.Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

  View details for DOI 10.2106/JBJS.OA.19.00061

  View details for PubMedID 33123663

  View details for PubMedCentralID PMC7418912

• Clinical Trial Outcomes in Urology: Assessing Early Discontinuation, Results Reporting, and Publication in ClinicalTrials.Gov Registrations 2007-2019. The Journal of urology Magnani, C. J., Steinberg, J. R., Harmange, C. I., Zhang, X. n., Driscoll, C. n., Bell, A. n., Larson, J. n., You, J. G., Weeks, B. T., Turner, B. E., Brooks, J. D. 2020: 101097JU0000000000001432

  Abstract

  Clinical trials require significant resources, but benefits are only realized after trial completion and dissemination of results. We comprehensively assessed early discontinuation, registry results reporting, and publication by trial sponsor and subspecialty in urology trials.We assessed trial registrations from 2007-2019 on ClinicalTrials.gov and publication data from PubMed/MEDLINE. Associations between sponsor or subspecialty with early discontinuation were assessed using Cox Proportional Hazards and results reporting or publication with logistic regression at three years after completion.Of 8,636 trials, 3,541 (41.0%) were completed while 999 (11.6%) were discontinued. 26.9% of completed trials reported results, and 21.6% were published. Sponsors included Academic institutions (53.1%), Industry (37.1%), or US Government (9.8%). Academic-sponsored (adjusted hazard ratio (aHR):0.81, 95% Confidence Interval (CI):0.69-0.96, p=0.012) and Government-sponsored trials (aHR:0.62, 95%CI:0.49-0.78, p <0.001) were less likely than Industry to discontinue early. Government-sponsored trials were more likely to report (adjusted odds ratio (aOR):1.72, 95%CI:1.17-2.54, p=0.006) and publish (aOR:1.89, 95%CI:1.23-2.89, p=0.004). Academic-sponsored were less likely to report (aOR:0.65, CI:0.48-0.88, p=0.006) but more likely to publish (aOR:1.72, 95%CI:1.25-2.37, p <0.001). These outcomes were similar across subspecialties; however, endourology was more likely to discontinue early (aHR:2.00, 95%CI:1.53-2.95, p <0.001), general urology more likely to report results (aOR:1.54, 95%CI:1.13-2.11, p=0.006), and andrology less likely to publish (aOR:0.53, 95%CI:0.35-0.81, p=0.003).Sponsor type is significantly associated with trial completion and dissemination; Government-sponsored trials had the best performance while Industry and Academic-sponsored lagged in trial completion and results reporting, respectively. Subspecialty played a lesser role. Lack of dissemination remains a problem for urology trials.

  View details for DOI 10.1097/JU.0000000000001432

  View details for PubMedID 33079618

• Association between patient-initiated emails and overall 2-year survival in cancer patients undergoing chemotherapy: Evidence from the real-world setting. Cancer medicine Coquet, J. n., Blayney, D. W., Brooks, J. D., Hernandez-Boussard, T. n. 2020

  Abstract

  Prior studies suggest email communication between patients and providers may improve patient engagement and health outcomes. The purpose of this study was to determine whether patient-initiated emails are associated with overall survival benefits among cancer patients undergoing chemotherapy.We identified patient-initiated emails through the patient portal in electronic health records (EHR) among 9900 cancer patients receiving chemotherapy between 2013 and 2018. Email users were defined as patients who sent at least one email 12 months before to 2 months after chemotherapy started. A propensity score-matched cohort analysis was carried out to reduce bias due to confounding (age, primary cancer type, gender, insurance payor, ethnicity, race, stage, income, Charlson score, county of residence). The cohort included 3223 email users and 3223 non-email users. The primary outcome was overall 2-year survival stratified by email use. Secondary outcomes included number of face-to-face visits, prescriptions, and telephone calls. The healthcare teams' response to emails and other forms of communication was also investigated. Finally, a quality measure related to chemotherapy-related inpatient and emergency department visits was evaluated.Overall 2-year survival was higher in patients who were email users, with an adjusted hazard ratio of 0.80 (95 CI 0.72-0.90; p < 0.001). Email users had higher rates of healthcare utilization, including face-to-face visits (63 vs. 50; p < 0.001), drug prescriptions (28 vs. 21; p < 0.001), and phone calls (18 vs. 16; p < 0.001). Clinical quality outcome measure of inpatient use was better among email users (p = 0.015).Patient-initiated emails are associated with a survival benefit among cancer patients receiving chemotherapy and may be a proxy for patient engagement. As value-based payment models emphasize incorporating the patients' voice into their care, email communications could serve as a novel source of patient-generated data.

  View details for DOI 10.1002/cam4.3483

  View details for PubMedID 32986931

• Reporting of demographic data and representativeness in machine learning models using electronic health records. Journal of the American Medical Informatics Association : JAMIA Bozkurt, S. n., Cahan, E. M., Seneviratne, M. G., Sun, R. n., Lossio-Ventura, J. A., Ioannidis, J. P., Hernandez-Boussard, T. n. 2020

  Abstract

  The development of machine learning (ML) algorithms to address a variety of issues faced in clinical practice has increased rapidly. However, questions have arisen regarding biases in their development that can affect their applicability in specific populations. We sought to evaluate whether studies developing ML models from electronic health record (EHR) data report sufficient demographic data on the study populations to demonstrate representativeness and reproducibility.We searched PubMed for articles applying ML models to improve clinical decision-making using EHR data. We limited our search to papers published between 2015 and 2019.Across the 164 studies reviewed, demographic variables were inconsistently reported and/or included as model inputs. Race/ethnicity was not reported in 64%; gender and age were not reported in 24% and 21% of studies, respectively. Socioeconomic status of the population was not reported in 92% of studies. Studies that mentioned these variables often did not report if they were included as model inputs. Few models (12%) were validated using external populations. Few studies (17%) open-sourced their code. Populations in the ML studies include higher proportions of White and Black yet fewer Hispanic subjects compared to the general US population.The demographic characteristics of study populations are poorly reported in the ML literature based on EHR data. Demographic representativeness in training data and model transparency is necessary to ensure that ML models are deployed in an equitable and reproducible manner. Wider adoption of reporting guidelines is warranted to improve representativeness and reproducibility.

  View details for DOI 10.1093/jamia/ocaa164

  View details for PubMedID 32935131

• Acute pain after breast surgery and reconstruction: A two-institution study of surgical factors influencing short-term pain outcomes. Journal of surgical oncology Azad, A. D., Bozkurt, S. n., Wheeler, A. J., Curtin, C. n., Wagner, T. H., Hernandez-Boussard, T. n. 2020

  Abstract

  Acute postoperative pain following surgery is known to be associated with chronic pain development and lower quality of life. We sought to analyze the relationship between differing breast cancer excisional procedures, reconstruction, and short-term pain outcomes.Women undergoing breast cancer excisional procedures with or without reconstruction at two systems: an academic hospital (AH) and Veterans Health Administration (VHA) were included. Average pain scores at the time of discharge and at 30-day follow-up were analyzed across demographic and clinical characteristics. Linear mixed effects modeling was used to assess the relationship between patient/clinical characteristics and interval pain scores with a random slope to account for differences in baseline pain.Our study included 1402 patients at AH and 1435 at VHA, of which 426 AH and 165 patients with VHA underwent reconstruction. Pain scores improved over time and were found to be highest at discharge. Time at discharge, 30-day follow-up, and preoperative opioid use were the strongest predictors of high pain scores. Younger age and longer length of stay were independently associated with worse pain scores.Younger age, preoperative opioid use, and longer length of stay were associated with higher levels of postoperative pain across both sites.

  View details for DOI 10.1002/jso.26070

  View details for PubMedID 32563208

• Integrating Adjuvant Analgesics into Perioperative Pain Practice: Results from an Academic Medical Center PAIN MEDICINE Chin, K., Carroll, I., Desai, K., Asch, S., Seto, T., McDonald, K. M., Curtin, C., Hernandez-Boussard, T. 2020; 21 (1): 161–70

  View details for DOI 10.1093/pm/pnz053

  View details for Web of Science ID 000522867400020

• Improvement in Patient Safety May Precede Policy Changes: Trends in Patient Safety Indicators in the United States, 2000-2013. Journal of patient safety Tedesco, D. n., Moghavem, N. n., Weng, Y. n., Fantini, M. P., Hernandez-Boussard, T. n. 2020

  Abstract

  Quality and safety improvement are global priorities. In the last two decades, the United States has introduced several payment reforms to improve patient safety. The Agency for Healthcare Research and Quality (AHRQ) developed tools to identify preventable inpatient adverse events using administrative data, patient safety indicators (PSIs). The aim of this study was to assess changes in national patient safety trends that corresponded to U.S. pay-for-performance reforms.This is a retrospective, longitudinal analysis to estimate temporal changes in 13 AHRQ's PSIs. National inpatient sample from the AHRQ and estimates were weighted to represent a national sample. We analyzed PSI trends, Center for Medicaid and Medicare Services payment policy changes, and Inpatient Prospective Payment System regulations and notices between 2000 and 2013.Of the 13 PSIs studied, 10 had an overall decrease in rates and 3 had an increase. Joinpoint analysis showed that 12 of 13 PSIs had decreasing or stable trends in the last 5 years of the study. Central-line blood stream infections had the greatest annual decrease (-31.1 annual percent change between 2006 and 2013), whereas postoperative respiratory failure had the smallest decrease (-3.5 annual percent change between 2005 and 2013). With the exception of postoperative hip fracture, significant decreases in trends preceded federal payment reform initiatives.National in-hospital patient safety has significantly improved between 2000 and 2015, as measured by PSIs. In this study, improvements in PSI trends often proceeded policies targeting patient safety events, suggesting that intense public discourses targeting patient safety may drive national policy reforms and that these improved trends may be sustained by the Center for Medicare and Medicaid Services policies that followed.

  View details for DOI 10.1097/PTS.0000000000000615

  View details for PubMedID 32217926

• Clinical Documentation to Predict Factors Associated with Urinary Incontinence Following Prostatectomy for Prostate Cancer RESEARCH AND REPORTS IN UROLOGY Li, K., Banerjee, I., Magnani, C. J., Blayney, D. W., Brooks, J. D., Hernandez-Boussard, T. 2020; 12: 7–14

  View details for DOI 10.2147/RRU.S234178

  View details for Web of Science ID 000512137700001

• The Impact of Hospital Quality on Thyroid Cancer Survival. Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Megwalu, U. C., Ma, Y. n., Hernandez-Boussard, T. n., Divi, V. n., Gomez, S. L. 2020: 194599819900760

  Abstract

  To develop a composite measure of thyroid cancer-specific hospital quality and to evaluate the association between hospital quality and survival in patients with well-differentiated thyroid cancer.Retrospective cohort study.Population-based cancer database.Data were extracted from the California Cancer Registry data set linked with discharge records and hospital characteristics from the California Office of Statewide Health Planning and Development. The study cohort comprised adult patients with well-differentiated thyroid cancer diagnosed between January 1, 2004, and December 31, 2015. Principal component analysis, incorporating hospital volume, adherence to national guidelines, and accreditation/certification status, was used to generate a composite thyroid cancer-specific hospital quality score.Treatment in hospitals ranked in the highest quartile of quality was associated with improved overall survival (OS) (hazard ratio [HR], 0.81; 95% confidence interval [CI], 0.67-0.98) and disease-specific survival (DSS) (HR, 0.72; 95% CI, 0.54-0.98). Treatment in hospitals meeting the combined metric of 10 or more thyroid cancer cases/year and 80% of patients with high-risk tumors treated with total/near-total thyroidectomy was associated with improved OS (HR, 0.80; 95% CI, 0.70-0.90) and DSS (HR, 0.77; 95% CI, 0.64-0.94).Treatment in high-quality hospitals is associated with improved survival outcomes in patients with thyroid cancer. These findings are important because they help identify hospitals that are better suited to treat patients with thyroid cancer and provide actionable targets for quality improvement.

  View details for DOI 10.1177/0194599819900760

  View details for PubMedID 31961755

• Preoperative opioid use and postoperative pain associated with surgical readmissions AMERICAN JOURNAL OF SURGERY Dasinger, E. A., Graham, L. A., Wahl, T. S., Richman, J. S., Baker, S. J., Hawn, M. T., Hernandez-Boussard, T., Rosen, A. K., Mull, H. J., Copeland, L. A., Whittle, J. C., Burns, E. A., Morris, M. S. 2019; 218 (5): 828–35

  View details for DOI 10.1016/j.amjsurg.2019.02.033

  View details for Web of Science ID 000490752400004

• Clinical named-entity recognition: A short comparison. Proceedings. IEEE International Conference on Bioinformatics and Biomedicine Lossio-Ventura, J. A., Boussard, S., Morzan, J., Hernandez-Boussard, T. 2019; 2019: 1548-1550

  Abstract

  The adoption of electronic health records has increased the volume of clinical data, which has opened an opportunity for healthcare research. There are several biomedical annotation systems that have been used to facilitate the analysis of clinical data. However, there is a lack of clinical annotation comparisons to select the most suitable tool for a specific clinical task. In this work, we used clinical notes from the MIMIC-III database and evaluated three annotation systems to identify four types of entities: (1) procedure, (2) disorder, (3) drug, and (4) anatomy. Our preliminary results demonstrate that BioPortal performs well when extracting disorder and drug. This can provide clinical researchers with real-clinical insights into patient's health patterns and it may allow to create a first version of an annotated dataset.

  View details for DOI 10.1109/bibm47256.2019.8983406

  View details for PubMedID 35463810

  View details for PubMedCentralID PMC9028678

• Clustering and topic modeling over tweets: A comparison over a health dataset. Proceedings. IEEE International Conference on Bioinformatics and Biomedicine Lossio-Ventura, J. A., Morzan, J., Alatrista-Salas, H., Hernandez-Boussard, T., Bian, J. 2019; 2019: 1544-1547

  Abstract

  Twitter became the most popular form of social interactions in the healthcare domain. Thus, various teams have evaluated Twitter as an additional source where patients share information about their healthcare with the potential goal to improve their outcomes. Several existing topic modeling and document clustering applications have been adapted to assess tweets showing that the performances of the applications are negatively affected due to the nature and characteristics of tweets. Moreover, Twitter health research has become difficult to measure because of the absence of comparisons between the existing applications. In this paper, we perform an evaluation based on internal indexes of different topic modeling and document clustering applications over two Twitter health-related datasets. Our results show that Online Twitter LDA and Gibbs LDA get a better performance for extracting topics and grouping tweets. We want to provide health practitioners this comparison to select the most suitable application for their tasks.

  View details for DOI 10.1109/bibm47256.2019.8983167

  View details for PubMedID 35463811

  View details for PubMedCentralID PMC9028681

• Automated extraction of ophthalmic surgery outcomes from the electronic health record. International journal of medical informatics Wang, S. Y., Pershing, S., Tran, E., Hernandez-Boussard, T. 2019; 133: 104007

  Abstract

  OBJECTIVE: Comprehensive analysis of ophthalmic surgical outcomes is often restricted by limited methodologies for efficiently and accurately extracting clinical information from electronic health record (EHR) systems because much is in free-text form. This study aims to utilize advanced methods to automate extraction of clinical concepts from the EHR free text to study visual acuity (VA), intraocular pressure (IOP), and medication outcomes of cataract and glaucoma surgeries.METHODS: Patients who underwent cataract or glaucoma surgery at an academic medical center between 2009 and 2018 were identified by Current Procedural Terminology codes. Rule-based algorithms were developed and used on EHR clinical narrative text to extract intraocular lens (IOL) power and implant type, as well as to create a surgery laterality classifier. MedEx (version 1.3.7) was used on free-text clinical notes to extract information on eye medications and compared to information from medication orders. Random samples of free-text notes were reviewed by two independent masked annotators to assess inter-annotator agreement on outcome variable classification and accuracy of classifiers. VA and IOP were available from semi-structured fields.RESULTS: This study cohort included 6347 unique patients, with 8550 stand-alone cataract surgeries, 451 combined cataract/glaucoma surgeries, and 961 glaucoma surgeries without concurrent cataract surgery. The rule-based laterality classifier achieved 100% accuracy compared to manual review of a sample of operative notes by independent masked annotators. For cataract surgery alone, glaucoma surgery alone, or combined cataract/glaucoma surgeries, our automated extraction algorithm achieved 99-100% accuracy compared to manual annotation of samples of notes from each group, including IOL model and IOL power for cataract surgeries, and glaucoma implant for glaucoma surgeries. For glaucoma medications, there was 90.7% inter-annotator agreement. After adjudication, 85.0% of medications identified by MedEx determined to be correct. Determination of surgical laterality enabled evaluation of pre- and postoperative VA and IOP for operative eyes.CONCLUSION: This text-processing pipeline can accurately capture surgical laterality and implant model usage from free-text operative notes of cataract and glaucoma surgeries, enabling extraction of clinical outcomes including visual acuities, intraocular pressure, and medications from the EHR system. Use of this approach with EHRs to assess ophthalmic surgical outcomes can benefit research groups interested in studying the safety and clinical efficacies of different surgical approaches.

  View details for DOI 10.1016/j.ijmedinf.2019.104007

  View details for PubMedID 31706228

• Trajectory analysis for postoperative pain using electronic health records: A nonparametric method with robust linear regression and K-medians cluster analysis. Health informatics journal Weng, Y., Tian, L., Tedesco, D., Desai, K., Asch, S. M., Carroll, I., Curtin, C., McDonald, K. M., Hernandez-Boussard, T. 2019: 1460458219881339

  Abstract

  Postoperative pain scores are widely monitored and collected in the electronic health record, yet current methods fail to fully leverage the data with fast implementation. A robust linear regression was fitted to describe the association between the log-scaled pain score and time from discharge after total knee replacement. The estimated trajectories were used for a subsequent K-medians cluster analysis to categorize the longitudinal pain score patterns into distinct clusters. For each cluster, a mixture regression model estimated the association between pain score and time to discharge adjusting for confounding. The fitted regression model generated the pain trajectory pattern for given cluster. Finally, regression analyses examined the association between pain trajectories and patient outcomes. A total of 3442 surgeries were identified with a median of 22 pain scores at an academic hospital during 2009-2016. Four pain trajectory patterns were identified and one was associated with higher rates of outcomes. In conclusion, we described a novel approach with fast implementation to model patients' pain experience using electronic health records. In the era of big data science, clinical research should be learning from all available data regarding a patient's episode of care instead of focusing on the "average" patient outcomes.

  View details for DOI 10.1177/1460458219881339

  View details for PubMedID 31621460

• Predicting the Incidence of Pressure Ulcers in the Intensive Care Unit Using Machine Learning. EGEMS (Washington, DC) Cramer, E. M., Seneviratne, M. G., Sharifi, H., Ozturk, A., Hernandez-Boussard, T. 2019; 7 (1): 49

  Abstract

  Background: Reducing hospital-acquired pressure ulcers (PUs) in intensive care units (ICUs) has emerged as an important quality metric for health systems internationally. Limited work has been done to characterize the profile of PUs in the ICU using observational data from the electronic health record (EHR). Consequently, there are limited EHR-based prognostic tools for determining a patient's risk of PU development, with most institutions relying on nurse-calculated risk scores such as the Braden score to identify high-risk patients.Methods and Results: Using EHR data from 50,851 admissions in a tertiary ICU (MIMIC-III), we show that the prevalence of PUs at stage 2 or above is 7.8 percent. For the 1,690 admissions where a PU was recorded on day 2 or beyond, we evaluated the prognostic value of the Braden score measured within the first 24 hours. A high-risk Braden score (<=12) had precision 0.09 and recall 0.50 for the future development of a PU. We trained a range of machine learning algorithms using demographic parameters, diagnosis codes, laboratory values and vitals available from the EHR within the first 24 hours. A weighted linear regression model showed precision 0.09 and recall 0.71 for future PU development. Classifier performance was not improved by integrating Braden score elements into the model.Conclusion: We demonstrate that an EHR-based model can outperform the Braden score as a screening tool for PUs. This may be a useful tool for automatic risk stratification early in an admission, helping to guide quality protocols in the ICU, including the allocation and timing of prophylactic interventions.

  View details for DOI 10.5334/egems.307

  View details for PubMedID 31534981

• Extracting Patient-Centered Outcomes from Clinical Notes in Electronic Health Records: Assessment of Urinary Incontinence After Radical Prostatectomy. EGEMS (Washington, DC) Gori, D., Banerjee, I., Chung, B. I., Ferrari, M., Rucci, P., Blayney, D. W., Brooks, J. D., Hernandez-Boussard, T. 2019; 7 (1): 43

  Abstract

  Objective: To assess documentation of urinary incontinence (UI) in prostatectomy patients using unstructured clinical notes from Electronic Health Records (EHRs).Methods: We developed a weakly-supervised natural language processing tool to extract assessments, as recorded in unstructured text notes, of UI before and after radical prostatectomy in a single academic practice across multiple clinicians. Validation was carried out using a subset of patients who completed EPIC-26 surveys before and after surgery. The prevalence of UI as assessed by EHR and EPIC-26 was compared using repeated-measures ANOVA. The agreement of reported UI between EHR and EPIC-26 was evaluated using Cohen's Kappa coefficient.Results: A total of 4870 patients and 716 surveys were included. Preoperative prevalence of UI was 12.7 percent. Postoperative prevalence was 71.8 percent at 3 months, 50.2 percent at 6 months and 34.4 and 41.8 at 12 and 24 months, respectively. Similar rates were recorded by physicians in the EHR, particularly for early follow-up. For all time points, the agreement between EPIC-26 and the EHR was moderate (all p < 0.001) and ranged from 86.7 percent agreement at baseline (Kappa = 0.48) to 76.4 percent agreement at 24 months postoperative (Kappa = 0.047).Conclusions: We have developed a tool to assess documentation of UI after prostatectomy using EHR clinical notes. Our results suggest such a tool can facilitate unbiased measurement of important PCOs using real-word data, which are routinely recorded in EHR unstructured clinician notes. Integrating PCO information into clinical decision support can help guide shared treatment decisions and promote patient-valued care.

  View details for DOI 10.5334/egems.297

  View details for PubMedID 31497615

• Putting the data before the algorithm in big data addressing personalized healthcare NPJ DIGITAL MEDICINE Cahan, E. M., Hernandez-Boussard, T., Thadaney-Israni, S., Rubin, D. L. 2019; 2: 78

  Abstract

  Technologies leveraging big data, including predictive algorithms and machine learning, are playing an increasingly important role in the delivery of healthcare. However, evidence indicates that such algorithms have the potential to worsen disparities currently intrinsic to the contemporary healthcare system, including racial biases. Blame for these deficiencies has often been placed on the algorithm-but the underlying training data bears greater responsibility for these errors, as biased outputs are inexorably produced by biased inputs. The utility, equity, and generalizability of predictive models depend on population-representative training data with robust feature sets. So while the conventional paradigm of big data is deductive in nature-clinical decision support-a future model harnesses the potential of big data for inductive reasoning. This may be conceptualized as clinical decision questioning, intended to liberate the human predictive process from preconceived lenses in data solicitation and/or interpretation. Efficacy, representativeness and generalizability are all heightened in this schema. Thus, the possible risks of biased big data arising from the inputs themselves must be acknowledged and addressed. Awareness of data deficiencies, structures for data inclusiveness, strategies for data sanitation, and mechanisms for data correction can help realize the potential of big data for a personalized medicine era. Applied deliberately, these considerations could help mitigate risks of perpetuation of health inequity amidst widespread adoption of novel applications of big data.

  View details for DOI 10.1038/s41746-019-0157-2

  View details for Web of Science ID 000481541800001

  View details for PubMedID 31453373

  View details for PubMedCentralID PMC6700078

• Real world evidence in cardiovascular medicine: assuring data validity in electronic health record-based studies. Journal of the American Medical Informatics Association : JAMIA Hernandez-Boussard, T., Monda, K. L., Crespo, B. C., Riskin, D. 2019

  Abstract

  OBJECTIVE: With growing availability of digital health data and technology, health-related studies are increasingly augmented or implemented using real world data (RWD). Recent federal initiatives promote the use of RWD to make clinical assertions that influence regulatory decision-making. Our objective was to determine whether traditional real world evidence (RWE) techniques in cardiovascular medicine achieve accuracy sufficient for credible clinical assertions, also known as "regulatory-grade" RWE.DESIGN: Retrospective observational study using electronic health records (EHR), 2010-2016.METHODS: A predefined set of clinical concepts was extracted from EHR structured (EHR-S) and unstructured (EHR-U) data using traditional query techniques and artificial intelligence (AI) technologies, respectively. Performance was evaluated against manually annotated cohorts using standard metrics. Accuracy was compared to pre-defined criteria for regulatory-grade. Differences in accuracy were compared using Chi-square test.RESULTS: The dataset included 10840 clinical notes. Individual concept occurrence ranged from 194 for coronary artery bypass graft to 4502 for diabetes mellitus. In EHR-S, average recall and precision were 51.7% and 98.3%, respectively and 95.5% and 95.3% in EHR-U, respectively. For each clinical concept, EHR-S accuracy was below regulatory-grade, while EHR-U met or exceeded criteria, with the exception of medications.CONCLUSIONS: Identifying an appropriate RWE approach is dependent on cohorts studied and accuracy required. In this study, recall varied greatly between EHR-S and EHR-U. Overall, EHR-S did not meet regulatory grade criteria, while EHR-U did. These results suggest that recall should be routinely measured in EHR-based studes intended for regulatory use. Furthermore, advanced data and technologies may be required to achieve regulatory grade results.

  View details for DOI 10.1093/jamia/ocz119

  View details for PubMedID 31414700

• Perioperative opioid use and pain-related outcomes in the Veterans Health Administration. American journal of surgery Hernandez-Boussard, T., Graham, L. A., Carroll, I., Dasinger, E. A., Titan, A. L., Morris, M. S., Hawn, M. T. 2019

  Abstract

  Understanding variation in perioperative opioid exposure and its effect on patients' outcomes is critical for pain management. This study characterized perioperative exposure to morphine and its association with postoperative pain and 30-day readmissions. We utilized nationwide Veterans Healthcare Administration (VHA) data on four high-volume surgical procedures, 2007-2014. We identified 235,239 Veterans undergoing orthopedic, general, or vascular surgery; 5.4% high trajectories (116.1 OME/Day), 53.2% medium trajectories (39.7 OME/Day), and 41.4% low trajectories (19.1 OME/Day). Modeled estimates suggest that patients in the high OME group had higher risk of a pain-related readmission (OR: 1.59; CI: 1.39, 1.83) compared to the low OME trajectory. Yet when stratified by pain trajectory, patients with high pain and high OME had lower risk of a pain-related readmission compared to patients in the high pain low OME group (OR: 0.76, CI: 0.62, 0.94). In conclusion, patients receiving high perioperative OME are more likely to return to care for pain-related problems. This study highlights opportunities to reduce the amount of prescriptions opioids in the communities.

  View details for DOI 10.1016/j.amjsurg.2019.06.022

  View details for PubMedID 31280840

• Comparison of orthogonal NLP methods for clinical phenotyping and assessment of bone scan utilization among prostate cancer patients JOURNAL OF BIOMEDICAL INFORMATICS Coquet, J., Bozkurt, S., Kan, K. M., Ferrari, M. K., Blayney, D. W., Brooks, J. D., Hernandez-Boussard, T. 2019; 94

  View details for DOI 10.1016/j.jbi.2019.103184

  View details for Web of Science ID 000525692600015

• Integrating Adjuvant Analgesics into Perioperative Pain Practice: Results from an Academic Medical Center. Pain medicine (Malden, Mass.) Chin, K., Carroll, I., Desai, K., Asch, S., Seto, T., McDonald, K. M., Curtin, C., Hernandez-Boussard, T. 2019

  Abstract

  BACKGROUND: Opioid-sparing postoperative pain management therapies are important considering the opioid epidemic. Total knee arthroplasty (TKA) is a common and painful procedure accounting for a large number of opioid prescriptions. Adjuvant analgesics, nonopioid drugs with primary indications other than pain, have shown beneficial pain management and opioid-sparing effects following TKA in clinical trials. We evaluated the adjuvant analgesic gabapentin for its usage patterns and its effects on opioid use, pain, and readmissions.METHODS: This retrospective, observational study included 4,046 patients who received primary TKA between 2009 and 2017 using electronic health records from an academic tertiary care medical institute. Descriptive statistics and multivariate modeling were used to estimate associations between inpatient gabapentin use and adverse pain outcomes as well as inpatient oral morphine equivalents per day (OME).RESULTS: Overall, there was an 8.72% annual increase in gabapentin use (P<0.001). Modeled estimates suggest that gabapentin is associated with a significant decrease in opioid consumption (estimate = 0.63, 95% confidence interval = 0.49-0.82, P<0.001) when controlling for patient characteristics. Patients receiving gabapentin had similar discharge pain scores, follow-up pain scores, and 30-day unplanned readmission rates compared with patients receiving no adjuvant analgesics (P>0.05).CONCLUSIONS: When assessed in a real-world setting over a large cohort of TKA patients, gabapentin is an effective pain management therapy that is associated with reduced opioid consumption-a national priority in this time of opioid crisis-while maintaining the same quality of pain management.

  View details for PubMedID 30933284

• Utilization of Prostate Cancer Quality Metrics for Research and Quality Improvement: A Structured Review JOINT COMMISSION JOURNAL ON QUALITY AND PATIENT SAFETY Gori, D., Dulal, R., Blayney, D. W., Brooks, J. D., Fantini, M. P., McDonald, K. M., Hernandez-Boussard, T. 2019; 45 (3): 217–26

  Abstract

  The shift toward value-based care in the United States emphasizes the role of quality measures in payment models. Many diseases, such as prostate cancer, have a proliferation of quality measures, resulting in resource burden and physician burnout. This study aimed to identify and summarize proposed prostate cancer quality measures and describe their frequency and use in peer-reviewed literature.The PubMed database was used to identify quality measures relevant to prostate cancer care, and included articles in English through April 2018. A gray literature search for other documents was also conducted. After the selection process of the pertinent articles, measure characteristics were abstracted, and uses were summarized for the 10 most frequently utilized measures in the literature.A total of 26 articles were identified for review. Of the 71 proposed prostate cancer quality measures, only 47 were used, and less than 10% of these were endorsed by the National Quality Forum. Process measures were most frequently reported (84.5%). Only 6 outcome measures (8.5%) were proposed-none of which were among the most frequently utilized.Although a high number of proposed prostate cancer quality measures are reported in the literature, few were assessed, and the majority of these were non-endorsed process measures. Process measures were most commonly assessed; outcome measures were rarely evaluated. In a step to close the quality chasm, a "top 5" core set of quality measures for prostate cancer care, including structure, process, and outcomes measures, is suggested. Future studies should consider this comprehensive set of quality measures.

  View details for DOI 10.1016/j.jcjq.2018.06.004

  View details for Web of Science ID 000461797400013

  View details for PubMedID 30236510

• Preoperative opioid use and postoperative pain associated with surgical readmissions. American journal of surgery Dasinger, E. A., Graham, L. A., Wahl, T. S., Richman, J. S., Baker, S. J., Hawn, M. T., Hernandez-Boussard, T., Rosen, A. K., Mull, H. J., Copeland, L. A., Whittle, J. C., Burns, E. A., Morris, M. S. 2019

  Abstract

  BACKGROUND: The extent of preoperative opioid utilization and the relationship with pain-related readmissions are not well understood.METHODS: VA Surgical Quality Improvement Program data on general, vascular, and orthopedic surgeries (2007-2014) were merged with pharmacy data to evaluate preoperative opioid use and pain-related readmissions. Opioid use in the 6-month preoperative period was categorized as none, infrequent, frequent, and daily.RESULTS: In the six-month preoperative period, 65.7% had no opioid use, 16.7% had infrequent use, 6.3% frequent use, and 11.4% were daily opioid users. Adjusted odds of pain-related readmission were higher for opioid-exposed groups vs the opioid-naive group: infrequent (OR 1.17; 95% CI:1.04-1.31), frequent (OR 1.28; 95% CI:1.08-1.52), and daily (OR 1.49; 95% CI:1.27-1.74). Among preoperative opioid users, those with a pain-related readmission had higher daily preoperative oral morphine equivalents (mean 44.5 vs. 36.1, p < 0.001).CONCLUSIONS: Patients using opioids preoperatively experienced higher rates of pain-related readmissions, which increased with frequency and dosage of opioid exposure.

  View details for PubMedID 30879796

• Disparities in Access to Care Following Traumatic Digit Amputation. Hand (New York, N.Y.) Long, C., Suarez, P. A., Hernandez-Boussard, T., Curtin, C. 2019: 1558944718824700

  Abstract

  BACKGROUND: Care of digit amputations ranges from revision amputation to replantation. Many factors determine the treatment type. We looked at the epidemiology of amputation and factors associated with escalation of care after presenting to the emergency department (ED). We hypothesized that disparities in care following digit amputation exist.METHODS: We queried the State ED Databases and State Inpatient Databases of the Healthcare Cost and Utilization Project and developed a cohort using the diagnosis codes for thumb and finger amputation. Escalation of care was defined as patients whose disposition from the ED was referral to a higher level hospital or inpatient admission. Bivariate and multivariable analyses were conducted to identify the characteristics associated with escalation of care.RESULTS: Our cohort included 45 586 patients, of which 37 539 (82.4%) were men; 7130 (15.6%) and 38 456 (84.4%) suffered a thumb or finger amputation, respectively. The mean age was 39.3 ± 20.4 years, and 7487 (16.4%) received escalated care. Female sex (odds ratio [OR] = 0.7) was a negative independent predictor of escalation of care, while high income (OR = 1.1), machinery-related mechanism (OR = 1.8), self-harm (OR = 4.2), thumb amputation (OR = 1.7), Medicaid (OR = 1.3) or Medicare (OR = 1.1) insurance, trauma hospitals (OR = 1.3), and metropolitan teaching hospitals (OR = 1.2) were positive predictors.CONCLUSIONS: Male patients who suffered a thumb and/or self-inflicted amputation, are from a higher income zip code, have Medicaid or Medicare insurance, and present to a teaching trauma center are more likely to receive escalated care. This highlights differences in care that can serve as a starting point for work on barriers to access.

  View details for PubMedID 30701984

• Weakly supervised natural language processing for assessing patient-centered outcome following prostate cancer treatment. JAMIA open Banerjee, I. n., Li, K. n., Seneviratne, M. n., Ferrari, M. n., Seto, T. n., Brooks, J. D., Rubin, D. L., Hemandez-Boussard, T. n. 2019; 2 (1): 150–59

  Abstract

  The population-based assessment of patient-centered outcomes (PCOs) has been limited by the efficient and accurate collection of these data. Natural language processing (NLP) pipelines can determine whether a clinical note within an electronic medical record contains evidence on these data. We present and demonstrate the accuracy of an NLP pipeline that targets to assess the presence, absence, or risk discussion of two important PCOs following prostate cancer treatment: urinary incontinence (UI) and bowel dysfunction (BD).We propose a weakly supervised NLP approach which annotates electronic medical record clinical notes without requiring manual chart review. A weighted function of neural word embedding was used to create a sentence-level vector representation of relevant expressions extracted from the clinical notes. Sentence vectors were used as input for a multinomial logistic model, with output being either presence, absence or risk discussion of UI/BD. The classifier was trained based on automated sentence annotation depending only on domain-specific dictionaries (weak supervision).The model achieved an average F1 score of 0.86 for the sentence-level, three-tier classification task (presence/absence/risk) in both UI and BD. The model also outperformed a pre-existing rule-based model for note-level annotation of UI with significant margin.We demonstrate a machine learning method to categorize clinical notes based on important PCOs that trains a classifier on sentence vector representations labeled with a domain-specific dictionary, which eliminates the need for manual engineering of linguistic rules or manual chart review for extracting the PCOs. The weakly supervised NLP pipeline showed promising sensitivity and specificity for identifying important PCOs in unstructured clinical text notes compared to rule-based algorithms.

  View details for PubMedID 31032481

• Clustering and topic modeling over tweets: A comparison over a health dataset Lossio-Ventura, J., Morzan, J., Alatrista-Salas, H., Hernandez-Boussard, T., Bian, J., Yoo, I. H., Bi, J. B., Hu IEEE. 2019: 1544–47

  View details for Web of Science ID 000555804900285

• Clinical named-entity recognition: A short comparison Lossio-Ventura, J., Boussard, S., Morzan, J., Hernandez-Boussard, T., Yoo, I. H., Bi, J. B., Hu IEEE. 2019: 1548–50

  View details for Web of Science ID 000555804900286

• Machine Learning Approaches for Extracting Stage from Pathology Reports in Prostate Cancer. Studies in health technology and informatics Lenain, R. n., Seneviratne, M. G., Bozkurt, S. n., Blayney, D. W., Brooks, J. D., Hernandez-Boussard, T. n. 2019; 264: 1522–23

  Abstract

  Clinical and pathological stage are defining parameters in oncology, which direct a patient's treatment options and prognosis. Pathology reports contain a wealth of staging information that is not stored in structured form in most electronic health records (EHRs). Therefore, we evaluated three supervised machine learning methods (Support Vector Machine, Decision Trees, Gradient Boosting) to classify free-text pathology reports for prostate cancer into T, N and M stage groups.

  View details for DOI 10.3233/SHTI190515

  View details for PubMedID 31438212

• Is it possible to automatically assess pretreatment digital rectal examination documentation using natural language processing? A single-centre retrospective study. BMJ open Bozkurt, S. n., Kan, K. M., Ferrari, M. K., Rubin, D. L., Blayney, D. W., Hernandez-Boussard, T. n., Brooks, J. D. 2019; 9 (7): e027182

  Abstract

  To develop and test a method for automatic assessment of a quality metric, provider-documented pretreatment digital rectal examination (DRE), using the outputs of a natural language processing (NLP) framework.An electronic health records (EHR)-based prostate cancer data warehouse was used to identify patients and associated clinical notes from 1 January 2005 to 31 December 2017. Using a previously developed natural language processing pipeline, we classified DRE assessment as documented (currently or historically performed), deferred (or suggested as a future examination) and refused.We investigated the quality metric performance, documentation 6 months before treatment and identified patient and clinical factors associated with metric performance.The cohort included 7215 patients with prostate cancer and 426 227 unique clinical notes associated with pretreatment encounters. DREs of 5958 (82.6%) patients were documented and 1257 (17.4%) of patients did not have a DRE documented in the EHR. A total of 3742 (51.9%) patient DREs were documented within 6 months prior to treatment, meeting the quality metric. Patients with private insurance had a higher rate of DRE 6 months prior to starting treatment as compared with Medicaid-based or Medicare-based payors (77.3%vs69.5%, p=0.001). Patients undergoing chemotherapy, radiation therapy or surgery as the first line of treatment were more likely to have a documented DRE 6 months prior to treatment.EHRs contain valuable unstructured information and with NLP, it is feasible to accurately and efficiently identify quality metrics with current documentation clinician workflow.

  View details for DOI 10.1136/bmjopen-2018-027182

  View details for PubMedID 31324681

• PSA Testing Use and Prostate Cancer Diagnostic Stage After the 2012 U.S. Preventive Services Task Force Guideline Changes. Journal of the National Comprehensive Cancer Network : JNCCN Magnani, C. J., Li, K. n., Seto, T. n., McDonald, K. M., Blayney, D. W., Brooks, J. D., Hernandez-Boussard, T. n. 2019; 17 (7): 795–803

  Abstract

  Most patients with prostate cancer are diagnosed with low-grade, localized disease and may not require definitive treatment. In 2012, the U.S. Preventive Services Task Force (USPSTF) recommended against prostate cancer screening to address overdetection and overtreatment. This study sought to determine the effect of guideline changes on prostate-specific antigen (PSA) screening and initial diagnostic stage for prostate cancer.A difference-in-differences analysis was conducted to compare changes in PSA screening (exposure) relative to cholesterol testing (control) after the 2012 USPSTF guideline changes, and chi-square test was used to determine whether there was a subsequent decrease in early-stage, low-risk prostate cancer diagnoses. Data were derived from a tertiary academic medical center's electronic health records, a national commercial insurance database (OptumLabs), and the SEER database for men aged ≥35 years before (2008-2011) and after (2013-2016) the guideline changes.In both the academic center and insurance databases, PSA testing significantly decreased for all men compared with the control. The greatest decrease was among men aged 55 to 74 years at the academic center and among those aged ≥75 years in the commercial database. The proportion of early-stage prostate cancer diagnoses (

  View details for DOI 10.6004/jnccn.2018.7274

  View details for PubMedID 31319390

• Comparison of Orthogonal NLP Methods for Clinical Phenotyping and Assessment of Bone Scan Utilization among Prostate Cancer Patients. Journal of biomedical informatics Coquet, J. n., Bozkurt, S. n., Kan, K. M., Ferrari, M. K., Blayney, D. W., Brooks, J. D., Hernandez-Boussard, T. n. 2019: 103184

  Abstract

  Clinical care guidelines recommend that newly diagnosed prostate cancer patients at high risk for metastatic spread receive a bone scan prior to treatment and that low risk patients not receive it. The objective was to develop an automated pipeline to interrogate heterogeneous data to evaluate the use of bone scans using a two different Natural Language Processing (NLP) approaches.Our cohort was divided into risk groups based on Electronic Health Records (EHR). Information on bone scan utilization was identified in both structured data and free text from clinical notes. Our pipeline annotated sentences with a combination of a rule-based method using the ConText algorithm (a generalization of NegEx) and a Convolutional Neural Network (CNN) method using word2vec to produce word embeddings.A total of 5,500 patients and 369,764 notes were included in the study. A total of 39% of patients were high-risk and 73% of these received a bone scan; of the 18% low risk patients, 10% received one. The accuracy of CNN model outperformed the rule-based model one (F-measure = 0.918 and 0.897 respectively). We demonstrate a combination of both models could maximize precision or recall, based on the study question.Using structured data, we accurately classified patients' cancer risk group, identified bone scan documentation with two NLP methods, and evaluated guideline adherence. Our pipeline can be used to provide concrete feedback to clinicians and guide treatment decisions.

  View details for PubMedID 31014980

• Merging heterogeneous clinical data to enable knowledge discovery. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Seneviratne, M. G., Kahn, M. G., Hernandez-Boussard, T. 2019; 24: 439–43

  Abstract

  The vision of precision medicine relies on the integration of large-scale clinical, molecular and environmental datasets. Data integration may be thought of along two axes: data fusion across institutions, and data fusion across modalities. Cross-institutional data sharing that maintains semantic integrity hinges on the adoption of data standards and a push toward ontology-driven integration. The goal should be the creation of query-able data repositories spanning primary and tertiary care providers, disease registries, research organizations etc. to produce rich longitudinal datasets. Cross-modality sharing involves the integration of multiple data streams, from structured EHR data (diagnosis codes, laboratory tests) to genomics, imaging, monitors and patient-generated data including wearable devices. This integration presents unique technical, semantic, and ethical challenges; however recent work suggests that multi-modal clinical data can significantly improve the performance of phenotyping and prediction algorithms, powering knowledge discovery at the patient- and population-level.

  View details for PubMedID 30864344

• Predicting inadequate postoperative pain management in depressed patients: A machine learning approach. PloS one Parthipan, A., Banerjee, I., Humphreys, K., Asch, S. M., Curtin, C., Carroll, I., Hernandez-Boussard, T. 2019; 14 (2): e0210575

  Abstract

  Widely-prescribed prodrug opioids (e.g., hydrocodone) require conversion by liver enzyme CYP-2D6 to exert their analgesic effects. The most commonly prescribed antidepressant, selective serotonin reuptake inhibitors (SSRIs), inhibits CYP-2D6 activity and therefore may reduce the effectiveness of prodrug opioids. We used a machine learning approach to identify patients prescribed a combination of SSRIs and prodrug opioids postoperatively and to examine the effect of this combination on postoperative pain control. Using EHR data from an academic medical center, we identified patients receiving surgery over a 9-year period. We developed and validated natural language processing (NLP) algorithms to extract depression-related information (diagnosis, SSRI use, symptoms) from structured and unstructured data elements. The primary outcome was the difference between preoperative pain score and postoperative pain at discharge, 3-week and 8-week time points. We developed computational models to predict the increase or decrease in the postoperative pain across the 3 time points by using the patient's EHR data (e.g. medications, vitals, demographics) captured before surgery. We evaluate the generalizability of the model using 10-fold cross-validation method where the holdout test method is repeated 10 times and mean area-under-the-curve (AUC) is considered as evaluation metrics for the prediction performance. We identified 4,306 surgical patients with symptoms of depression. A total of 14.1% were prescribed both an SSRI and a prodrug opioid, 29.4% were prescribed an SSRI and a non-prodrug opioid, 18.6% were prescribed a prodrug opioid but were not on SSRIs, and 37.5% were prescribed a non-prodrug opioid but were not on SSRIs. Our NLP algorithm identified depression with a F1 score of 0.95 against manual annotation of 300 randomly sampled clinical notes. On average, patients receiving prodrug opioids had lower average pain scores (p<0.05), with the exception of the SSRI+ group at 3-weeks postoperative follow-up. However, SSRI+/Prodrug+ had significantly worse pain control at discharge, 3 and 8-week follow-up (p < .01) compared to SSRI+/Prodrug- patients, whereas there was no difference in pain control among the SSRI- patients by prodrug opioid (p>0.05). The machine learning algorithm accurately predicted the increase or decrease of the discharge, 3-week and 8-week follow-up pain scores when compared to the pre-operative pain score using 10-fold cross validation (mean area under the receiver operating characteristic curve 0.87, 0.81, and 0.69, respectively). Preoperative pain, surgery type, and opioid tolerance were the strongest predictors of postoperative pain control. We provide the first direct clinical evidence that the known ability of SSRIs to inhibit prodrug opioid effectiveness is associated with worse pain control among depressed patients. Current prescribing patterns indicate that prescribers may not account for this interaction when choosing an opioid. The study results imply that prescribers might instead choose direct acting opioids (e.g. oxycodone or morphine) in depressed patients on SSRIs.

  View details for PubMedID 30726237

• Understanding Patient Attitudes Toward Multifocal Intraocular Lenses in Online Medical Forums Through Sentiment Analysis Wang, S. Y., Hernandez-Boussard, T., Chang, R. T., Pershing, S., OhnoMachado, L., Seroussi, B. IOS PRESS. 2019: 1378–82

  View details for DOI 10.3233/SHT1190453

  View details for Web of Science ID 000569653400278

• Practice Patterns in Perioperative Nonopioid Analgesic Administration by Anesthesiologists in a Veterans Affairs Hospital. Pain medicine (Malden, Mass.) Kwong, J. Z., Mudumbai, S. C., Hernandez-Boussard, T. n., Popat, R. A., Mariano, E. R. 2019

  Abstract

  Although multimodal analgesia (MMA) is recommended for perioperative pain management, previous studies have found substantial variability in its utilization. To better understand the factors that influence anesthesiologists' choices, we assessed the associations between patient or surgical characteristics and number of nonopioid analgesic modes received intraoperatively across a variety of surgeries in a university-affiliated Veteran Affairs hospital.We included elective inpatient surgeries (orthopedic, thoracic, spine, abdominal, and pelvic procedures) that used at least one nonopioid analgesic within a one-year period. Multivariable multinomial logistic regression models were used to estimate adjusted odds ratios and 95% confidence intervals (CIs). We also described the combinations of analgesia used in each surgical subtype and conducted exploratory analyses to test the associations between the number of modes used and postoperative outcomes.Of the 1,087 procedures identified, 33%, 53%, and 14% were managed with one, two, and three or more modes, respectively. Older patients had lower odds of receiving three or more modes (adjusted odds ratio [aOR] = 0.28, 95% confidence interval [CI] = 0.15-0.52), as were patients with more comorbidities (two modes: aOR = 0.87, 95% CI = 0.79-0.96; three or more modes: aOR = 0.81, 95% CI = 0.71-0.94). Utilization varied across surgical subtypes P < 0.0001). Increasing the number of modes, particularly use of regional anesthesia, was associated with shorter length of stay.Our study suggests that age, comorbidities, and surgical type contribute to variability in MMA utilization. Risks and benefits of multiple modes should be carefully considered for older and sicker patients. Future directions include developing patient- and procedure-specific perioperative MMA recommendations.

  View details for DOI 10.1093/pm/pnz226

  View details for PubMedID 31559430

• Understanding Patient Attitudes Toward Multifocal Intraocular Lenses in Online Medical Forums Through Sentiment Analysis. Studies in health technology and informatics Wang, S. Y., Hernandez-Boussard, T. n., Chang, R. T., Pershing, S. n. 2019; 264: 1378–82

  Abstract

  Multifocal intraocular lens implants (IOLs) are a premium option for cataract surgery which patients may purchase to achieve improved spectacle-independence for near vision but may have trade-offs with visual quality. We demonstrate the use of sentiment analysis to evaluate multifocal lenses discussed on MedHelp, a leading online health forum. A search for "multifocal IOL" was performed on MedHelp.org on November 1, 2016, yielding relevant patient posts. Sentiment analysis was performed using IBM's Watson, which extracted 30,066 unique keywords and their associated sentiment scores from 7495 posts written by 1474 unique patient users. Keywords associated with monovision, monofocal, and toric lenses had positive mean sentiment, significantly higher than for keywords associated with multifocals, which had negative mean sentiment (p < 0.001, ANOVA). Many keywords represented complaints and were associated with negative sentiment, including glare, halo, and ghosting. Sentiment analysis can provide insights into patient perspectives towards multifocal lenses by interpreting online patient posts.

  View details for DOI 10.3233/SHTI190453

  View details for PubMedID 31438152

• Extremely large outlier treatment effects may be a footprint of bias in trials from less developed countries: randomized trials of gabapentinoids. Journal of clinical epidemiology Desai, K., Carroll, I., Asch, S., Hernandez-Boussard, T., Ioannidis, J. P. 2018

  Abstract

  OBJECTIVE: Court documents have proven that a manufacturer-orchestrated strategy tried to promote gabapentin by distorting evidence in randomized trials. Given this background, we aimed to assess whether implausibly large treatment effects for gabapentin and for a similar gabapentinoid, pregabalin may have been published.STUDY DESIGN AND SETTING: We identified meta-analyses on gabapentin or pregabalin on any outcome from Google Scholar, PubMed and EMBASE. We explored excess of significance in meta-analyses and whether outlier studies with extreme results (differing >0.8 standard deviations from the summary effect of the meta-analysis) were scrutinized.RESULTS: All 10 evaluated meta-analyses showed statistically significant favorable findings. Heterogeneity I2 estimates exceeding 90% were noted in 4 meta-analyses of post-operative pain. In these 4 meta-analyses, 77 studies had estimates differing >0.8 standard deviations from the summary estimate. 39/77 represented extremely favorable results and 33 of them came from less developed countries with no tradition of clinical research, 22 reported no information on funding and 20 reported no conflicts of interest. Conversely, 27/38 studies with unfavorable results came from more developed countries.CONCLUSION: Extremely favorable outlier studies in the meta-analyzed literature of gabapentin and pregabalin may be a footprint of bias in studies done in less developed countries.

  View details for PubMedID 30366063

• Thirty-day unplanned postoperative inpatient and emergency department visits following thoracotomy. The Journal of surgical research Shaffer, R., Backhus, L., Finnegan, M. A., Remington, A. C., Kwong, J. Z., Curtin, C., Hernandez-Boussard, T. 2018; 230: 117–24

  Abstract

  BACKGROUND: Unplanned visits to the emergency department (ED) and inpatient setting are expensive and associated with poor outcomes in thoracic surgery. We assessed 30-d postoperative ED visits and inpatient readmissions following thoracotomy, a high morbidity procedure.MATERIALS AND METHODS: We retrospectively analyzed inpatient and ED administrative data from California, Florida, and New York, 2010-2011. "Return to care" was defined as readmission to inpatient facility or ED within 30 d of discharge. Factors associated with return to care were analyzed via multivariable logistic regressions with a fixed effect for hospital variability.RESULTS: Of 30,154 thoracotomies, 6.3% were admitted to the ED and 10.2% to the inpatient setting within 30 d of discharge. Increased risk of inpatient readmission was associated with Medicare (odds ratio [OR] 1.30; P<0.001) and Medicaid (OR 1.31; P<0.0001) insurance status compared to private insurance and black race (OR 1.18; P=0.02) compared to white race. Lung cancer diagnosis (OR 0.83; P<0.001) and higher median income (OR 0.89; P=0.04) were associated with decreased risk of inpatient readmission. Postoperative ED visits were associated with Medicare (OR 1.24; P<0.001) and Medicaid insurance status (OR 1.59; P<0.001) compared to private insurance and Hispanic race (OR 1.19; P=0.04) compared to white race.CONCLUSIONS: Following thoracotomy, postoperative ED visits and inpatient readmissions are common. Patients with public insurance were at high risk for readmission, while patients with underlying lung cancer diagnosis had a lower readmission risk. Emphasizing postoperative management in at-risk populations could improve health outcomes and reduce unplanned returns to care.

  View details for PubMedID 30100026

• Impact of rehabilitation on mortality and readmissions after surgery for hip fracture BMC HEALTH SERVICES RESEARCH Tedesco, D., Gibertoni, D., Rucci, P., Hernandez-Boussard, T., Rosa, S., Bianciardi, L., Rolli, M., Fantini, M. 2018; 18: 701

  Abstract

  Hip fracture in elderly patients is a rising global public health concern because of population ageing, and increasing frailty. Long-term morbidity related to poor management of hip fracture is associated with decreased quality of life, survival, and increase in healthcare costs. Receiving postoperative rehabilitation is associated with better outcomes and a higher likelihood of returning to pre-existing level of functioning. However little is known about which postoperative rehabilitation pathways are more effective to optimize patient outcomes. Few studies have analyzed postoperative rehabilitation pathways in a universal healthcare system. The aim of this study is to analyze the impact of post-acute rehabilitation pathways on mortality and readmission in elderly patients undergoing surgery for hip fracture in a large metropolitan area in Italy.In this retrospective cohort study, we analyzed 6-month mortality from admission and 6-month readmission after hospital discharge in patients who underwent surgical repair for hip fracture in the hospitals of the Bologna metropolitan area between 1.1.2013 and 30.6.2014. Data were drawn from the regional hospital discharge records database. Kaplan-Meier estimates and multiple Cox regression were used to analyze mortality as a function of rehabilitation pathways. Multiple logistic regression determined predictors of readmission.The study population includes 2208 patients, mostly women (n = 1677, 76%), with a median age of 83.8 years. Hospital rehabilitation was provided to 519 patients (23.5%), 907 (41.1%) received rehabilitation in private inpatient rehabilitation facilities (IRF) accredited by the National Health System, and 782 (35.4%) received no post-acute rehabilitation. Compared with patient receiving hospital rehabilitation, the other groups showed significantly higher mortality risks (no rehabilitation, Hazard Ratio (HR) = 2.19, 95%CI = 1.54-3.12, p < 0.001; IRF rehabilitation, HR = 1.66, 95%CI = 1.54-1.79, p < 0.001). The risk of readmission did not differ significantly among rehabilitation pathways.Intensive hospital rehabilitation was significantly associated with a lower risk of mortality compared to IRF rehabilitation and no rehabilitation. Our results may help in the development of evidence-based recommendations aimed to improve resource utilization and quality of care in hip fracture patients. Further research is warranted to investigate the impact of the rehabilitation pathway on other outcomes, such as patients' functional status and quality of life.

  View details for PubMedID 30200950

• Leveraging Health Information Technology to Measure and Report Patient Centered Outcomes Hernandez-Boussard, T., Zimlichman, E. OXFORD UNIV PRESS. 2018: 62–63

  View details for DOI 10.1093/intqhc/mzy167.96

  View details for Web of Science ID 000458655100097

• Utilization and effectiveness of multimodal discharge analgesia for postoperative pain management. The Journal of surgical research Desai, K., Carroll, I., Asch, S. M., Seto, T., McDonald, K. M., Curtin, C., Hernandez-Boussard, T. 2018; 228: 160–69

  Abstract

  BACKGROUND: Although evidence-based guidelines recommend a multimodal approach to pain management, limited information exists on adherence to these guidelines and its association with outcomes in a generalized population. We sought to assess the association between discharge multimodal analgesia and postoperative pain outcomes in two diverse health care settings.METHODS: We evaluated patients undergoing four common surgeries associated with high pain in electronic health records from an academic hospital (AH) and Veterans Health Administration (VHA). Multimodal analgesia at discharge was characterized as opioids in combination with acetaminophen (O+A) and nonsteroidal antiinflammatory (O+A+N) drugs. Hierarchical models estimated associations of analgesia with 45-d follow-up pain scores and 30-d readmissions.RESULTS: We identified 7893 patients at AH and 34,581 at VHA. In both settings, most patients were discharged with O+A (60.6% and 54.8%, respectively), yet a significant proportion received opioids alone (AH: 24.3% and VHA: 18.8%). Combining acetaminophen with opioids was associated with decreased follow-up pain in VHA (Odds ratio [OR]: 0.86, 95% confidence interval [CI]: 0.79, 0.93) and readmissions (AH OR: 0.74, CI: 0.60, 0.90; VHA OR: 0.89, CI: 0.82, 0.96). Further addition of nonsteroidal antiinflammatory drugs was associated with further decreased follow-up pain (AH OR: 0.71, CI: 0.53, 0.96; VHA OR: 0.77, CI: 0.69, 0.86) and readmissions (AH OR: 0.46, CI: 0.31, 0.69; VHA OR: 0.84, CI: 0.76, 0.93). In both systems, patients receiving multimodal analgesia received 10%-40% less opioids per day compared to opioids only.CONCLUSIONS: A majority of surgical patients receive a multimodal pain approach at discharge yet many receive only opioids. Multimodal regimen at discharge was associated with better follow-up pain and all-cause readmissions compared to the opioid-only regimen.

  View details for PubMedID 29907207

• Architecture and Implementation of a Clinical Research Data Warehouse for Prostate Cancer. EGEMS (Washington, DC) Seneviratne, M. G., Seto, T., Blayney, D. W., Brooks, J. D., Hernandez-Boussard, T. 2018; 6 (1): 13

  Abstract

  Background: Electronic health record (EHR) based research in oncology can be limited by missing data and a lack of structured data elements. Clinical research data warehouses for specific cancer types can enable the creation of more robust research cohorts.Methods: We linked data from the Stanford University EHR with the Stanford Cancer Institute Research Database (SCIRDB) and the California Cancer Registry (CCR) to create a research data warehouse for prostate cancer. The database was supplemented with information from clinical trials, natural language processing of clinical notes and surveys on patient-reported outcomes.Results: 11,898 unique prostate cancer patients were identified in the Stanford EHR, of which 3,936 were matched to the Stanford cancer registry and 6153 in the CCR. 7158 patients with EHR data and at least one of SCIRDB and CCR data were initially included in the warehouse.Conclusions: A disease-specific clinical research data warehouse combining multiple data sources can facilitate secondary data use and enhance observational research in oncology.

  View details for PubMedID 30094285

• Evidence of Drug-Free Interventions for Postoperative Pain Management After Total Knee Arthroplasty-Reply. JAMA surgery Hernandez-Boussard, T. n., Gori, D. n., Tedesco, D. n. 2018

  View details for PubMedID 29387887

• Advances in Electronic Phenotyping: From Rule-Based Definitions to Machine Learning Models ANNUAL REVIEW OF BIOMEDICAL DATA SCIENCE, VOL 1 Banda, J. M., Seneviratne, M., Hernandez-Boussard, T., Shah, N. H., Altman, R. B., Levitt, M. 2018; 1: 53–68

  View details for DOI 10.1146/annurev-biodatasci-080917-013315

  View details for Web of Science ID 000466876200003

• Identifying Cases of Metastatic Prostate Cancer Using Machine Learning on Electronic Health Records. AMIA ... Annual Symposium proceedings. AMIA Symposium Seneviratne, M. G., Banda, J. M., Brooks, J. D., Shah, N. H., Hernandez-Boussard, T. M. 2018; 2018: 1498–1504

  Abstract

  Cancer stage is rarely captured in structured form in the electronic health record (EHR). We evaluate the performance of a classifier, trained on structured EHR data, in identifying prostate cancer patients with metastatic disease. Using EHR data for a cohort of 5,861 prostate cancer patients mapped to the Observational Health Data Sciences and Informatics (OHDSI) data model, we constructed feature vectors containing frequency counts of conditions, procedures, medications, observations and laboratory values. Staging information from the California Cancer Registry was used as the ground-truth. For identifying patients with metastatic disease, a random forest model achieved precision and recall of 0.90, 0.40 using data within 12 months of diagnosis. This compared to precision 0.33, recall 0.54 for an ICD code-based query. High-precision classifiers using hundreds of structured data elements significantly outperform ICD queries, and may assist in identifying cohorts for observational research or clinical trial matching.

  View details for PubMedID 30815195

• An Automated Feature Engineering for Digital Rectal Examination Documentation using Natural Language Processing. AMIA ... Annual Symposium proceedings. AMIA Symposium Bozkurt, S., Park, J. I., Kan, K. M., Ferrari, M., Rubin, D. L., Brooks, J. D., Hernandez-Boussard, T. 2018; 2018: 288–94

  Abstract

  Digital rectal examination (DRE) is considered a quality metric for prostate cancer care. However, much of the DRE related rich information is documented as free-text in clinical narratives. Therefore, we aimed to develop a natural language processing (NLP) pipeline for automatic documentation of DRE in clinical notes using a domain-specific dictionary created by clinical experts and an extended version of the same dictionary learned by clinical notes using distributional semantics algorithms. The proposed pipeline was compared to a baseline NLP algorithm and the results of the proposed pipeline were found superior in terms of precision (0.95) and recall (0.90) for documentation of DRE. We believe the rule-based NLP pipeline enriched with terms learned from the whole corpus can provide accurate and efficient identification of this quality metric.

  View details for PubMedID 30815067

• Distribution of global health measures from routinely collected PROMIS surveys in patients with breast cancer or prostate cancer. Cancer Seneviratne, M. G., Bozkurt, S. n., Patel, M. I., Seto, T. n., Brooks, J. D., Blayney, D. W., Kurian, A. W., Hernandez-Boussard, T. n. 2018

  Abstract

  The collection of patient-reported outcomes (PROs) is an emerging priority internationally, guiding clinical care, quality improvement projects and research studies. After the deployment of Patient-Reported Outcomes Measurement Information System (PROMIS) surveys in routine outpatient workflows at an academic cancer center, electronic health record data were used to evaluate survey completion rates and self-reported global health measures across 2 tumor types: breast and prostate cancer.This study retrospectively analyzed 11,657 PROMIS surveys from patients with breast cancer and 4411 surveys from patients with prostate cancer, and it calculated survey completion rates and global physical health (GPH) and global mental health (GMH) scores between 2013 and 2018.A total of 36.6% of eligible patients with breast cancer and 23.7% of patients with prostate cancer completed at least 1 survey, with completion rates lower among black patients for both tumor types (P < .05). The mean T scores (calibrated to a general population mean of 50) for GPH were 48.4 ± 9 for breast cancer and 50.6 ± 9 for prostate cancer, and the GMH scores were 52.7 ± 8 and 52.1 ± 9, respectively. GPH and GMH were frequently lower among ethnic minorities, patients without private health insurance, and those with advanced disease.This analysis provides important baseline data on patient-reported global health in breast and prostate cancer. Demonstrating that PROs can be integrated into clinical workflows, this study shows that supportive efforts may be needed to improve PRO collection and global health endpoints in vulnerable populations.

  View details for PubMedID 30512191

• Secondary use of electronic medical records for clinical research: Challenges and Opportunities. Convergent science physical oncology Yim, W. W., Wheeler, A. J., Curtin, C. n., Wagner, T. H., Hernandez-Boussard, T. n. 2018; 4 (1)

  Abstract

  With increasingly ubiquitous electronic medical record (EMR) implementation accelerated by the adoption of the HITECH Act, there is much interest in the secondary use of collected data to improve outcomes and promote personalized medicine. A plethora of research has emerged using EMRs to investigate clinical research questions and assess variations in both treatments and outcomes. However, whether because of genuine complexities of modeling disease physiology or because of practical problems regarding data capture, data accuracy, and data completeness, the state of current EMR research is challenging and gives rise to concerns regarding study accuracy and reproducibility. This work explores challenges in how different experimental design decisions can influence results using a specific example of breast cancer patients undergoing excision and reconstruction surgeries from EMRs in an academic hospital and the Veterans Health Administration (VHA) We discuss emerging strategies that will mitigate these limitations, including data sharing, application of natural language processing, and improved EMR user design.

  View details for PubMedID 29732166

  View details for PubMedCentralID PMC5933881

• Defining Postoperative Opioid Needs Among Preoperative Opioid Users. JAMA surgery Hah, J. n., Hernandez-Boussard, T. n. 2018

  View details for PubMedID 29590286

• Treatment of Degenerative Lumbar Spondylolisthesis With Fusion or Decompression Alone Results in Similar Rates of Reoperation at 5 Years. Clinical spine surgery Vorhies, J. S., Hernandez-Boussard, T. n., Alamin, T. n. 2018; 31 (1): E74–E79

  Abstract

  Population-based analysis of administrative discharge records from California, Florida, and New York inpatient, ambulatory, and emergency department settings between 2005 and 2011, utilizing Healthcare Cost and Utilization Project data.We aimed to compare, and characterize rates of reoperation and readmission among patients with degenerative spondylolisthesis treated with surgical decompression alone versus fusion.Degenerative lumbar spondylolisthesis with stenosis can be treated by decompression with or without fusion. Fusion has traditionally been preferred. We hypothesized that rates of reoperation after decompression alone would be higher than after fusion.We undertook a population-based analysis of administrative discharge records from California, Florida, and New York inpatient, ambulatory, and emergency department settings between 2005 and 2011, with Healthcare Cost and Utilization Project data. We identified all patients who had degenerative spondylolisthesis who were treated with decompression alone or with fusion and compared their rates of reoperation at 1, 3, and 5 years from the index operation. We used descriptive statistics and a hierarchical logistic regression model to generate risk-adjusted odds of all-cause readmissions.Our study consisted of 75,024 patients with spondylolisthesis; 6712 (8.95%) of them underwent decompression alone and 68,312 (91.05%) of them underwent fusion. Rates of reoperation were higher for decompression versus fusion at 1 year; 6.87% versus 5.53% (P≤0.001), but at 3 years; 13.86% versus 12.91% (P=0.18) and 5 years; 16.9% versus 17.7% (P=0.398) years rates of reoperation were not statistically different. Patients treated with decompression alone that had a second operation tended to have the operation sooner 512.6 versus 567.4 days (P=0.008).Our study suggests that treatment of degenerative spondylolisthesis with fusion or decompression alone results in similar rates of reoperation at 5 years. This medium term data indicate that decompression alone may be a viable treatment for some patients with degenerative spondylolisthesis.

  View details for PubMedID 28671881

• IDENTIFICATION OF PATIENTS AT HIGH RISK FOR POOR PAIN MANAGEMENT USING CLINICAL PATHWAYS WITHIN EHRS Hernandez-Boussard, T., Desai, K. OXFORD UNIV PRESS. 2017: 20

  View details for Web of Science ID 000417189000028

• Sutureless vs Sutured Gastroschisis Closure: A Prospective Randomized Controlled Trial. Journal of the American College of Surgeons Bruzoni, M., Jaramillo, J. D., Dunlap, J. L., Abrajano, C., Stack, S. W., Hintz, S. R., Hernandez-Boussard, T., Dutta, S. 2017; 224 (6): 1091-1096 e1

  Abstract

  Sutureless gastroschisis repair involves covering the abdominal wall defect with the umbilical cord or a synthetic dressing to allow closure by secondary intention. No randomized studies have described the outcomes of this technique. Our objective was to prospectively compare short-term outcomes of sutureless vs sutured closure in a randomized fashion.We recruited patients who presented with gastroschisis between 2009 and 2014 and were randomized into either sutureless or sutured treatment groups. Patients with complicated gastroschisis (stricture, perforation, and ischemia) were excluded. Predefined ventilation, feeding, and dressing change protocols were instituted. Primary outcomes were time to extubation and time to full feeds. Secondary outcomes included time to discharge and rate of complications. Data were analyzed using Fisher's exact or t-tests using a p value ≤ 0.05. Factors associated with increased time to discharge were estimated using multivariate analyses.Thirty-nine patients were enrolled, 19 to sutureless and 20 to sutured repair. There was no statistical difference in time to extubation (sutureless 1.89 vs sutured 3.15 days; p = 0.061). The sutureless group had a significant increase in mean time to full feeds (45.1 vs 27.8 days; p = 0.031) and mean time to discharge (49.3 vs 31.4 days; p = 0.016). Complication rates were similar in both groups. Multivariate regression modeling showed that an increase in time to discharge was independently associated with sutureless repair, feeding complications, and sepsis.Sutureless repair of uncomplicated gastroschisis can be performed safely, however, it is associated with a significant increase in time to full feeds and time to discharge.

  View details for DOI 10.1016/j.jamcollsurg.2017.02.014

  View details for PubMedID 28279777

• Effect of Medicare's Nonpayment Policy on Surgical Site Infections Following Orthopedic Procedures. Infection control and hospital epidemiology Kwong, J. Z., Weng, Y., Finnegan, M., Schaffer, R., Remington, A., Curtin, C., McDonald, K. M., Bhattacharya, J., Hernandez-Boussard, T. 2017: 1-6

  Abstract

  OBJECTIVE Orthopedic procedures are an important focus in efforts to reduce surgical site infections (SSIs). In 2008, the Centers for Medicare and Medicaid (CMS) stopped reimbursements for additional charges associated with serious hospital-acquired conditions, including SSI following certain orthopedic procedures. We aimed to evaluate the CMS policy's effect on rates of targeted orthopedic SSIs among the Medicare population. DESIGN We examined SSI rates following orthopedic procedures among the Medicare population before and after policy implementation compared to a similarly aged control group. Using the Nationwide Inpatient Sample database for 2000-2013, we estimated rate ratios (RRs) of orthopedic SSIs among Medicare and non-Medicare patients using a difference-in-differences approach. RESULTS Following policy implementation, SSIs significantly decreased among both the Medicare and non-Medicare populations (RR, 0.7; 95% confidence interval [CI], 0.6-0.8) and RR, 0.8l; 95% CI, 0.7-0.9), respectively. However, the estimated decrease among the Medicare population was not significantly greater than the decrease among the control population (RR, 0.9; 95% CI, 0.8-1.1). CONCLUSIONS While SSI rates decreased significantly following the implementation of the CMS nonpayment policy, this trend was not associated with policy intervention but rather larger secular trends that likely contributed to decreasing SSI rates over time. Infect Control Hosp Epidemiol 2017;1-6.

  View details for DOI 10.1017/ice.2017.86

  View details for PubMedID 28487001

• A Double-Blind Placebo Randomized Controlled Trial of Minocycline to Reduce Pain After Carpal Tunnel and Trigger Finger Release. journal of hand surgery Curtin, C. M., Kenney, D., Suarez, P., Hentz, V. R., Hernandez-Boussard, T., Mackey, S., Carroll, I. R. 2017; 42 (3): 166-174

  Abstract

  Minocycline is a microglial cell inhibitor and decreases pain behaviors in animal models. Minocycline might represent an intervention for reducing postoperative pain. This trial tested whether perioperative administration of minocycline reduced time to pain resolution (TPR) after standardized hand surgeries with known prolonged pain profiles: carpal tunnel release (CTR) and trigger finger release (TFR).This double-blinded randomized controlled trial included patients undergoing CTR or TFR under local anesthesia. Before surgery, participants recorded psychological and pain measures. Participants received oral minocycline, 200 mg, or placebo 2 hours prior to procedure, and then 100 mg of minocycline or placebo 2 times a day for 5 days. After surgery, participants were called daily assessing their pain. The primary end point of TPR was when participants had 3 consecutive days of 0 postsurgical pain. Futility analysis and Kaplan-Meier analyses were performed.A total of 131 participants were randomized and 56 placebo and 58 controls were analyzed. Median TPR for CTR was 3 weeks, with 15% having pain more than 6 weeks. Median TPR for TFR was 2 weeks with 18% having pain more than 6 weeks. The overall median TPR for the placebo group was 2 weeks (10% pain > 6 weeks) versus 2.5 weeks (17% pain > 6 weeks) for the minocycline group. Futility analysis found that the likelihood of a true underlying clinically meaningful reduction in TPR owing to minocycline was only 3.5%. Survival analysis found minocycline did not reduce TPR. However, subgroup analysis of those with elevated posttraumatic distress scores found the minocycline group had longer TPR.Oral administration of minocycline did not reduce TPR after minor hand surgery. There was evidence that minocycline might increase length of pain in those with increased posttraumatic stress disorder symptoms.Therapeutic I.

  View details for DOI 10.1016/j.jhsa.2016.12.011

  View details for PubMedID 28259273

• Temporal Relationship of Onset of Necrotizing Enterocolitis and Introduction of Enteric Feedings and Powdered Milk Fortifier. American journal of perinatology Vaks, Y. n., Birnie, K. L., Carmichael, S. L., Hernandez-Boussard, T. n., Benitz, W. E. 2017

  View details for PubMedID 29190848

• Enhanced Quality Measurement Event Detection: An Application to Physician Reporting. EGEMS (Washington, DC) Tamang, S. R., Hernandez-Boussard, T. n., Ross, E. G., Gaskin, G. n., Patel, M. I., Shah, N. H. 2017; 5 (1): 5

  Abstract

  The wide-scale adoption of electronic health records (EHR)s has increased the availability of routinely collected clinical data in electronic form that can be used to improve the reporting of quality of care. However, the bulk of information in the EHR is in unstructured form (e.g., free-text clinical notes) and not amenable to automated reporting. Traditional methods are based on structured diagnostic and billing data that provide efficient, but inaccurate or incomplete summaries of actual or relevant care processes and patient outcomes. To assess the feasibility and benefit of implementing enhanced EHR- based physician quality measurement and reporting, which includes the analysis of unstructured free- text clinical notes, we conducted a retrospective study to compare traditional and enhanced approaches for reporting ten physician quality measures from multiple National Quality Strategy domains. We found that our enhanced approach enabled the calculation of five Physician Quality and Performance System measures not measureable in billing or diagnostic codes and resulted in over a five-fold increase in event at an average precision of 88 percent (95 percent CI: 83-93 percent). Our work suggests that enhanced EHR-based quality measurement can increase event detection for establishing value-based payment arrangements and can expedite quality reporting for physician practices, which are increasingly burdened by the process of manual chart review for quality reporting.

  View details for PubMedID 29881731

• Mining Electronic Health Records to Extract Patient-Centered Outcomes Following Prostate Cancer Treatment. AMIA ... Annual Symposium proceedings. AMIA Symposium Hernandez-Boussard, T., Kourdis, P. D., Seto, T., Ferrari, M., Blayney, D. W., Rubin, D., Brooks, J. D. 2017; 2017: 876–82

  Abstract

  The clinical, granular data in electronic health record (EHR) systems provide opportunities to improve patient care using informatics retrieval methods. However, it is well known that many methodological obstacles exist in accessing data within EHRs. In particular, clinical notes routinely stored in EHR are composed from narrative, highly unstructured and heterogeneous biomedical text. This inherent complexity hinders the ability to perform automated large-scale medical knowledge extraction tasks without the use of computational linguistics methods. The aim of this work was to develop and validate a Natural Language Processing (NLP) pipeline to detect important patient-centered outcomes (PCOs) as interpreted and documented by clinicians in their dictated notes for male patients receiving treatment for localized prostate cancer at an academic medical center.

  View details for PubMedID 29854154

• Opioid Abuse And Poisoning: Trends In Inpatient And Emergency Department Discharges. Health affairs (Project Hope) Tedesco, D. n., Asch, S. M., Curtin, C. n., Hah, J. n., McDonald, K. M., Fantini, M. P., Hernandez-Boussard, T. n. 2017; 36 (10): 1748–53

  Abstract

  Addressing the opioid epidemic is a national priority. We analyzed national trends in inpatient and emergency department (ED) discharges for opioid abuse, dependence, and poisoning using Healthcare Cost and Utilization Project data. Inpatient and ED discharge rates increased overall across the study period, but a decline was observed for prescription opioid-related discharges beginning in 2010, while a sharp increase in heroin-related discharges began in 2008.

  View details for PubMedID 28971919

• Drug-Free Interventions to Reduce Pain or Opioid Consumption After Total Knee Arthroplasty: A Systematic Review and Meta-analysis. JAMA surgery Tedesco, D. n., Gori, D. n., Desai, K. R., Asch, S. n., Carroll, I. R., Curtin, C. n., McDonald, K. M., Fantini, M. P., Hernandez-Boussard, T. n. 2017: e172872

  Abstract

  There is increased interest in nonpharmacological treatments to reduce pain after total knee arthroplasty. Yet, little consensus supports the effectiveness of these interventions.To systematically review and meta-analyze evidence of nonpharmacological interventions for postoperative pain management after total knee arthroplasty.Database searches of MEDLINE (PubMed), EMBASE (OVID), Cochrane Central Register of Controlled Trials (CENTRAL), Cochrane Database of Systematic Reviews, Web of Science (ISI database), Physiotherapy Evidence (PEDRO) database, and ClinicalTrials.gov for the period between January 1946 and April 2016.Randomized clinical trials comparing nonpharmacological interventions with other interventions in combination with standard care were included.Two reviewers independently extracted the data from selected articles using a standardized form and assessed the risk of bias. A random-effects model was used for the analyses.Postoperative pain and consumption of opioids and analgesics.Of 5509 studies, 39 randomized clinical trials were included in the meta-analysis (2391 patients). The most commonly performed interventions included continuous passive motion, preoperative exercise, cryotherapy, electrotherapy, and acupuncture. Moderate-certainty evidence showed that electrotherapy reduced the use of opioids (mean difference, -3.50; 95% CI, -5.90 to -1.10 morphine equivalents in milligrams per kilogram per 48 hours; P = .004; I2 = 17%) and that acupuncture delayed opioid use (mean difference, 46.17; 95% CI, 20.84 to 71.50 minutes to the first patient-controlled analgesia; P < .001; I2 = 19%). There was low-certainty evidence that acupuncture improved pain (mean difference, -1.14; 95% CI, -1.90 to -0.38 on a visual analog scale at 2 days; P = .003; I2 = 0%). Very low-certainty evidence showed that cryotherapy was associated with a reduction in opioid consumption (mean difference, -0.13; 95% CI, -0.26 to -0.01 morphine equivalents in milligrams per kilogram per 48 hours; P = .03; I2 = 86%) and in pain improvement (mean difference, -0.51; 95% CI, -1.00 to -0.02 on the visual analog scale; P < .05; I2 = 62%). Low-certainty or very low-certainty evidence showed that continuous passive motion and preoperative exercise had no pain improvement and reduction in opioid consumption: for continuous passive motion, the mean differences were -0.05 (95% CI, -0.35 to 0.25) on the visual analog scale (P = .74; I2 = 52%) and 6.58 (95% CI, -6.33 to 19.49) opioid consumption at 1 and 2 weeks (P = .32, I2 = 87%), and for preoperative exercise, the mean difference was -0.14 (95% CI, -1.11 to 0.84) on the Western Ontario and McMaster Universities Arthritis Index Scale (P = .78, I2 = 65%).In this meta-analysis, electrotherapy and acupuncture after total knee arthroplasty were associated with reduced and delayed opioid consumption.

  View details for PubMedID 28813550

• Emergency Department Visits Following Elective Total Hip and Knee Replacement Surgery: Identifying Gaps in Continuity of Care. The Journal of bone and joint surgery. American volume Finnegan, M. A., Shaffer, R. n., Remington, A. n., Kwong, J. n., Curtin, C. n., Hernandez-Boussard, T. n. 2017; 99 (12): 1005–12

  Abstract

  Major joint replacement surgical procedures are common, elective procedures with a care episode that includes both inpatient readmissions and postoperative emergency department (ED) visits. Inpatient readmissions are well studied; however, to our knowledge, little is known about ED visits following these procedures. We sought to characterize 30-day ED visits following a major joint replacement surgical procedure.We used administrative records from California, Florida, and New York, from 2010 through 2012, to identify adults undergoing total knee and hip arthroplasty. Factors associated with increased risk of an ED visit were estimated using hierarchical regression models controlling for patient variables with a fixed hospital effect. The main outcome was an ED visit within 30 days of discharge.Among the 152,783 patients who underwent major joint replacement, 5,229 (3.42%) returned to the inpatient setting and 8,883 (5.81%) presented to the ED for care within 30 days. Among ED visits, 17.94% had a primary diagnosis of pain and 25.75% had both a primary and/or a secondary diagnosis of pain. Patients presenting to the ED for subsequent care had more comorbidities and were more frequently non-white with public insurance relative to those not returning to the ED (p < 0.001). There was a significantly increased risk (p < 0.05) of isolated ED visits with regard to type of insurance when patients with Medicaid (odds ratio [OR], 2.28 [95% confidence interval (CI), 2.04 to 2.55]) and those with Medicare (OR, 1.38 [95% CI, 1.29 to 1.47]) were compared with patients with private insurance and with regard to race when black patients (OR, 1.38 [95% CI, 1.25 to 1.53]) and Hispanic patients (OR, 1.12 [95% CI, 1.03 to 1.22]) were compared with white patients. These increases in risk were stronger for isolated ED visits for patients with a pain diagnosis.ED visits following an elective major joint replacement surgical procedure were numerous and most commonly for pain-related diagnoses. Medicaid patients had almost double the risk of an ED or pain-related ED visit following a surgical procedure. The future of U.S. health-care insurance coverage expansions are uncertain; however, there are ongoing attempts to improve quality across the continuum of care. It is therefore essential to ensure that all patients, particularly vulnerable populations, receive appropriate postoperative care, including pain management.Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

  View details for PubMedID 28632589

• The Fifth Vital Sign: Postoperative Pain Predicts 30-day Readmissions and Subsequent Emergency Department Visits. Annals of surgery Hernandez-Boussard, T. n., Graham, L. A., Desai, K. n., Wahl, T. S., Aucoin, E. n., Richman, J. S., Morris, M. S., Itani, K. M., Telford, G. L., Hawn, M. T. 2017

  Abstract

  We hypothesized that inpatient postoperative pain trajectories are associated with 30-day inpatient readmission and emergency department (ED) visits.Surgical readmissions have few known modifiable predictors. Pain experienced by patients may reflect surgical complications and/or inadequate or difficult symptom management.National Veterans Affairs Surgical Quality Improvement data on inpatient general, vascular, and orthopedic surgery from 2008 to 2014 were merged with laboratory, vital sign, health care utilization, and postoperative complications data. Six distinct postoperative inpatient patient-reported pain trajectories were identified: (1) persistently low, (2) mild, (3) moderate or (4) high trajectories, and (5) mild-to-low or (6) moderate-to-low trajectories based on postoperative pain scores. Regression models estimated the association between pain trajectories and postdischarge utilization while controlling for important patient and clinical variables.Our sample included 211,231 surgeries-45.4% orthopedics, 37.0% general, and 17.6% vascular. Overall, the 30-day unplanned readmission rate was 10.8%, and 30-day ED utilization rate was 14.2%. Patients in the high pain trajectories had the highest rates of postdischarge readmissions and ED visits (14.4% and 16.3%, respectively, P < 0.001). In multivariable models, compared with the persistently low pain trajectory, there was a dose-dependent increase in postdischarge ED visits and readmission for pain-related diagnoses, but not postdischarge complications (χ trend P < 0.001).Postoperative pain trajectories identify populations at risk for 30-day readmissions and ED visits, and do not seem to be mediated by postdischarge complications. Addressing pain control expectations before discharge may help reduce surgical readmissions in high pain categories.

  View details for PubMedID 28657940

• The Epidemiology of Retinopathy of Prematurity in the United States. Ophthalmic surgery, lasers & imaging retina Ludwig, C. A., Chen, T. A., Hernandez-Boussard, T. n., Moshfeghi, A. A., Moshfeghi, D. M. 2017; 48 (7): 553–62

  Abstract

  Retinopathy of prematurity (ROP) is a leading cause of blindness in premature and low birth weight infants. Here, the authors examine the incidence of ROP in the United States and evaluate risk factors associated with ROP development.The National Healthcare Cost and Utilization Project Kids' Inpatient Database was queried for all newborns with and without ROP. Adjusted odds ratios were constructed for predictors of ROP using multivariate logistic regression modeling.The incidence of ROP increased from 14.70% in 2000 to 19.88% in 2012. Multivariate regression analysis indicated that female gender, birth weight, and gestational age predicted ROP. The frequency of ROP was 2.40% in newborns weighing more than 2,500 grams (g) and 30.22% in newborns with a birth weight between 750 g and 999 g.The authors' report examines a nationwide cohort of ROP infants and reveals an increase in the incidence of ROP from 2000 to 2012. This trend is inversely related to a simultaneous decline in newborn mortality. [ Ophthalmic Surg Lasers Imaging Retina . 2017;48:553-562.].

  View details for DOI 10.3928/23258160-20170630-06

  View details for PubMedID 28728176

• Characterization of Young Adult Emergency Department Users: Evidence to Guide Policy JOURNAL OF ADOLESCENT HEALTH Burns, C., Wang, N. E., Goldstein, B. A., Hernandez-Boussard, T. 2016; 59 (6): 654-661

  Abstract

  The purpose of this study was to characterize young adult patients aged 19-25 years who are emergency department (ED) frequent users and study factors associated with frequent ED use.ED visits among 19- to 25-year olds were identified from administrative records in California, Florida, Iowa, Massachusetts, and New York, 2010. Patients were analyzed for 12 months to study the frequency of their ED utilization. ED visits were categorized according to primary diagnosis. Patients were stratified by frequency of ED use: one visit (single users), two to four visits (infrequent users), and five or more visits (frequent users) in a 1-year period.We identified 1,711,774 young adult patients who made 3,650,966 ED visits. Sixty-six percent of patients were single users, 29% were infrequent users, and 4.6% were frequent users. Frequent users accounted for a disproportionate 28.8% of visits within the population studied. Frequent users had the largest proportion of visits for complications of pregnancy (13.6%) compared to single users (6.1%) and Medicaid (42.6%) compared to private insurance (17.3%). There was an increased risk of frequent ED use associated with females (odds ratio [OR]: 1.77), Medicaid (OR: 3.21), and Medicare insurance (OR: 4.22) compared to private insurance, and diseases of the blood (OR: 3.36) and mental illness (OR: 1.99) compared to injury and poisoning.Frequent users comprise a significant portion of the young adult ED population and present with a large proportion of visits for complications of pregnancy. Policies targeting this population might focus on improved access to primary and urgent care, acute obstetric care, and better coordination of care.

  View details for DOI 10.1016/j.jadohealth.2016.07.011

  View details for Web of Science ID 000389534900008

  View details for PubMedID 27613220

• Cataract Surgery Complications and Revisit Rates Among Three States AMERICAN JOURNAL OF OPHTHALMOLOGY Pershing, S., Morrison, D. E., Hernandez-Boussard, T. 2016; 171: 130-138

  Abstract

  To characterize population-based 30-day procedure-related readmissions (revisits) following cataract surgery.Ambulatory cataract surgery performed in California, Florida, or New York DESIGN: Retrospective cohort study.This study used all-capture state administrative datasets. Cataract procedures from CA, FL, and NY state ambulatory surgery settings were identified using ICD-9-CM and CPT codes. Thirty-day readmissions (revisits) were identified in inpatient, ambulatory, and emergency department settings across each state RESULTS: Across the three states, the all-cause 30-day readmission rate was 6.0% and the procedure-related readmission (revisit) rate was 1.0%. Procedure-related revisits were highest for patients aged 20-29 (2.9%) and 30-39 (2.3%) and lowest for patients aged 70-79 (0.9%). Multivariate associations between clinical characteristics and 30-day procedure-related revisits included age 20-29 (Odds Ratio [OR]: 3.13; 95% Confidence Intervals [CI]: 2.33-4.20) and age 30-39 (OR: 2.35; CI: 1.91-2.89) compared to age 70-79, male gender (OR: 1.29; CI: 1.24-1.34), races black (OR: 1.37; CI: 1.27-1.48) and Hispanic (OR: 1.16; CI: 1.08-1.24) compared to white, and Medicaid insurance (OR: 1.18, CI: 1.07-1.30) compared to Medicare. Diabetes was also associated with increased 30-day procedure-related revisits (OR: 1.093, CI: 1.024-1.168).Cataract surgery is a common and, in aggregate, expensive procedure. Complication-related revisits follow a similar trend as surgical complications in large-scale population data, and may be useful as a preliminary, screening, outcome measure. Our results highlight the importance of age as a risk factor for cataract surgery readmissions, and suggest a relationship between black or Hispanic race, Medicaid insurance, and diabetes associated with higher risk for cataract surgery complications.

  View details for DOI 10.1016/j.ajo.2016.08.036

  View details for Web of Science ID 000388545800018

  View details for PubMedID 27615607

• Lymph Node Ratio Analysis After Neoadjuvant Chemotherapy is Prognostic in Hormone Receptor-Positive and Triple-Negative Breast Cancer. Annals of surgical oncology Tsai, J., Bertoni, D., Hernandez-Boussard, T., Telli, M. L., Wapnir, I. L. 2016; 23 (10): 3310-3316

  Abstract

  Lymph node ratios (LNR), the proportion of positive lymph nodes over the number excised, both defined as ranges and single ratio values are prognostic of outcome. Little is known of the prognostic value of LNR after neoadjuvant chemotherapy (NAC) according to molecular subtype.From 2003 to 2014, patients who underwent definitive surgery after NAC were identified. LNR was calculated for node-positive patients who received axillary dissection or had at least 6 nodes removed. DFS was calculated using the Kaplan-Meier log rank test for yp N0-3 status, LNR categories (LNRC) ≤0.20 (low), 0.21-0.65 (intermediate), >0.65 (high), and single LNR values.Of 428 NAC recipients, 263 were node negative and 165 (38.6 %) node positive: ypN1 = 97 (58.8 %), ypN2 = 43 (26.1 %), and ypN3 = 25 (15.2 %). Among node-positive cancers, the median number of LN removed was 14 (range, 6-51) and the median LNR was 0.22 (range, 0.03-1.0). Nodal stage was inversely associated with 5-year DFS: 91.5 % (ypN0), 74.5 % (ypN1), 49.8 % (ypN2), and 50.7 % (ypN3) (p < 0.001). LNRC was similarly inversely associated with DFS: 69.1 % (low), 71.4 % (intermediate), 49.3 % (high) (p < 0.001). Significant associations between LNRC and DFS were demonstrated in hormone receptor (HR)-positive and triple negative breast cancer (TNBC) subtypes, p = 0.02 and p = 0.003. A single-value LNR ≤ 0.15 in node-positive, HR-positive (94.1 vs 67.7 %; p = 0.04) and TNBC (94.1 vs 47.8 %; p = 0.001) groups was also significant.Residual nodal disease after NAC, analyzed by LNRC or LNR = 0.15 cutoff value, is prognostic and can discriminate between favorable and unfavorable outcomes for HR-positive and TNBC cancers.

  View details for DOI 10.1245/s10434-016-5319-8

  View details for PubMedID 27401442

• Risk-adjustment models for heart failure patients' 30-day mortality and readmission rates: the incremental value of clinical data abstracted from medical charts beyond hospital discharge record BMC HEALTH SERVICES RESEARCH Lenzi, J., Avaldi, V. M., Hernandez-Boussard, T., Descovich, C., Castaldini, I., Urbinati, S., Di Pasquale, G., Rucci, P., Fantini, M. P. 2016; 16

  Abstract

  Hospital discharge records (HDRs) are routinely used to assess outcomes of care and to compare hospital performance for heart failure. The advantages of using clinical data from medical charts to improve risk-adjustment models remain controversial. The aim of the present study was to evaluate the additional contribution of clinical variables to HDR-based 30-day mortality and readmission models in patients with heart failure.This retrospective observational study included all patients residing in the Local Healthcare Authority of Bologna (about 1 million inhabitants) who were discharged in 2012 from one of three hospitals in the area with a diagnosis of heart failure. For each study outcome, we compared the discrimination of the two risk-adjustment models (i.e., HDR-only model and HDR-clinical model) through the area under the ROC curve (AUC).A total of 1145 and 1025 patients were included in the mortality and readmission analyses, respectively. Adding clinical data significantly improved the discrimination of the mortality model (AUC = 0.84 vs. 0.73, p < 0.001), but not the discrimination of the readmission model (AUC = 0.65 vs. 0.63, p = 0.08).We identified clinical variables that significantly improved the discrimination of the HDR-only model for 30-day mortality following heart failure. By contrast, clinical variables made little contribution to the discrimination of the HDR-only model for 30-day readmission.

  View details for DOI 10.1186/s12913-016-1731-9

  View details for Web of Science ID 000382448300001

  View details for PubMedID 27600617

  View details for PubMedCentralID PMC5012069

• Evaluating patient safety indicators in orthopedic surgery between Italy and the USA INTERNATIONAL JOURNAL FOR QUALITY IN HEALTH CARE Tedesco, D., Hernandez-Boussard, T., Carretta, E., Rucci, P., Rolli, M., Di Denia, P., McDonald, K., Fantini, M. P. 2016; 28 (4): 486-491

  Abstract

  To compare patient safety in major orthopedic procedures between an orthopedic hospital in Italy, and 26 US hospitals of similar size.Retrospective analysis of administrative data from hospital discharge records in Italy and Florida, USA, 2011-13. Patient Safety Indicators (PSIs) developed by the Agency for Healthcare Quality and Research were used to identify inpatient adverse events (AEs). We examined the factors associated with the development of each different PSI, taking into account known confounders, using logistic regression.One Italian orthopedic hospital and 26 hospitals in Florida with ≥ 1000 major orthopedic procedures per year.Patients ≥ 18 years who underwent 1 of the 17 major orthopedic procedures, and with a length of stay (LOS) > 1 day.Patient Safety management between Italy and the USA.Patient Safety Indicators.A total of 14 393 patients in Italy (mean age = 59.8 years) and 131 371 in the USA (mean age = 65.4 years) were included. US patients had lower adjusted odds of developing a PSI compared to Italy for pressure ulcers (odds ratio [OR]: 0.21; 95% confidence interval [CI]: 0.10-0.45), hemorrhage or hematoma (OR: 0.42; CI 0.23-0.78), physiologic and metabolic derangement (OR: 0.08; CI 0.02-0.37). Italian patients had lower odds of pulmonary embolism/deep vein thrombosis (OR: 3.17; CI 2.16-4.67) compared to US patients.Important differences in patient safety events were identified across countries using US developed PSIs. Though caution about potential coding differences is wise when comparing PSIs internationally, other differences may explain AEs, and offer opportunities for cross-country learning about safe practices.

  View details for DOI 10.1093/intqhc/mzw053

  View details for Web of Science ID 000384660300008

  View details for PubMedID 27272404

• Protecting Nipple Perfusion by Devascularization and Surgical Delay in Patients at Risk for Ischemic Complications During Nipple-Sparing Mastectomies ANNALS OF SURGICAL ONCOLOGY Bertoni, D. M., Dung Nguyen, D., Rochlin, D., Hernandez-Boussard, T., Meyer, S., Choy, N., Gurtner, G. C., Wapnir, I. L. 2016; 23 (8): 2665-2672

  Abstract

  Indications for nipple-sparing mastectomy (NSM) are expanding; however, high-risk patients have more ischemic complications. Surgical devascularization of the nipple-areolar complex (NAC) prior to NSM can reduce complications. This study reports perfusion patterns and complications in high-risk patients undergoing 2-stage NSM.Surgical devascularization of the NAC was performed 3-6 weeks prior to NSM in 28 women. Risk factors included ptosis, obesity, smoking, prior breast surgery, and radiation. Using indocyanine green (ICG)-based fluorescence and an infrared camera, blood inflow was visualized intraoperatively. NAC perfusion patterns were classified as: V1, underlying breast; V2, surrounding skin; V3 = V1 + V2, or V4, capillary fill following devascularization. Ischemic complications were analyzed.Baseline perfusion for 54 breasts was 35 % V1, 32 % V2, and 33 % V3. Increasing ptosis was associated with V1 pattern: 86 % for grade 3, 31 % for grade 2, and 18 % for grade 1. Postdevascularization epidermolysis was observed in 63 % of V1 baseline, 41 % of V2, and 22 % of V3 (P = .042) and after NSM in 26 % for V1, 7 % for V2, and 6 % for V3 (P = .131). Ptosis was significantly associated with epidermolysis postdevascularization (P = .002) and NSM (P = .002). Smoking and BMI ≥30 were related to increased ischemic complications. Two or more risk factors were associated with postdevascularization ischemic changes (P = .026), but were not significant after NSM. Nipple loss was not observed, but 2 patients underwent partial areolar resection.Adaptive circulatory changes after devascularization allow tissues to tolerate the additional ischemic challenge of mastectomy. Our findings support extending 2-staged operations to high-risk women previously considered unsuitable for NSM.

  View details for DOI 10.1245/s10434-016-5201-8

  View details for PubMedID 27038458

• Analyzing treatment aggressiveness and identifying high-risk patients in diabetic foot ulcer return to care. Wound repair and regeneration Remington, A. C., Hernandez-Boussard, T., Warstadt, N. M., Finnegan, M. A., Shaffer, R., Kwong, J. Z., Curtin, C. 2016; 24 (4): 731-736

  Abstract

  Rates of diabetes and its associated comorbidities have been increasing in the United States, with diabetic foot ulcer treatment representing a large cost to the patient and healthcare system. These ulcers often result in multiple hospital admissions. This study examined readmissions following inpatient care for a diabetic foot ulcer and identified modifiable factors associated with all-cause 30-day readmissions to the inpatient or emergency department (ED) setting. We hypothesized that patients undergoing aggressive treatment would have lower 30-day readmission rates. We identified patient discharge records containing International Classification of Disease ninth revision codes for both diabetes mellitus and distal foot ulcer in the State Inpatient and Emergency Department databases from the Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project in Florida and New York, 2011-2012. All-cause 30-day return to care visits (ED or inpatient) were analyzed. Patient demographics and treatment characteristics were evaluated using univariate and multivariable regression models. The cohort included 25,911 discharges, having a mean age of 63 and an average of 3.8 comorbidities. The overall rate of return to care was 30%, and 21% of subjects underwent a toe or midfoot amputation during their index stay. The most common diagnosis codes upon readmission were diabetes mellitus (19%) and infection (13%). Patients with a toe or midfoot amputation procedure were less likely to be readmitted within 30 days (odds ratio: 0.78; 95% confidence interval: 0.73, 0.84). Presence of comorbidities, black and Hispanic ethnicities, and Medicare and Medicaid payer status were also associated with higher odds of readmission following initial hospitalization (p < 0.05). The study suggests that there are many factors that affect readmission rates for diabetic foot ulcer patients. Understanding patients at high-risk for readmission can improve counseling and treatment strategies for this fragile patient population.

  View details for DOI 10.1111/wrr.12439

  View details for PubMedID 27144893

• Robot-assisted versus open radical prostatectomy utilization in hospitals offering robotics CANADIAN JOURNAL OF UROLOGY Yanamadala, S., Chung, B. I., Hernandez-Boussard, T. M. 2016; 23 (3): 8280-8285

  Abstract

  Prostate cancer is an extremely prevalent cause of morbidity and mortality among American men. Several different treatments exist, but differences in utilization between these treatments are not well understood.We performed an observational study using administrative datasets linked to hospital survey data, which included non-metastatic prostate cancer patients receiving robot-assisted radical prostatectomy (RARP) or open radical prostatectomy (ORP) in California, Florida, or New York from 2009-2011. We developed two hierarchical regression models with fixed effect accounting for hospital clustering and physician clustering to determine factors associated with utilization of RARP versus ORP at hospitals offering robotic surgery.A total of 36,694 patients were identified, with 77.13% receiving RARP and 22.87% receiving ORP. African American patients had lower RARP rates than White patients (OR = 0.80, p < 0.001). Patients using Medicare (OR = 0.91, p = 0.028), Medicaid (OR = 0.68, p < 0.001), or self-pay (OR = 0.72, p = 0.046) had lower RARP rates than patients using private insurance. Patients in Florida had lower RARP rates than patients in California (OR = 0.48, p = 0.010). Patients treated at teaching hospitals had lower RARP rates than patients treated at non-teaching hospitals (OR = 0.50, p = 0.006). The average cost of RARP was $13,614.83, and the average cost of ORP was $12,167.44 (p < 0.001).This population based study suggests that both patient and hospital characteristics are associated with utilization of RARP versus ORP in hospitals where robotic surgery is offered.

  View details for Web of Science ID 000379635800006

• Robot-assisted versus open radical prostatectomy utilization in hospitals offering robotics. Canadian journal of urology Yanamadala, S., Chung, B. I., Hernandez-Boussard, T. M. 2016; 23 (3): 8279-8284

  Abstract

  Prostate cancer is an extremely prevalent cause of morbidity and mortality among American men. Several different treatments exist, but differences in utilization between these treatments are not well understood.We performed an observational study using administrative datasets linked to hospital survey data, which included non-metastatic prostate cancer patients receiving robot-assisted radical prostatectomy (RARP) or open radical prostatectomy (ORP) in California, Florida, or New York from 2009-2011. We developed two hierarchical regression models with fixed effect accounting for hospital clustering and physician clustering to determine factors associated with utilization of RARP versus ORP at hospitals offering robotic surgery.A total of 36,694 patients were identified, with 77.13% receiving RARP and 22.87% receiving ORP. African American patients had lower RARP rates than White patients (OR = 0.80, p < 0.001). Patients using Medicare (OR = 0.91, p = 0.028), Medicaid (OR = 0.68, p < 0.001), or self-pay (OR = 0.72, p = 0.046) had lower RARP rates than patients using private insurance. Patients in Florida had lower RARP rates than patients in California (OR = 0.48, p = 0.010). Patients treated at teaching hospitals had lower RARP rates than patients treated at non-teaching hospitals (OR = 0.50, p = 0.006). The average cost of RARP was $13,614.83, and the average cost of ORP was $12,167.44 (p < 0.001).This population based study suggests that both patient and hospital characteristics are associated with utilization of RARP versus ORP in hospitals where robotic surgery is offered.

  View details for PubMedID 27347621

• Relationship of Affordable Care Act Implementation to Emergency Department Utilization Among Young Adults ANNALS OF EMERGENCY MEDICINE Hernandez-Boussard, T., Morrison, D., Goldstein, B. A., Hsia, R. Y. 2016; 67 (6): 714-720

  Abstract

  The 2010 provision of the Patient Protection and Affordable Care Act (ACA) extended eligibility for health insurance for young adults aged 19 to 25 years. It is unclear, however, how expanded coverage changes health care behavior and promotes efficient use of emergency department (ED) services. Our objective was to use population-level emergency department data to characterize any changes in diagnoses seen in ED among young adults since the implementation of the ACA dependent coverage expansion.We performed a difference-in-differences analysis of 2009 to 2011 ED visits from California, Florida, and New York, using all-capture administrative data to determine how the use of ED services changed for clinical categories after the ACA provision among young adults aged 19 to 25 years compared with slightly older adults unaffected by the provision, aged 26 to 31 years.We analyzed a total of 10,158,254 ED visits made by 4,734,409 patients. After the implementation of the 2010 ACA provision, young adults had a relative decrease of 0.5% ED visits per 1,000 people compared with the older group. For the majority of diagnostic categories, young adults' rates and risk of visit did not change relative to that of slightly older adults after the implementation of the ACA. However, although young adults' ED visits significantly increased for mental illnesses (2.6%) and diseases of the circulatory system (eg, nonspecific chest pain) (4.8%), visits decreased for pregnancy-related diagnoses and diseases of the skin (eg, cellulitis, abscess) compared with that of the older group (3.7% and 3.1%, respectively).Our results indicate that increased coverage has kept young adults out of the ED for specific conditions that can be cared for through access to other channels. As EDs face capacity challenges, these results are encouraging and offer insight into what could be expected under further insurance expansions from health care reform.

  View details for DOI 10.1016/j.annemergmed.2015.11.034

  View details for Web of Science ID 000377424400007

  View details for PubMedID 26778281

• Risks of adverse events in colorectal patients: population-based study JOURNAL OF SURGICAL RESEARCH Hernandez-Boussard, T. M., McDonald, K. M., Morrison, D. E., Rhoads, K. F. 2016; 202 (2): 328-334

  Abstract

  Postoperative (PO) outcomes are rapidly being integrated into value-based purchasing programs and associated penalties are slated for inclusion in the near future. Colorectal surgery procedures are extremely common and account for a high proportion of morbidity among general surgery. We sought to assess adverse events in colorectal surgical patients.We performed a retrospective study using the Nationwide Inpatient Sample database, 2008-2012. Patients were identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes and classified based on procedure indication: colon cancer, benign polyps, diverticulitis, inflammatory bowel disease, and ischemic colitis. The outcome of interest was inpatient adverse event identified by Agency for Healthcare Research and Quality's patient safety indicators (PSIs).We identified 1,100,184 colorectal patients who underwent major surgery; 2.7% developed a PSI during their hospital stay. Compared to all colorectal patients, those with ischemic colitis had significantly higher risk-adjusted rates per 1000 case for pressure ulcer (50.20), failure to rescue (211.30), central line bloodstream infection (2.33) and PO DE/deep vein thrombosis (16.02), and sepsis (46.99), whereas benign polyps were associated with significantly lower risk-adjusted rates per 1000 cases for pressure ulcer (11.48), failure to rescue (84.79), central line bloodstream infection (0.97) and PO pulmonary embolism/deep vein thrombosis (4.81), and sepsis (11.23). Compared to both patient demographic and clinical characteristics, the procedure indication was the strongest predictor of any PSI relevant to colorectal surgery; patients with ischemic colitis had higher odds of experiencing a PSI (odds ratio, 1.84; 95% confidence interval, 1.71-1.99) compared with cancer patients.Among colorectal surgery patients, inpatient events were not uncommon. We found important differential rates of adverse events by diagnostic category, with the highest odds ratio occurring in patients undergoing surgery for ischemic colitis. Our work elaborates the need for rigorous risk adjustment, quality improvement strategies for high-risk populations, and attention to detail in calculating financial incentives in emerging value-based purchasing programs.

  View details for DOI 10.1016/j.jss.2016.01.013

  View details for Web of Science ID 000376334700013

  View details for PubMedID 27229107

• Electronic Health Records and Quality of Care: An Observational Study Modeling Impact on Mortality, Readmissions, and Complications MEDICINE Yanamadala, S., Morrison, D., Curtin, C., McDonald, K., Hernandez-Boussard, T. 2016; 95 (19)

  Abstract

  Electronic health records (EHRs) were implemented to improve quality of care and patient outcomes. This study assessed the relationship between EHR-adoption and patient outcomes.We performed an observational study using State Inpatient Databases linked to American Hospital Association survey, 2011. Surgical and medical patients from 6 large, diverse states were included. We performed univariate analyses and developed hierarchical regression models relating level of EHR utilization and mortality, readmission rates, and complications. We evaluated the effect of EHR adoption on outcomes in a difference-in-differences analysis, 2008 to 2011.Medical and surgical patients sought care at hospitals reporting no EHR (3.5%), partial EHR (55.2%), and full EHR systems (41.3%). In univariate analyses, patients at hospitals with full EHR had the lowest rates of inpatient mortality, readmissions, and Patient Safety Indicators followed by patients at hospitals with partial EHR and then patients at hospitals with no EHR (P < 0.05). However, these associations were not robust when accounting for other patient and hospital factors, and adoption of an EHR system was not associated with improved patient outcomes (P > 0.05).These results indicate that patients receiving medical and surgical care at hospitals with no EHR system have similar outcomes compared to patients seeking care at hospitals with a full EHR system, after controlling for important confounders.To date, we have not yet seen the promised benefits of EHR systems on patient outcomes in the inpatient setting. EHRs may play a smaller role than expected in patient outcomes and overall quality of care.

  View details for DOI 10.1097/MD.0000000000003332

  View details for Web of Science ID 000376927000010

  View details for PubMedID 27175631

  View details for PubMedCentralID PMC4902473

• The Ontology for Biomedical Investigations PLOS ONE Bandrowski, A., Brinkman, R., Brochhausen, M., Brush, M. H., Bug, B., Chibucos, M. C., Clancy, K., Courtot, M., Derom, D., Dumontier, M., Fan, L., Fostel, J., Fragoso, G., Gibson, F., Gonzalez-Beltran, A., Haendel, M. A., He, Y., Heiskanen, M., Hernandez-Boussard, T., Jensen, M., Lin, Y., Lister, A. L., Lord, P., Malone, J., Manduchi, E., McGee, M., Morrison, N., Overton, J. A., Parkinson, H., Peters, B., Rocca-Serra, P., Ruttenberg, A., Sansone, S., Scheuermann, R. H., Schober, D., Smith, B., Soldatova, L. N., Stoeckert, C. J., Taylor, C. F., Torniai, C., Turner, J. A., Vita, R., Whetzel, P. L., Zheng, J. 2016; 11 (4)

  Abstract

  The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

  View details for DOI 10.1371/journal.pone.0154556

  View details for PubMedID 27128319

• Performance Measures in Neurosurgical Patient Care Differing Applications of Patient Safety Indicators MEDICAL CARE Moghavem, N., McDonald, K., Ratliff, J. K., Hernandez-Boussard, T. 2016; 54 (4): 359-364

  Abstract

  Patient Safety Indicators (PSIs) are administratively coded identifiers of potentially preventable adverse events. These indicators are used for multiple purposes, including benchmarking and quality improvement efforts. Baseline PSI evaluation in high-risk surgeries is fundamental to both purposes.Determine PSI rates and their impact on other outcomes in patients undergoing cranial neurosurgery compared with other surgeries.The Agency for Healthcare Research and Quality (AHRQ) PSI software was used to flag adverse events and determine risk-adjusted rates (RAR). Regression models were built to assess the association between PSIs and important patient outcomes.We identified cranial neurosurgeries based on International Classification of Diseases, Ninth Revision, Clinical Modification codes in California, Florida, New York, Arkansas, and Mississippi State Inpatient Databases, AHRQ, 2010-2011.PSI development, 30-day all-cause readmission, length of stay, hospital costs, and inpatient mortality.A total of 48,424 neurosurgical patients were identified. Procedure indication was strongly associated with PSI development. The neurosurgical population had significantly higher RAR of most PSIs evaluated compared with other surgical patients. Development of a PSI was strongly associated with increased length of stay and hospital cost and, in certain PSIs, increased inpatient mortality and 30-day readmission.In this population-based study, certain accountability measures proposed for use as value-based payment modifiers show higher RAR in neurosurgery patients compared with other surgical patients and were subsequently associated with poor outcomes. Our results indicate that for quality improvement efforts, the current AHRQ risk-adjustment models should be viewed in clinically meaningful stratified subgroups: for profiling and pay-for-performance applications, additional factors should be included in the risk-adjustment models. Further evaluation of PSIs in additional high-risk surgeries is needed to better inform the use of these metrics.

  View details for DOI 10.1097/MLR.0000000000000490

  View details for Web of Science ID 000372935200004

• Performance Measures in Neurosurgical Patient Care: Differing Applications of Patient Safety Indicators. Medical care Moghavem, N., McDonald, K., Ratliff, J. K., Hernandez-Boussard, T. 2016; 54 (4): 359-64

  Abstract

  Patient Safety Indicators (PSIs) are administratively coded identifiers of potentially preventable adverse events. These indicators are used for multiple purposes, including benchmarking and quality improvement efforts. Baseline PSI evaluation in high-risk surgeries is fundamental to both purposes.Determine PSI rates and their impact on other outcomes in patients undergoing cranial neurosurgery compared with other surgeries.The Agency for Healthcare Research and Quality (AHRQ) PSI software was used to flag adverse events and determine risk-adjusted rates (RAR). Regression models were built to assess the association between PSIs and important patient outcomes.We identified cranial neurosurgeries based on International Classification of Diseases, Ninth Revision, Clinical Modification codes in California, Florida, New York, Arkansas, and Mississippi State Inpatient Databases, AHRQ, 2010-2011.PSI development, 30-day all-cause readmission, length of stay, hospital costs, and inpatient mortality.A total of 48,424 neurosurgical patients were identified. Procedure indication was strongly associated with PSI development. The neurosurgical population had significantly higher RAR of most PSIs evaluated compared with other surgical patients. Development of a PSI was strongly associated with increased length of stay and hospital cost and, in certain PSIs, increased inpatient mortality and 30-day readmission.In this population-based study, certain accountability measures proposed for use as value-based payment modifiers show higher RAR in neurosurgery patients compared with other surgical patients and were subsequently associated with poor outcomes. Our results indicate that for quality improvement efforts, the current AHRQ risk-adjustment models should be viewed in clinically meaningful stratified subgroups: for profiling and pay-for-performance applications, additional factors should be included in the risk-adjustment models. Further evaluation of PSIs in additional high-risk surgeries is needed to better inform the use of these metrics.

  View details for DOI 10.1097/MLR.0000000000000490

  View details for PubMedID 26759981

• New Paradigms for Patient-Centered Outcomes Research in Electronic Medical Records: An Example of Detecting Urinary Incontinence Following Prostatectomy. EGEMS (Washington, DC) Hernandez-Boussard, T., Tamang, S., Blayney, D., Brooks, J., Shah, N. 2016; 4 (3): 1231-?

  Abstract

  National initiatives to develop quality metrics emphasize the need to include patient-centered outcomes. Patient-centered outcomes are complex, require documentation of patient communications, and have not been routinely collected by healthcare providers. The widespread implementation of electronic medical records (EHR) offers opportunities to assess patient-centered outcomes within the routine healthcare delivery system. The objective of this study was to test the feasibility and accuracy of identifying patient centered outcomes within the EHR.Data from patients with localized prostate cancer undergoing prostatectomy were used to develop and test algorithms to accurately identify patient-centered outcomes in post-operative EHRs - we used urinary incontinence as the use case. Standard data mining techniques were used to extract and annotate free text and structured data to assess urinary incontinence recorded within the EHRs.A total 5,349 prostate cancer patients were identified in our EHR-system between 1998-2013. Among these EHRs, 30.3% had a text mention of urinary incontinence within 90 days post-operative compared to less than 1.0% with a structured data field for urinary incontinence (i.e. ICD-9 code). Our workflow had good precision and recall for urinary incontinence (positive predictive value: 0.73 and sensitivity: 0.84).Our data indicate that important patient-centered outcomes, such as urinary incontinence, are being captured in EHRs as free text and highlight the long-standing importance of accurate clinician documentation. Standard data mining algorithms can accurately and efficiently identify these outcomes in existing EHRs; the complete assessment of these outcomes is essential to move practice into the patient-centered realm of healthcare.

  View details for DOI 10.13063/2327-9214.1231

  View details for PubMedID 27347492

• Pediatric Patient and Hospital Characteristics Associated With Treatment of Peritonsillar Abscess and Peritonsillar Cellulitis. Clinical pediatrics Nguyen, T., Haberland, C. A., Hernandez-Boussard, T. 2015; 54 (13): 1240-1246

  Abstract

  Objective. To identify patient and hospital characteristics associated with the choice of treatment for pediatric patients who present in the acute setting with peritonsillar abscess/cellulitis (PTA/PTC). Study Design. A retrospective cohort study was performed using Healthcare Cost and Utilization Project emergency department, ambulatory, and inpatient state databases for the years 2010 and 2011. Children aged 0 to 17 years were identified using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis code for PTA/PTC. The main outcome of interest was treatment received, which included medical therapy alone, incision and drainage (IND) or tonsillectomy. Multiple logistic regression analyses were conducted to model non-clinical factors associated with treatment received after adjusting for age, hospital state, race, primary expected payer, existing chronic condition(s), and type of hospital. Results. We identified 2994 patients who presented with PTA/PTC. The most common treatment choice was medical therapy alone (30.8%), followed by IND (30.5%) and tonsillectomy (9.4%). There were significant associations between treatment choice and race, primary payer status, and type of hospital (P < .05). We found that Hispanic patients, those with Medicaid as their primary expected payer, and those treated at a designated children's hospital were 3 nonclinical factors independently associated with an increase in likelihood of receiving tonsillectomy as treatment. Conclusion. There are important nonclinical factors associated with treatment of children who present in the acute setting with PTA/PTC. Additional research is recommended to understand these observed differences in care and how they may affect health outcomes.

  View details for DOI 10.1177/0009922814565884

  View details for PubMedID 25589309

• The Effect of Moving Carpal Tunnel Releases Out of Hospitals on Reducing United States Health Care Charges. journal of hand surgery Nguyen, C., Milstein, A., Hernandez-Boussard, T., Curtin, C. M. 2015; 40 (8): 1657-1662

  Abstract

  To better understand how perioperative care affects charges for carpal tunnel release (CTR).We developed a cohort using ICD9-CM procedure code 04.43 for CTR in the National Survey of Ambulatory Surgery 2006 to test perioperative factors potentially associated with CTR costs. We examined factors that might affect costs, including patient characteristics, payer, surgical time, setting (hospital outpatient department vs. freestanding ambulatory surgery center), anesthesia type, anesthesia provider, discharge status, and adverse events. Records were grouped by facility to reduce the impact of surgeon and patient heterogeneity. Facilities were divided into quintiles based on average total facility charges per CTR. This division allowed comparison of factors associated with the lowest and highest quintile of facilities based on average charge per CTR.A total of 160,000 CTRs were performed in 2006. Nearly all patients were discharged home without adverse events. Mean charge across facilities was $2,572 (SD, $2,331-$2,813). Patient complexity and intraoperative duration of surgery was similar across quintiles (approximately 13 min). Anesthesia techniques were not significantly associated with patient complexity, charges, and total perioperative time. Hospital outpatient department setting was strongly associated with total charges, with $500 higher charge per CTR. Half of all CTRs were performed in hospital outpatient departments. Facilities in the lowest quintile charge group were freestanding ambulatory surgery centers.Examination of charges for CTR suggests that surgical setting is a large cost driver with the potential opportunity to lower charges for CTRs by approximately 30% if performed in ASCs.Economic/decision analysis II.

  View details for DOI 10.1016/j.jhsa.2015.04.023

  View details for PubMedID 26070229

• Cranial neurosurgical 30-day readmissions by clinical indication JOURNAL OF NEUROSURGERY Moghavem, N., Morrison, D., Ratliff, J. K., Hernandez-Boussard, T. 2015; 123 (1): 189-197

  Abstract

  Postsurgical readmissions are common and vary by procedure. They are significant drivers of increased expenditures in the health care system. Reducing readmissions is a national priority that has summoned significant effort and resources. Before the impact of quality improvement efforts can be measured, baseline procedure-related 30-day all-cause readmission rates are needed. The objects of this study were to determine population-level, 30-day, all-cause readmission rates for cranial neurosurgery and identify factors associated with readmission.The authors identified patient discharge records for cranial neurosurgery and their 30-day all-cause readmissions using the Agency for Healthcare Research and Quality (AHRQ) State Inpatient Databases for California, Florida, and New York. Patients were categorized into 4 groups representing procedure indication based on ICD-9-CM diagnosis codes. Logistic regression models were developed to identify patient characteristics associated with readmissions. The main outcome measure was unplanned inpatient admission within 30 days of discharge.A total of 43,356 patients underwent cranial neurosurgery for neoplasm (44.23%), seizure (2.80%), vascular conditions (26.04%), and trauma (26.93%). Inpatient mortality was highest for vascular admissions (19.30%) and lowest for neoplasm admissions (1.87%; p < 0.001). Thirty-day readmissions were 17.27% for the neoplasm group, 13.89% for the seizure group, 23.89% for the vascular group, and 19.82% for the trauma group (p < 0.001). Significant predictors of 30-day readmission for neoplasm were Medicaid payer (OR 1.33, 95% CI 1.15-1.54) and fluid/electrolyte disorder (OR 1.44, 95% CI 1.29-1.62); for seizure, male sex (OR 1.74, 95% CI 1.17-2.60) and index admission through the emergency department (OR 2.22, 95% CI 1.45-3.43); for vascular, Medicare payer (OR 1.21, 95% CI 1.05-1.39) and renal failure (OR 1.52, 95% CI 1.29-1.80); and for trauma, congestive heart failure (OR 1.44, 95% CI 1.16-1.80) and coagulopathy (OR 1.51, 95% CI 1.25-1.84). Many readmissions had primary diagnoses identified by the AHRQ as potentially preventable.The frequency of 30-day readmission rates for patients undergoing cranial neurosurgery varied by diagnosis between 14% and 24%. Important patient characteristics and comorbidities that were associated with an increased readmission risk were identified. Some hospital-level characteristics appeared to be associated with a decreased readmission risk. These baseline readmission rates can be used to inform future efforts in quality improvement and readmission reduction.

  View details for DOI 10.3171/2014.12.JNS14447

  View details for Web of Science ID 000356981200025

  View details for PubMedID 25658784

• Patient safety in plastic surgery: identifying areas for quality improvement efforts. Annals of plastic surgery Hernandez-Boussard, T., McDonald, K. M., Rhoads, K. F., Curtin, C. M. 2015; 74 (5): 597-602

  Abstract

  Improving quality of health care is a global priority. Before quality benchmarks are established, we first must understand rates of adverse events (AEs). This project assessed risk-adjusted rates of inpatient AEs for soft tissue reconstructive procedures.Patients receiving soft tissue reconstructive procedures from 2005 to 2010 were extracted from the Nationwide Inpatient Sample. Inpatient AEs were identified using patient safety indicators (PSIs), established measures developed by Agency for Healthcare Research and Quality.We identified 409,991 patients with soft tissue reconstruction and 16,635 (4.06%) had a PSI during their hospital stay. Patient safety indicators were associated with increased risk-adjusted mortality, longer length of stay, and decreased routine disposition (P < 0.01). Patient characteristics associated with a higher risk-adjusted rate per 1000 patients at risk included older age, men, nonwhite, and public payer (P < 0.05). Overall, plastic surgery patients had significantly lower risk-adjusted rate compared to other surgical inpatients for all events evaluated except for failure to rescue and postoperative hemorrhage or hematoma, which were not statistically different. Risk-adjusted rates of hematoma hemorrhage were significantly higher in patients receiving size-reduction surgery, and these rates were further accentuated when broken down by sex and payer.In general, plastic surgery patients had lower rates of in-hospital AEs than other surgical disciplines, but PSIs were not uncommon. With the establishment of national basal PSI rates in plastic surgery patients, benchmarks can be devised and target areas for quality improvement efforts identified. Further prospective studies should be designed to elucidate the drivers of AEs identified in this population.

  View details for DOI 10.1097/SAP.0b013e318297791e

  View details for PubMedID 24108144

• The TRANSFORM Patient Safety Project: A Microsystem Approach to Improving Outcomes on Inpatient Units JOURNAL OF GENERAL INTERNAL MEDICINE Braddock, C. H., Szaflarski, N., Forsey, L., Abel, L., Hernandez-Boussard, T., Morton, J. 2015; 30 (4): 425-433

  Abstract

  Improvements in hospital patient safety have been made, but innovative approaches are needed to accelerate progress. Evidence is emerging that microsystem approaches to quality and safety improvement in hospital care are effective.We aimed to evaluate the effects of a multifaceted, microsystem-level patient safety program on clinical outcomes and safety culture on inpatient units.A 1-year prospective interventional study was conducted, followed by a 6-month sustainability phase.Four medical and surgical inpatient units within an academic university medical center were included, with registered nurses and residents representing study participants.In situ simulation training; debriefing of medical emergencies; monthly patient safety team meetings; patient safety champion role; interdisciplinary patient safety conferences; recognition program for exemplary teamwork.Hospital-acquired severe sepsis/septic shock and acute respiratory failure; unplanned transfers to higher level of care (HLOC); weighted risk-adjusted mortality. Safety culture was measured using a widely accepted, validated survey.Rates of hospital-acquired severe sepsis/septic shock and acute respiratory failure decreased on study units, from 1.78 to 0.64 (p = 0.04) and 2.44 to 0.43 per 1,000 unit discharges (p = 0.03), respectively. The mean number of days between cases of severe sepsis/septic shock increased from baseline to the intervention period (p = 0.03). Unplanned transfers to HLOC increased from 715 to 764 per 1,000 unit transfers (p = 0.08). The weighted risk-adjusted observed-to-expected mortality ratio on all study units decreased from 0.50 to 0.40 (p < 0.001). Overall scores of safety culture on study units improved after the 1-year intervention, significantly for nurses (p < 0.001), but not for residents (p = 0.06). Scores significantly improved in nine of twelve survey dimensions for nurses, compared to in four dimensions for residents.A multifaceted patient safety program suggested an association with improved hospital-acquired complications and weighted, risk-adjusted mortality, and improved nurses' perceptions of safety culture on inpatient study units.

  View details for DOI 10.1007/s11606-014-3067-7

  View details for Web of Science ID 000351664000014

  View details for PubMedID 25348342

• Ambulatory surgery center utilization by vitreoretinal surgeons: 1999-2011. Ophthalmic surgery, lasers & imaging retina Vaziri, K., Moshfeghi, D. M., Hernandez-Boussard, T., Callaway, N. F., Moshfeghi, A. A. 2015; 46 (3): 355-361

  Abstract

  To evaluate the utilization rates of ambulatory surgery centers (ASCs) in the state of Florida for vitreoretinal, cataract, and glaucoma surgical procedures over a 13-year period from 1999 through 2011.Retrospective analysis utilizing the State Ambulatory Surgery Databases (SASD) for Florida from 1999 through 2011. ICD-9 codes for vitreoretinal, cataract, and glaucoma procedures were queried. Joinpoint regression was used to calculate average annual percent change (APC) in ASC utilization by these procedures over the 13-year study period and also separately for the years 2007 to 2011.From 1999 through 2011, APC in ambulatory surgery center utilization was +26.4% (P = .0039) for vitreoretinal, +21.3% (P = .012) for cataract, and +20.9% (P = .0063) for glaucoma surgery. The APC from 2007 through 2011 was -1.2% for vitreoretinal (P = .47), -9.2% for cataract (P = .0039), and -17.3% for glaucoma surgery (P = .008).A significant overall increase in ASC utilization by vitreoretinal, cataract, and glaucoma surgeons over the study period was seen; however, the most recent 5-year data show that these trends may have begun to reverse. [Ophthalmic Surg Lasers Imaging Retina. 2015;46:355-361.].

  View details for DOI 10.3928/23258160-20150323-10

  View details for PubMedID 25856823

• Ambulatory surgery center utilization by vitreoretinal surgeons: 1999-2011. Ophthalmic surgery, lasers & imaging retina Vaziri, K., Moshfeghi, D. M., Hernandez-Boussard, T., Callaway, N. F., Moshfeghi, A. A. 2015; 46 (3): 355-361

  View details for DOI 10.3928/23258160-20150323-10

  View details for PubMedID 25856823

• Impact of histological subtype on long-term outcomes of neuroendocrine carcinoma of the breast BREAST CANCER RESEARCH AND TREATMENT Cloyd, J. M., Yang, R. L., Allison, K. H., Norton, J. A., Hernandez-Boussard, T., Wapnir, I. L. 2014; 148 (3): 637-644

  Abstract

  Although rare, neuroendocrine carcinoma of the breast (NECB) is becoming an increasingly recognized entity. The current literature is limited to case reports and small series and therefore a comprehensive population-based analysis was conducted to investigate the clinicopathologic features and long-term outcomes associated with NECB. We included all patients in the SEER Database from 2003 to 2010 with a diagnosis of NECB. The 2012 WHO classification system was used to categorize patients based on histopathologic diagnosis: well-differentiated neuroendocrine tumors, small/oat cell or poorly differentiated neuroendocrine tumors, adenocarcinoma with neuroendocrine features (ANF), large cell neuroendocrine and carcinoid tumors. Survival analysis was performed for disease specific (DSS) and overall (OS) survival. Of the 284 cases identified, 52.1% were classified as well-differentiated, 25.7% small cell, 14.8% ANF, 4.9% large cell, and 2.5% carcinoid. In general, patients presented with advanced disease: 36.2% had positive lymph node metastases and 20.4% presented with systemic metastases. Five-year DSS rates for stage I-IV NECB were 88.1, 67.8, 60.5, and 12.4%, respectively, while five-year OS rates were 77.9, 57.3, 52.9, and 8.9%, respectively. DSS and OS were significantly different for well-differentiated neuroendocrine tumors and ANFs compared to small cell and carcinoid tumors. On univariate Cox proportional hazards regression, small cell carcinoma was significantly associated with worse DSS (OR 1.97, 95% CI 1.05-3.67) and OS (OR 2.66, 95% CI 1.49-4.72) compared to other neuroendocrine tumors. NECB is associated with advanced stage disease at presentation and an unfavorable prognosis for stage II-IV disease and small cell, large cell, and carcinoid histologic subtypes.

  View details for DOI 10.1007/s10549-014-3207-0

  View details for Web of Science ID 000345370600018

• Impact of histological subtype on long-term outcomes of neuroendocrine carcinoma of the breast. Breast cancer research and treatment Cloyd, J. M., Yang, R. L., Allison, K. H., Norton, J. A., Hernandez-Boussard, T., Wapnir, I. L. 2014; 148 (3): 637-644

  Abstract

  Although rare, neuroendocrine carcinoma of the breast (NECB) is becoming an increasingly recognized entity. The current literature is limited to case reports and small series and therefore a comprehensive population-based analysis was conducted to investigate the clinicopathologic features and long-term outcomes associated with NECB. We included all patients in the SEER Database from 2003 to 2010 with a diagnosis of NECB. The 2012 WHO classification system was used to categorize patients based on histopathologic diagnosis: well-differentiated neuroendocrine tumors, small/oat cell or poorly differentiated neuroendocrine tumors, adenocarcinoma with neuroendocrine features (ANF), large cell neuroendocrine and carcinoid tumors. Survival analysis was performed for disease specific (DSS) and overall (OS) survival. Of the 284 cases identified, 52.1% were classified as well-differentiated, 25.7% small cell, 14.8% ANF, 4.9% large cell, and 2.5% carcinoid. In general, patients presented with advanced disease: 36.2% had positive lymph node metastases and 20.4% presented with systemic metastases. Five-year DSS rates for stage I-IV NECB were 88.1, 67.8, 60.5, and 12.4%, respectively, while five-year OS rates were 77.9, 57.3, 52.9, and 8.9%, respectively. DSS and OS were significantly different for well-differentiated neuroendocrine tumors and ANFs compared to small cell and carcinoid tumors. On univariate Cox proportional hazards regression, small cell carcinoma was significantly associated with worse DSS (OR 1.97, 95% CI 1.05-3.67) and OS (OR 2.66, 95% CI 1.49-4.72) compared to other neuroendocrine tumors. NECB is associated with advanced stage disease at presentation and an unfavorable prognosis for stage II-IV disease and small cell, large cell, and carcinoid histologic subtypes.

  View details for DOI 10.1007/s10549-014-3207-0

  View details for PubMedID 25399232

• Interhospital Facility Transfers in the United States: A Nationwide Outcomes Study. Journal of patient safety Hernandez-Boussard, T., Davies, S., McDonald, K., Wang, N. E. 2014: -?

  Abstract

  Patient transfers between hospitals are becoming more common in the United States. Disease-specific studies have reported varying outcomes associated with transfer status. However, even as national quality improvement efforts and regulations are being actively adopted, forcing hospitals to become financially accountable for the quality of care provided, surprisingly little is known about transfer patients or their outcomes at a population level. This population-wide study provides timely analyses of the characteristics of this particularly vulnerable and sizable inpatient population. We identified and compared characteristics and outcomes of transfer and nontransfer patients.With the use of the 2009 Nationwide Inpatient Sample, a nationally representative sample of U.S. hospitalizations, we examined patient characteristics, in-hospital adverse events, and discharge disposition for transfer versus nontransfer patients in this observational study.We identified 1,397,712 transfer patients and 31,692,211 nontransfer patients. Age, sex, race, and payer were significantly associated with odds of transfer (P < 0.05). Transfer patients had higher risk-adjusted inpatient mortality (4.6 versus 2.1, P < 0.01), longer length of stay (13.3 versus 4.5, P < 0.01), and fewer routine disposition discharges (53.6 versus 68.7, P < 0.01). In-hospital adverse events were significantly higher in transfer patients compared with nontransfer patients (P < 0.05).Our results suggest that transfer patients have inferior outcomes compared with nontransfer patients. Although they are clinically complex patients and assessing accountability as between the transferring and receiving hospitals is methodologically difficult, transfer patients must nonetheless be included in quality benchmark data to assess the potential impact this population has on hospital outcome profiles. With hospital accountability and value-based payments constituting an integral part of health care reform, documenting the quality of care delivered to transfer patients is essential before accurate quality assessment improvement efforts can begin in this patient population.

  View details for PubMedID 25397857

• Restrictive blood transfusion practices are associated with improved patient outcomes. Transfusion Goodnough, L. T., Maggio, P., Hadhazy, E., Shieh, L., Hernandez-Boussard, T., Khari, P., Shah, N. 2014; 54 (10): 2753-2759

  Abstract

  Blood transfusion has been cited as one of the five most overutilized therapeutic procedures in the United States. We assessed the impact of clinical decision support at computerized physician order entry and education on red blood cell (RBC) transfusions and clinical patient outcomes at our institution.Clinical patient outcomes and RBC transfusions were assessed before and after implementation of a best practice alert triggered for transfusions when the hemoglobin level was higher than 7 g/dL for all inpatient discharges from January 2008 through December 2013. Retrospective clinical and laboratory data related to RBC transfusions were extracted: case-mix complexity, patient discharges and selected surgical volumes, and patient outcomes (mortality, 30-day readmissions, length of stay).There was a significant improvement in RBC utilization as assessed by RBC units transfused per 100 patient-days-at-risk. Concurrently, hospital-wide clinical patient outcomes showed improvement (mortality, p = 0.034; length of stay, p = 0.003) or remained stable (30-day readmission rates, p = 0.909). Outcome improvements were even more pronounced in patients who received blood transfusions, with decreased mortality rate (55.2 to 33.0, p < 0.001), length of stay (mean, 10.1 to 6.2 days, p < 0.001), and 30-day readmission rate (136.9 to 85.0, p < 0.001). The mean number of units transfused per patient also declined (3.6 to 2.7, p < 0.001). Acquisition costs of RBC units per 1000 patient discharges decreased from $283,130 in 2009 to $205,050 in 2013 with total estimated savings of $6.4 million and likely far greater impact on total transfusion-related costs.Improved blood utilization is associated with improved clinical patient outcomes.

  View details for DOI 10.1111/trf.12723

  View details for PubMedID 24995770

• Restrictive blood transfusion practices are associated with improved patient outcomes TRANSFUSION Goodnough, L. T., Maggio, P., Hadhazy, E., Shieh, L., Hernandez-Boussard, T., Khari, P., Shah, N. 2014; 54 (10): 2753-2759

  Abstract

  Blood transfusion has been cited as one of the five most overutilized therapeutic procedures in the United States. We assessed the impact of clinical decision support at computerized physician order entry and education on red blood cell (RBC) transfusions and clinical patient outcomes at our institution.Clinical patient outcomes and RBC transfusions were assessed before and after implementation of a best practice alert triggered for transfusions when the hemoglobin level was higher than 7 g/dL for all inpatient discharges from January 2008 through December 2013. Retrospective clinical and laboratory data related to RBC transfusions were extracted: case-mix complexity, patient discharges and selected surgical volumes, and patient outcomes (mortality, 30-day readmissions, length of stay).There was a significant improvement in RBC utilization as assessed by RBC units transfused per 100 patient-days-at-risk. Concurrently, hospital-wide clinical patient outcomes showed improvement (mortality, p = 0.034; length of stay, p = 0.003) or remained stable (30-day readmission rates, p = 0.909). Outcome improvements were even more pronounced in patients who received blood transfusions, with decreased mortality rate (55.2 to 33.0, p < 0.001), length of stay (mean, 10.1 to 6.2 days, p < 0.001), and 30-day readmission rate (136.9 to 85.0, p < 0.001). The mean number of units transfused per patient also declined (3.6 to 2.7, p < 0.001). Acquisition costs of RBC units per 1000 patient discharges decreased from $283,130 in 2009 to $205,050 in 2013 with total estimated savings of $6.4 million and likely far greater impact on total transfusion-related costs.Improved blood utilization is associated with improved clinical patient outcomes.

  View details for DOI 10.1111/trf.12723

  View details for Web of Science ID 000343821100023

• Readmissions After Treatment of Distal Radius Fractures JOURNAL OF HAND SURGERY-AMERICAN VOLUME Curtin, C. M., Hernandez-Boussard, T. 2014; 39 (10): 1926-1932

  Abstract

  To assess the rates and associated diagnoses of readmissions for patients having received an intervention for treatment of distal radius fracture.We analyzed patient discharges from 2005-2011 for California, Florida, and New York. We used Agency for Healthcare Research and Quality data sets: (1) State Inpatient Database, (2) State Ambulatory Surgery Database, and (3) State Emergency Department Database. We examined inpatient, outpatient, and emergency room treatment locations. We identified patients by diagnosis code for distal radius fracture (813.41). Patients were stratified based on procedure codes for open reduction, closed reduction, and external fixation. The cohort was followed for 30 days to examine all-cause 30-day inpatient admissions and emergency department visits.We identified 35,241 discharges with a primary diagnosis of distal radius facture. Of those, 18,388 patients underwent a procedure for their fracture, and 1,679 (9%) were readmitted within 30 days of discharge. Readmission rates varied by procedure type: internal fixation 8%, closed reduction 14%, and external fixation 11%. The most common diagnosis codes associated with readmission were general distal radius fracture codes (11%) and pain diagnoses (10%). Open procedures had higher odds of having a readmission associated with pain compared with closed treatment and external fixation.Readmissions after treatment of distal radius fracture care are common. Our results show many distal radius fracture patients return to the health care system for pain-related issues. As more emphasis is placed on quality health care delivery, implementation of better pain management will be important to health care providers and patients.This study highlights that improved perioperative pain control may improve patient care and reduce readmissions.

  View details for DOI 10.1016/j.jhsa.2014.07.041

  View details for Web of Science ID 000342733500006

• Readmissions after treatment of distal radius fractures. journal of hand surgery Curtin, C. M., Hernandez-Boussard, T. 2014; 39 (10): 1926-1932

  Abstract

  To assess the rates and associated diagnoses of readmissions for patients having received an intervention for treatment of distal radius fracture.We analyzed patient discharges from 2005-2011 for California, Florida, and New York. We used Agency for Healthcare Research and Quality data sets: (1) State Inpatient Database, (2) State Ambulatory Surgery Database, and (3) State Emergency Department Database. We examined inpatient, outpatient, and emergency room treatment locations. We identified patients by diagnosis code for distal radius fracture (813.41). Patients were stratified based on procedure codes for open reduction, closed reduction, and external fixation. The cohort was followed for 30 days to examine all-cause 30-day inpatient admissions and emergency department visits.We identified 35,241 discharges with a primary diagnosis of distal radius facture. Of those, 18,388 patients underwent a procedure for their fracture, and 1,679 (9%) were readmitted within 30 days of discharge. Readmission rates varied by procedure type: internal fixation 8%, closed reduction 14%, and external fixation 11%. The most common diagnosis codes associated with readmission were general distal radius fracture codes (11%) and pain diagnoses (10%). Open procedures had higher odds of having a readmission associated with pain compared with closed treatment and external fixation.Readmissions after treatment of distal radius fracture care are common. Our results show many distal radius fracture patients return to the health care system for pain-related issues. As more emphasis is placed on quality health care delivery, implementation of better pain management will be important to health care providers and patients.This study highlights that improved perioperative pain control may improve patient care and reduce readmissions.

  View details for DOI 10.1016/j.jhsa.2014.07.041

  View details for PubMedID 25257486

• Interfacility transfer and mortality for patients with ruptured abdominal aortic aneurysm. Journal of vascular surgery Mell, M. W., Wang, N. E., Morrison, D. E., Hernandez-Boussard, T. 2014; 60 (3): 553-557

  Abstract

  Patients receiving interfacility transfer to a higher level of medical care for ruptured abdominal aortic aneurysms (rAAAs) are an important minority that are not well characterized and are typically omitted from outcomes and quality indicator studies. Our objective was to compare patients transferred for treatment of rAAAs with those treated without transfer, with particular emphasis on mortality and resource utilization.We linked longitudinal data from 2005 to 2010 Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases and Emergency Department Databases from California, Florida, and New York. Patients were identified using International Classification of Diseases-Ninth Revision-Clinical Modification codes. Our main outcome variables were mortality, length of stay, and cost. Data included discharge information on the transfer-out and transfer-in hospital. We used univariate and multivariate analysis to identify variables independently associated with transfer and in-hospital mortality.Of 4439 rAAA patients identified with intent to treat, 847 (19.1%) were transferred before receiving operative repair. Of those transferred, 141 (17%) died without undergoing AAA repair. By multivariate analysis, increasing age in years (odds ratio [OR] 0.98; 95% confidence interval [CI], 0.97-0.99; P < .001), private insurance vs Medicare (OR, 0.62; 95% CI, 0.47-0.80; P < .001), and increasing comorbidities as measured by the Elixhauser Comorbidity Index (OR, 0.90; 95% CI, 0.86-0.95; P < .001) were negatively associated with transfer. Weekend presentation (OR, 1.23; 95% CI, 1.02-1.47; P = .03) was positively associated with transfer. Transfer was associated with a lower operative mortality (adjusted OR, 0.81; 95% CI, 0.68-0.97; P < .02) but an increased overall mortality when including transferred patients who died without surgery (OR, 1.30; 95% CI, 1.05-1.60; P = .01). Among the transferred patients, there was no significant difference in travel distance between those who survived and those who died (median, 28.7 vs 25.8 miles; P = .07). Length of stay (median, 10 vs 9 days; P = .008), and hospital costs ($161,000 vs $146,000; P = .02) were higher for those transferred.The survival advantage for patients transferred who received treatment was eclipsed by increased mortality of the transfer process. Including 17% of transferred patients who died without receiving definitive repair, mortality was increased for patients transferred for rAAA repair compared with those not transferred after adjusting for demographic, clinical, and hospital factors. Transferred patients used significantly more hospital resources. Improving systems and guidelines for interfacility transfer may further improve the outcomes for these patients and decrease associated hospital resource utilization.

  View details for DOI 10.1016/j.jvs.2014.02.061

  View details for PubMedID 24768368

• The Affordable Care Act reduces emergency department use by young adults: evidence from three States. Health affairs Hernandez-Boussard, T., Burns, C. S., Wang, N. E., Baker, L. C., Goldstein, B. A. 2014; 33 (9): 1648-1654

  Abstract

  The Affordable Care Act (ACA) extended eligibility for health insurance for young adults ages 19-25. This extension may have affected how young adults use emergency department (ED) care and other health services. To test the impact of the ACA on how young adults used ED services, we used 2009-11 state administrative records from California, Florida, and New York to compare changes in ED use in young adults ages 19-25 before and after the ACA provision was implemented with changes in the same period for people ages 26-31 (the control group). Following implementation of the ACA provision, the younger group had a decrease of 2.7 ED visits per 1,000 people compared to the older group-a relative change of -2.1 percent. The largest relative decreases were found in women (-3.0 percent) and blacks (-3.4 percent). This relative decrease in ED use implies a total reduction of more than 60,000 visits from young adults ages 19-25 across the three states in 2011. When we compared the probability of ever using the ED before and after implementation of the ACA provision, we found a minimal decrease (-0.4 percent) among the younger group compared to the older group. This suggests that the change in the number of visits was driven by fewer visits among ED users, not by changes in the number of people who ever visited the ED.

  View details for DOI 10.1377/hlthaff.2014.0103

  View details for PubMedID 25201671

• National Review of Factors Influencing Disparities and Types of Major Lower Extremity Amputations ANNALS OF VASCULAR SURGERY Zayed, M., Bech, F., Hernandez-Boussard, T. 2014; 28 (5): 1157-1165

  Abstract

  Despite advancements in the diagnosis and treatment of peripheral vascular disease, major lower extremity amputations are still performed at high rates with non-negligible economic burdens. Peri-operative morbidity and mortality is greater for patients who receive an above knee amputation (AKA) compared to patients who receive a below knee amputation (BKA). We sought to further evaluate what variables affect whether a patient receives a BKA versus an AKA using the Nationwide Inpatient Sample (NIS).From 2005 to 2008, all adult AKA and BKA procedures were identified in the NIS. Patients with trauma and oncologic diagnoses were excluded from the analysis. Rates of AKA and BKA were evaluated according to patient demographics, co-morbidities, extent of pre-amputation vascular intervention, hospital setting/type, and geographic region. Multivariate logistic regression and 2-way ANOVA analyses was used to determine statistical significance.A total of 228,624 patients met inclusion criteria (126,076 BKA, 102,548 AKA). Patients who received an AKA were more likely to be female (p<0.0001), older (p<0.0001), have non-private insurance (p<0.0001), and have a higher Elixhauser Co-morbidity Index (p<0.0001). Patients who received a BKA were more likely to have hypertension, diabetes, and a spinal cord injury (p<0.0001). Less limb salvage vascular interventions were attempted in low-volume hospitals and in patients who subsequently received AKA (p<0.0001), while more limb salvage vascular interventions were performed at high-volume centers where more BKA procedures were performed (p<0.0001). The majority of major amputations were performed in southern states (46.4%), and more BKA procedures were performed in urban and teaching hospitals (p<0.0001).Using the NIS database we found important differences between patients who receive a BKA versus an AKA. These differences are broadly observed between patient demographics, race, and co-morbidities, as well as insurance type, geographic region, and hospital type. Our findings highlight the need for more aggressive surveillance and preventative care of at risk populations.

  View details for DOI 10.1016/j.avsg.2013.11.008

  View details for Web of Science ID 000338090700011

  View details for PubMedID 24365081

• Cleft palate surgery: an evaluation of length of stay, complications, and costs by hospital type. Cleft palate-craniofacial journal Nguyen, C., Hernandez-Boussard, T., Davies, S. M., Bhattacharya, J., Khosla, R. K., Curtin, C. M. 2014; 51 (4): 412-419

  Abstract

  Objective : The purpose of this study was to assess length of stay (LOS), complication rates, costs, and charges of cleft palate repair by various hospital types. We hypothesized that pediatric hospitals would have shorter LOS, fewer complications, and lower costs and charges. Methods : Patients were identified by ICD-9-CM code for cleft palate repair (27.62) using databases from the Agency for Health Research and Quality Healthcare Cost and Utilization Project Kids' Inpatient Database from 1997, 2000, 2003, and 2006. Patient characteristics (age, race, gender, insurer, comorbidities) and facility resources (hospital beds, cleft palate surgery volume, nurse-to-bed ratio, pediatric intensive care unit [PICU], PICU intensivist, burn unit) were examined. Hospitals types included pediatric hospitals, general hospitals, and nonaccredited children's hospital. For each hospital type, mean LOS, extended LOS (LOS > 2), and complications were assessed. Results : A total of 14,153 patients had cleft repair with a mean LOS of 2 days (SD, 0.04), mortality 0.01%, transfusion 0.3%, and complication <3%. Pediatric hospitals had fewer patients with extended hospital stays. Patients with an LOS >2 days were associated with fourfold higher complications. Comorbidities increased the relative rate of LOS >2 days by 90%. Pediatric hospitals had the highest comorbidities, yet 35% decreased the relative rate of LOS >2 days. Median total charges of $10,835 increased to $15,104 with LOS >2 days; median total costs of $4367 increased to $6148 with a LOS >2 days. Conclusion : Pediatric hospitals had higher comorbidities yet shorter LOS. Pediatric resources significantly decreased the relative rate of LOS >2 days. Median costs and charges increased by 41% with LOS >2 days. Further research is needed to understand additional aspects of pediatric hospitals associated with lower LOS.

  View details for DOI 10.1597/12-150

  View details for PubMedID 24063682

• PHYSICIAN IDENTIFICATION AND PATIENT SATISFACTION IN THE EMERGENCY DEPARTMENT: ARE THEY RELATED? JOURNAL OF EMERGENCY MEDICINE Mercer, M. P., Hernandez-Boussard, T., Mahadevan, S. V., Strehlow, M. C. 2014; 46 (5): 711-718

  Abstract

  Patient satisfaction has become a quality indicator tracked closely by hospitals and emergency departments (EDs). Unfortunately, the primary factors driving patient satisfaction remain poorly studied. It has been suggested that correct physician identification impacts patient satisfaction in hospitalized patients, however, the limited studies that exist have demonstrated mixed results.In this study, we sought to identify factors associated with improved satisfaction among ED patients, and specifically, to test whether improving physician identification by patients would lead to increased satisfaction.We performed a pre- and postintervention, survey-based study of patients at the end of their ED visits. We compared patient satisfaction scores as well as patients' abilities to correctly identify their physicians over two separate 1-week periods: prior to and after introducing a multimedia presentation of the attending physicians into the waiting room.A total of 486 patients (25% of all ED visits) were enrolled in the study. In the combined study population, overall patient satisfaction was higher among patients who correctly identified their physicians than among those who could not identify their physicians (combined mean satisfaction score of 8.1 vs. 7.2; odds ratio [OR] 1.07). Overall satisfaction was also higher among parents or guardians of pediatric patients than among adult patients (satisfaction score of 8.4 vs. 7.4; OR 1.07), and among patients who experienced a shorter door-to-doctor time (satisfaction score of 8.2 for shorter waiting time vs. 5.6 for longer waiting time; OR 1.15). Ambulance patients showed decreased satisfaction over some satisfaction parameters, including physician courtesy and knowledge. No direct relationship was demonstrated between the study intervention (multimedia presentation) and improved patient satisfaction or physician identification.Improved patient satisfaction was found to be positively correlated with correct physician identification, shorter waiting times, and among the pediatric patient population. Further studies are needed to determine interventions that improve patients' abilities to identify their physicians and lower waiting times.

  View details for DOI 10.1016/j.jemermed.2013.08.036

  View details for PubMedID 24462030

• Factors Associated With the Disposition of Severely Injured Patients Initially Seen at Non-Trauma Center Emergency Departments Disparities by Insurance Status JAMA SURGERY Delgado, M. K., Yokell, M. A., Staudenmayer, K. L., Spain, D. A., Hernandez-Boussard, T., Wang, N. E. 2014; 149 (5): 422-430

  Abstract

  IMPORTANCE Trauma is the leading cause of potential years of life lost before age 65 years in the United States. Timely care in a designated trauma center has been shown to reduce mortality by 25%. However, many severely injured patients are not transferred to trauma centers after initially being seen at non-trauma center emergency departments (EDs). OBJECTIVES To determine patient-level and hospital-level factors associated with the decision to admit rather than transfer severely injured patients who are initially seen at non-trauma center EDs and to ascertain whether insured patients are more likely to be admitted than transferred compared with uninsured patients. DESIGN, SETTING, AND PARTICIPANTS Retrospective analysis of the 2009 Nationwide Emergency Department Sample. We included all ED encounters for major trauma (Injury Severity Score, >15) seen at non-trauma centers in patients aged 18 to 64 years. We excluded ED discharges and ED deaths. We quantified the absolute risk difference between admission vs transfer by insurance status, while adjusting for age, sex, mechanism of injury, Injury Severity Score, weekend admission and month of visit, and urban vs rural status and median household income of the home zip code, as well as annual ED visit volume and teaching status and US region. MAIN OUTCOMES AND MEASURES Inpatient admission vs transfer to another acute care facility. RESULTS In 2009, a total of 4513 observations from 636 non-trauma center EDs were available for analysis, representing a nationally weighted population of 19 312 non-trauma center ED encounters for major trauma. Overall, 54.5% in 2009 were admitted to the non-trauma center. Compared with patients without insurance, the adjusted absolute risk of admission vs transfer was 14.3% (95% CI, 9.2%-19.4%) higher for patients with Medicaid and 11.2% (95% CI, 6.9%-15.4%) higher for patients with private insurance. Other factors associated with admission vs transfer included severe abdominal injuries (risk difference, 15.9%; 95% CI, 9.4%-22.3%), urban teaching hospital vs non-teaching hospital (risk difference, 26.2%; 95% CI, 15.2%-37.2%), and annual ED visit volume (risk difference, 3.4%; 95% CI, 1.6%-5.3% higher for every additional 10 000 annual ED visits). CONCLUSIONS AND RELEVANCE Patients with severe injuries initially evaluated at non-trauma center EDs were less likely to be transferred if insured and were at risk of receiving suboptimal trauma care. Efforts in monitoring and optimizing trauma interhospital transfers and outcomes at the population level are warranted.

  View details for DOI 10.1001/jamasurg.2013.4398

  View details for Web of Science ID 000337908600005

• The Association of Nurse-to-Patient Ratio with Mortality and Preventable Complications Following Aortic Valve Replacement. Journal of cardiac surgery Arkin, N., Lee, P. H., McDonald, K., Hernandez-Boussard, T. 2014; 29 (2): 141-148

  Abstract

  To examine hospital resources associated with patient outcomes for aortic valve replacement (AVR), including inpatient adverse events and mortality.We used the Nationwide Inpatient Sample to identify AVR procedures from 1998 to 2010 and the American Hospital Association Annual Survey to augment hospital characteristics. Primary outcomes included mortality and the development of adverse events, identified using standardized patient safety indicators (PSI). Patient and hospital characteristics associated with PSI development were evaluated using univariate and multivariate analyses.An estimated 410,157 AVRs at 5009 hospitals were performed in the US between 1998 and 2010. The number of procedures grew annually by 4.72% (p = 0.0003) in high volume hospitals, 4.48% in medium volume hospitals (p < 0.0001), and 2.03% in low volume hospitals (p = 0.154). Mortality was highest in low volume hospitals, 4.70%, decreased from 4.14% to 3.73% in medium and high volume hospitals, respectively (p = 0.0002). Rates of PSIs did not vary significantly across volume terciles (p = 0.254). Multivariate logistic regression analysis showed low volume hospitals had increased risk of mortality as compared with high volume hospitals (odds ratio [OR]: 1.42; 95% confidence interval [CI]: 1.01 to 2.00), while hospital volume was not associated with adverse events. PSI development was associated with small hospitals as compared with large (OR: 1.63, 95% CI: 1.16 to 2.28) and inversely associated with higher nurse-to-patient ratio (OR: 0.94, 95% CI: 0.90 to 0.99).The volume-outcomes relationship was associated with mortality outcomes but not postoperative complications. We identified structural differences in hospital size, nurses-to-patient ratio, and nursing skill level indicative of high quality outcomes.

  View details for DOI 10.1111/jocs.12284

  View details for PubMedID 24417274

• Lower Skin Cancer Risk in Women with Higher Body Mass Index: The Women's Health Initiative Observational Study. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology Tang, J. Y., Henderson, M. T., Hernandez-Boussard, T., Kubo, J., Desai, M., Sims, S. T., Aroda, V., Thomas, F., McTiernan, A., Stefanick, M. L. 2013; 22 (12): 2412-2415

  Abstract

  The unclear relationship of obesity to incident melanoma and nonmelanoma skin cancer (NMSC) risks was evaluated in the large, geographically diverse longitudinal, prospective Women's Health Initiative (WHI) observational study. Risks of melanoma and NMSC in normal weight women were compared with risks in overweight [body mass index (BMI) = 25-29.0 kg/m(2)] and obese (BMI ≥ 30 kg/m(2)) women, using Cox proportional hazards models for melanoma and logistic regression for NMSC. Over a mean 9.4 years of follow-up, there were 386 melanoma and 9,870 NSMC cases. Risk of melanoma did not differ across weight categories (P = 0.86), whereas in fully adjusted models, NMSC risk was lower in overweight [OR, 0.93; 95% confidence interval (CI), 0.89-0.99] and obese (OR, 0.85; 95% CI, 0.80-0.91) women (P < 0.001). Excess body weight was not associated with melanoma risk in postmenopausal women but was inversely associated with NMSC risk, possibly due to lower sun exposure in overweight and obese women. This supports previous work demonstrating the relationship between excess body weight and skin cancer risk. Cancer Epidemiol Biomarkers Prev; 22(12); 2412-5. ©2013 AACR.

  View details for DOI 10.1158/1055-9965.EPI-13-0647

  View details for PubMedID 24042260

• A national study on craniosynostosis surgical repair. Cleft palate-craniofacial journal Nguyen, C., Hernandez-Boussard, T., Khosla, R. K., Curtin, C. M. 2013; 50 (5): 555-560

  Abstract

  Objective :  Our study aimed to use national data to assess the perioperative outcomes of craniosynostosis surgical repair. Design :  Data were obtained from the Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project Kids Inpatient Database from 1997, 2000, 2003, and 2006. Setting :  Community hospitals in the United States. Patients :  The cohort was identified using the ICD-9-CM procedure codes for craniosynostosis surgical repair (2.01, 2.03, 2.04, 2.06). Main Outcome Measures(s) :  We determined patient and hospital characteristics. We clustered patients by age group (<7 months, 7 to 12 months, 1 to 3 years) and assessed mortality, comorbidities, mean length of stay (LOS), and total charge. We performed logistic regression with our dependent variable being longer average hospital stay: LOS >4.2 days. Results :  We found 3426 patients. Average age at the time of surgery was 181 days (SD 84). Average length of stay was 4.2 days. The majority of the patients were boys (66%), white (71%), and insured (93%). Nearly all patients underwent surgery in a teaching hospital (98%) in urban centers (99%). Approximately 10% of patients experienced an acute complication, most commonly hemorrhages or hematomas and airway or respiratory failure. Patients ages 1 to 3 years had the highest rates of comorbidities and a longer LOS. Mortality rate was <1%. Conclusions :  Craniosynostosis surgery is safe with low rates of mortality and acute complications. LOS >4.2 appears to be associated more with comorbidities than with complications. Higher rates of comorbidities and LOS >4.2 days for patients age 1 to 3 years warrant addition research to assess potential barriers to care.

  View details for DOI 10.1597/11-324

  View details for PubMedID 23030675

• A National Study on Craniosynostosis Surgical Repair CLEFT PALATE-CRANIOFACIAL JOURNAL Christine Nguyen, C., Hernandez-Boussard, T., Khosla, R. K., Curtin, C. M. 2013; 50 (5): 555-560

  Abstract

  Objective :  Our study aimed to use national data to assess the perioperative outcomes of craniosynostosis surgical repair. Design :  Data were obtained from the Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project Kids Inpatient Database from 1997, 2000, 2003, and 2006. Setting :  Community hospitals in the United States. Patients :  The cohort was identified using the ICD-9-CM procedure codes for craniosynostosis surgical repair (2.01, 2.03, 2.04, 2.06). Main Outcome Measures(s) :  We determined patient and hospital characteristics. We clustered patients by age group (<7 months, 7 to 12 months, 1 to 3 years) and assessed mortality, comorbidities, mean length of stay (LOS), and total charge. We performed logistic regression with our dependent variable being longer average hospital stay: LOS >4.2 days. Results :  We found 3426 patients. Average age at the time of surgery was 181 days (SD 84). Average length of stay was 4.2 days. The majority of the patients were boys (66%), white (71%), and insured (93%). Nearly all patients underwent surgery in a teaching hospital (98%) in urban centers (99%). Approximately 10% of patients experienced an acute complication, most commonly hemorrhages or hematomas and airway or respiratory failure. Patients ages 1 to 3 years had the highest rates of comorbidities and a longer LOS. Mortality rate was <1%. Conclusions :  Craniosynostosis surgery is safe with low rates of mortality and acute complications. LOS >4.2 appears to be associated more with comorbidities than with complications. Higher rates of comorbidities and LOS >4.2 days for patients age 1 to 3 years warrant addition research to assess potential barriers to care.

  View details for DOI 10.1597/11-324

  View details for Web of Science ID 000327536100011

• Breast reconstruction national trends and healthcare implications. breast journal Hernandez-Boussard, T., Zeidler, K., Barzin, A., Lee, G., Curtin, C. 2013; 19 (5): 463-469

  Abstract

  Breast reconstruction improves quality-of-life of breast cancer patients. Different reconstructive options exist, yet commentary in the plastic surgery literature suggests that financial constraints are limiting access to autologous reconstruction (AR). This study follows national trends in breast reconstruction and identifies factors associated with reconstructive choices. Data were obtained from the Nationwide Inpatient Sample from 1998 to 2008. Patients were categorized as having either implant or ARs. Bivariate and multivariate regression analysis identified variables associated with receiving implants versus AR. Physician fee schedules were analyzed using national average Medicare physician reimbursement rates. From 1998 to 2008, 324,134 breast reconstructions were performed. Reconstructions increased 4% per year. The proportion of implant reconstructions increased 11% per year, whereasARs decreased 5% per year (p < 0.05). Our model showed that the odds of having implant-based versus AR were significantly associated with age, disease severity, payer type, hospital teaching status, and year of surgery. Year of surgery was the strongest predictor of implant reconstruction; patients receiving breast reconstructive surgery in 2009 were three times more likely to have implant breast reconstructive surgery compared with similar patients in 2002. Medicare reimbursement steadily declined for AR over a similar time frame. From 1998 to 2008, autologous breast reconstruction has significantly declined, parallel to a decrease in physician reimbursement. Our data found no significant change in patient characteristics supporting the lack of choice of AR. Further research is warranted to better understand this shift to implant reconstruction and to ensure future access of these complex reconstructive procedures.

  View details for DOI 10.1111/tbj.12148

  View details for PubMedID 23758582

• No Difference in Mortality After Inter-Facility Transfer for Patients with Ruptured Abdominal Aortic Aneurysm Mell, M. W., Wang, N. E., Morrison, D. E., Hernandez-Boussard, T. MOSBY-ELSEVIER. 2013: 562–62

  View details for Web of Science ID 000322759500074

• Overlapping meta-analyses on the same topic: survey of published studies BMJ-BRITISH MEDICAL JOURNAL Siontis, K. C., Hernandez-Boussard, T., Ioannidis, J. P. 2013; 347

  Abstract

  To assess how common it is to have multiple overlapping meta-analyses of randomized trials published on the same topic.Survey of published meta-analyses.PubMed.Meta-analyses published in 2010 were identified, and 5% of them were randomly selected. We further selected those that included randomized trials and examined effectiveness of any medical intervention. For eligible meta-analyses, we searched for other meta-analyses on the same topic (covering the same comparisons, indications/settings, and outcomes or overlapping subsets of them) published until February 2013.Of 73 eligible meta-analyses published in 2010, 49 (67%) had at least one other overlapping meta-analysis (median two meta-analyses per topic, interquartile range 1-4, maximum 13). In 17 topics at least one author was involved in at least two of the overlapping meta-analyses. No characteristics of the index meta-analyses were associated with the potential for overlapping meta-analyses. Among pairs of overlapping meta-analyses in 20 randomly selected topics, 13 of the more recent meta-analyses did not include any additional outcomes. In three of the four topics with eight or more published meta-analyses, many meta-analyses examined only a subset of the eligible interventions or indications/settings covered by the index meta-analysis. Conversely, for statins in the prevention of atrial fibrillation after cardiac surgery, 11 meta-analyses were published with similar eligibility criteria for interventions and setting: there was still variability on which studies were included, but the results were always similar or even identical across meta-analyses.While some independent replication of meta-analyses by different teams is possibly useful, the overall picture suggests that there is a waste of efforts with many topics covered by multiple overlapping meta-analyses.

  View details for DOI 10.1136/bmj.f4501

  View details for Web of Science ID 000322247400002

  View details for PubMedID 23873947

  View details for PubMedCentralID PMC3716360

• Outcomes of Partial Mastectomy in Male Breast Cancer Patients: Analysis of SEER, 1983-2009 ANNALS OF SURGICAL ONCOLOGY Cloyd, J. M., Hernandez-Boussard, T., Wapnir, I. L. 2013; 20 (5): 1545-1550

  Abstract

  Although mastectomy is considered the gold standard for male breast cancer (MBC), the utilization of lumpectomy and its impact on outcomes in MBC patients has not been previously studied.The Surveillance, Epidemiology and End Results (SEER) database was used to identify all MBC patients who underwent either mastectomy or less than mastectomy (i.e., lumpectomy) between 1983 and 2009.A total of 4707 (86.8 %) men underwent mastectomy and 718 (13.2 %) underwent lumpectomy. A greater proportion of patients underwent lumpectomy later in the study period (1983 to 1986, 10.6 %, vs. 2007 to 2009, 15.1 %). A greater percentage of lumpectomy patients were 80 years or older (21.3 % vs. 16.3 %), had stage IV disease (7.3 % vs. 3.1 %), and received no lymph node sampling (34.3 % vs. 6.9 %). Only 35.4 % of patients underwent adjuvant radiotherapy after lumpectomy. Ten-year breast cancer-specific survival and overall survival were 82.8 % and 46.9 %, respectively, in lumpectomy patients vs. 77.3 % and 46.4 %, respectively, in mastectomy patients. On Cox proportional hazards regression, lumpectomy was not independently associated with worse breast cancer-specific survival (odds ratio 1.09, 95 % confidence interval 0.87-1.37) or overall survival (odds ratio 1.12, 95 % confidence interval 0.98-1.27) after controlling for age, race, stage, and grade, as well as whether radiotherapy was received.Lumpectomy is performed in a small but growing proportion of MBC patients. These patients are not only older and more likely to have advanced disease at the time of diagnosis, but they also are less likely to receive standard of care therapy, such as lymph node sampling and adjuvant radiotherapy. Despite these observations, breast cancer-specific survival is unaffected by the type of surgery.

  View details for DOI 10.1245/s10434-013-2918-5

  View details for PubMedID 23460016

• Poor compliance with breast cancer treatment guidelines in men undergoing breast-conserving surgery. Breast cancer research and treatment Cloyd, J. M., Hernandez-Boussard, T., Wapnir, I. L. 2013; 139 (1): 177-182

  Abstract

  Lumpectomy is performed in a small but growing proportion of men with breast cancer. It is unknown whether men undergoing breast-conserving surgery (BCS) receive care compliant with breast cancer treatment guidelines. Patients with breast cancer in the surveillance, epidemiology, and end results (SEER) database who underwent lumpectomy between 1983 and 2009 were identified. Gender differences in the receipt of lymph node staging and adjuvant radiation therapy were assessed. Multivariate logistic regression was utilized to evaluate the independent association of gender on these outcomes. The influence of gender on breast cancer-specific survival (BCSS) was analyzed. 382,030 of 824,408 (46.3 %) women compared to 712 of 6,039 (11.8 %) men with breast cancer underwent lumpectomy. Men were older, more likely to be black, less likely to have stage I disease and more likely to have stage IV disease. Only 59.2 % of men had lymph nodes sampled at the time of surgery compared to 81.6 % of women (p < 0.0001). In addition, only 35.4 % of men received adjuvant breast radiation therapy compared to 69.8 % of women (p < 0.0001). After controlling for age, race, stage, grade, and year of diagnosis, female gender was significantly associated with receiving adjuvant radiation therapy (OR 2.9, 95 % CI 2.4-3.4) and lymph node staging (OR 1.6, 95 % CI 1.3-1.90). Five- and ten-year BCSS were 88.0 and 83.5 % for men compared to 93.2 and 88.2 % for women (p < 0.001). Men with breast cancer are less likely to receive lymph node staging or adjuvant radiation therapy following BCS compared to women.

  View details for DOI 10.1007/s10549-013-2517-y

  View details for PubMedID 23572298

• Nonmelanoma Skin Cancer Visits and Procedure Patterns in a Nationally Representative Sample: National Ambulatory Medical Care Survey 1995-2007 DERMATOLOGIC SURGERY Wysong, A., Linos, E., Hernandez-Boussard, T., Arron, S. T., Gladstone, H., Tang, J. Y. 2013; 39 (4): 596-602

  Abstract

  The rising incidence of nonmelanoma skin cancer (NMSC) is well documented, but data are limited on the number of visits and treatment patterns of NMSC in the outpatient setting.To evaluate practice and treatment patterns of NMSC in the United States over the last decade and to characterize differences according to sex, age, race, insurance type, and physician specialty.Adults with an International Classification of Diseases, Ninth Revision, diagnosis of NMSC were included in this cross-sectional survey study of the National Ambulatory Medical Care Survey between 1995 and 2007. Primary outcomes included population-adjusted NMSC visit rates and odds ratios of receiving a procedure for NMSC using logistic regression.Rates of NMSC visits increased between 1995 and 2007. The number of visits was significantly higher in men, particularly those aged 65 and older. Fifty-nine percent of NMSC visits were associated with a procedure, and the individuals associated with that visit were more likely to be male, to be seen by a dermatologist, and to have private-pay insurance.Nonmelanoma skin cancer visit rates increased from 1995 to 2007 and were higher in men than women. Visits to a dermatologist are more likely to be associated with a procedure for NMSC, and there may be discrepancies in treatment patterns based on insurance type and sex.

  View details for DOI 10.1111/dsu.12092

  View details for Web of Science ID 000317018200010

  View details for PubMedID 23331766

• The Epidemiology of Idiopathic Acute Pancreatitis, Analysis of the Nationwide Inpatient Sample From 1998 to 2007 PANCREAS Chen, Y., Zak, Y., Hernandez-Boussard, T., Park, W., Visser, B. C. 2013; 42 (1): 1-5

  Abstract

  The study aimed to better define the epidemiology of idiopathic acute pancreatitis (IAP).We identified admissions with primary diagnosis of acute pancreatitis (AP) in Nationwide Inpatient Sample between 1998 and 2007. Idiopathic AP was defined as all cases after excluding International Classification of Diseases, Ninth Revision, codes for other causes of AP (including biliary, alcoholic, trauma, iatrogenic, hyperparathyroidism, hyperlipidemia, etc).Among the primary admissions for AP, 26.9% had biliary pancreatitis, 25.1% alcoholic, and 36.5% idiopathic. Idiopathic AP had estimated 81,8025 admissions with a mean hospitalization of 5.6 days. Patients with IAP accounted for almost half of the fatalities among the cases of AP (48.2%) and had a higher mortality rate than both patients with biliary pancreatitis and patients with alcoholic pancreatitis (1.9%, 1.5%, and 1.0%, respectively, P < 0.01). Forty-six percent of patients with biliary pancreatitis underwent cholecystectomy during the index hospitalization, compared with 0.42% of patients with IAP. Patients with IAP had a demographic distribution similar to that of patients with biliary AP (female predominant and older), which was distinct from patients with alcoholic pancreatitis (male predominant and younger). There was a gradual but steady decrease in the incidence of IAP, from 41% in 1998 to 30% in 2007.Despite improving diagnostics, IAP remains a common clinical problem with a significant mortality. Standardization of the clinical management of these patients warrants further investigation.

  View details for DOI 10.1097/MPA.0b013e3182572d3a

  View details for PubMedID 22750972

• Overlapping meta-analyses on the same topic: survey of published studies. BMJ (Clinical research ed.) Siontis, K. C., Hernandez-Boussard, T., Ioannidis, J. P. 2013; 347: f4501-?

  Abstract

  To assess how common it is to have multiple overlapping meta-analyses of randomized trials published on the same topic.Survey of published meta-analyses.PubMed.Meta-analyses published in 2010 were identified, and 5% of them were randomly selected. We further selected those that included randomized trials and examined effectiveness of any medical intervention. For eligible meta-analyses, we searched for other meta-analyses on the same topic (covering the same comparisons, indications/settings, and outcomes or overlapping subsets of them) published until February 2013.Of 73 eligible meta-analyses published in 2010, 49 (67%) had at least one other overlapping meta-analysis (median two meta-analyses per topic, interquartile range 1-4, maximum 13). In 17 topics at least one author was involved in at least two of the overlapping meta-analyses. No characteristics of the index meta-analyses were associated with the potential for overlapping meta-analyses. Among pairs of overlapping meta-analyses in 20 randomly selected topics, 13 of the more recent meta-analyses did not include any additional outcomes. In three of the four topics with eight or more published meta-analyses, many meta-analyses examined only a subset of the eligible interventions or indications/settings covered by the index meta-analysis. Conversely, for statins in the prevention of atrial fibrillation after cardiac surgery, 11 meta-analyses were published with similar eligibility criteria for interventions and setting: there was still variability on which studies were included, but the results were always similar or even identical across meta-analyses.While some independent replication of meta-analyses by different teams is possibly useful, the overall picture suggests that there is a waste of efforts with many topics covered by multiple overlapping meta-analyses.

  View details for DOI 10.1136/bmj.f4501

  View details for PubMedID 23873947

• Differences in readmissions after open repair versus endovascular aneurysm repair 26th Annual Meeting of the Western-Vascular-Society Casey, K., Hernandez-Boussard, T., Mell, M. W., Lee, J. T. MOSBY-ELSEVIER. 2013: 89–95

  Abstract

  Reintervention rates after repair of abdominal aortic aneurysm (AAA) are higher for endovascular repair (EVAR) than for open repair, mostly due to treatment for endoleaks, whereas open surgical operations for bowel obstruction and abdominal hernias are higher after open repair. However, readmission rates after EVAR or open repair for nonoperative conditions and complications that do not require an intervention are not well documented. We sought to determine reasons for all-cause readmissions within the first year after open repair and EVAR.Patients who underwent elective AAA repair in California during a 6-year period were identified from the Health Care and Utilization Project State Inpatient Database. All patients who had a readmission in California ≤1 year of their index procedure were included for evaluation. Readmission rates and primary and secondary diagnoses associated with each readmission were analyzed and recorded.From 2003 to 2008, there were 15,736 operations for elective AAA repair, comprising 9356 EVARs (60%) and 6380 open repairs (40%). At 1 year postoperatively, the readmission rate was 52.1% after open repair and 55.4% after EVAR (P=.0003). The three most common principle diagnoses associated with readmission after any type of AAA repair were failure to thrive, cardiac issues, and infection. When stratified by repair type, patients who underwent open repair were more likely to be readmitted with primary diagnoses associated with failure to thrive, cardiac complications, and infection compared with EVAR (all P<.001). Those who underwent EVAR were more likely, however, to be readmitted with primary diagnoses of device-related complications (P=.05), cardiac complications, and infection.Total readmission rates within 1 year after elective AAA repair are greater after EVAR than after open repair. Reasons for readmission vary between the two cohorts but are related to the magnitude of open surgery after open repair, device issues after EVAR, and the usual cardiac and infectious complications after either intervention. Systems-based analysis of these causes of readmission can potentially improve patient expectations and care after elective aneurysm repair.

  View details for DOI 10.1016/j.jvs.2012.07.005

  View details for Web of Science ID 000312833800016

  View details for PubMedID 23164606

• Normal Alcohol Metabolism after Gastric Banding and Sleeve Gastrectomy: A Case-Cross-Over Trial JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS Changchien, E. M., Woodard, G. A., Hernandez-Boussard, T., Morton, J. M. 2012; 215 (4): 475-479

  Abstract

  Severe obesity remains the leading public health concern of the industrialized world, with bariatric surgery as the only current effective enduring treatment. In addition to gastric bypass, gastric banding and sleeve gastrectomy have emerged as viable treatment options for the severely obese. Occasionally, poor postoperative psychological adjustment has been reported. It has been previously demonstrated that breath alcohol content (BAC) levels and time to sober were increased in postoperative gastric bypass patients. The aim of this study was to examine whether alcohol metabolism in patients undergoing restrictive-type bariatric procedures is also altered.Nine patients undergoing laparoscopic adjustable gastric banding (LAGB) and 7 patients undergoing laparoscopic sleeve gastrectomy (LSG) were recruited. Preoperatively, 3-month and 6-month BAC and time to sober were measured after administration of 5 ounces of red wine. In addition, participants were asked to complete a questionnaire of drinking habits.The 16 total participants achieved a mean 44.7% 6-month excess weight loss. There were no significant changes in peak BAC or time to sober from preoperative levels (0.033%, 67.8 min, respectively) to 3 months (0.032%, 77.1 min, respectively, p = 0.421) or 6 months (0.035%, 81.2 min, respectively, p = 0.198).Patients undergoing LAGB and LSG do not share the same altered alcohol metabolism as seen in gastric bypass patients. However, all bariatric surgery patients should be counseled regarding alcohol use.

  View details for DOI 10.1016/j.jamcollsurg.2012.06.008

  View details for Web of Science ID 000308910300003

  View details for PubMedID 22770864

• Pathologic Response to Preoperative Chemotherapy in Colorectal Liver Metastases: Fibrosis, not Necrosis, Predicts Outcome ANNALS OF SURGICAL ONCOLOGY Poultsides, G. A., Bao, F., Servais, E. L., Hernandez-Boussard, T., DeMatteo, R. P., Allen, P. J., Fong, Y., Kemeny, N. E., Saltz, L. B., Klimstra, D. S., Jarnagin, W. R., Shia, J., D'Angelica, M. I. 2012; 19 (9): 2797-2804

  Abstract

  Pathologic response to preoperative chemotherapy for colorectal liver metastases (CLM) is associated with survival after hepatectomy. Histologically, dominant response patterns include fibrosis, necrosis and/or acellular mucin, but some of these changes can appear without previous chemotherapy and their individual correlation with outcome is unknown.Pathology slides from patients who underwent CLM resection (irrespective of preoperative chemotherapy status) were rereviewed by a blinded pathologist. Pathologic response was recorded as the summation of percentage necrosis, fibrosis and acellular mucin. Associations between pathologic response, its components, preoperative chemotherapy, and survival were analyzed.Pathology slides were rereviewed in 366 patients undergoing CLM resection from 2003 to 2007. Preoperative chemotherapy was administered in 249 (68 %) patients, who, when compared to no preoperative chemotherapy patients, had higher rates of overall pathologic response (57 vs. 46 %, P < .01), fibrosis (21 vs. 12 %, P < .01) and acellular mucin (6 vs. 3 %, P = .05) but similar rates of necrosis (30 vs. 31 %, P = .30). In patients receiving preoperative chemotherapy, overall pathologic response ≥ 75 % (5 year, 83 vs. 47 %, P < .01) and fibrosis ≥ 40 % (5 year, 87 vs. 51 %, P < .01) independently correlated with disease-specific survival after hepatectomy. Preoperative hepatic artery infusion chemotherapy (P = .04) and bevacizumab (P = .05) were marginally associated with overall pathologic response and fibrosis, respectively.Fibrosis is the predominant chemotherapy-related pathologic alteration driving the association of treatment response with survival after CLM resection. Necrosis in CLM is not related to chemotherapy or outcome.

  View details for DOI 10.1245/s10434-012-2335-1

  View details for Web of Science ID 000308357100005

  View details for PubMedID 22476753

• Predictors of emergency department death for patients presenting with ruptured abdominal aortic aneurysms JOURNAL OF VASCULAR SURGERY Mell, M. W., Callcut, R. A., Bech, F., Delgado, M. K., Staudenmayer, K., Spain, D. A., Hernandez-Boussard, T. 2012; 56 (3): 651-655

  Abstract

  Ruptured abdominal aortic aneurysm (rAAA) is a critically time-sensitive condition with outcomes dependent on rapid diagnosis and definitive treatment. Emergency department (ED) death reflects the hemodynamic stability of the patient upon arrival and the ability to mobilize resources before hemodynamic stability is lost. The goals of this study were to determine the incidence and predictors of ED death for patients presenting to EDs with rAAAs.Data for patients presenting with International Classification of Disease, 9th Revision, Clinical Modification codes for rAAA from 2006 to 2008 were extracted from discharge data using the Nationwide Emergency Department Sample (NEDS), Healthcare Cost and Utilization Project, and Agency for Healthcare Research and Quality. The NEDS is the largest stratified weighted sample of US hospital-based ED visits with links to inpatient files. We compared those transferred to those admitted and treated. Sample weights were applied to produce nationally representative estimates. Patient and hospital factors associated with transfer were identified using multivariate logistic regression. These factors were then analyzed for a relationship with ED deaths.A total of 18,363 patients were evaluated for rAAAs. Of these, 7% (1201) died in the ED, 6% (1160) were admitted and died without a procedure, 42% (7731) were admitted and died after repair, and 41% (7479) were admitted, treated, and survived. Transfers accounted for 4% (793) of all ED visits for rAAAs. ED death was more likely for patients seen in nonmetropolitan hospitals (12.7%) vs metropolitan nonteaching (7.0%) or metropolitan teaching hospitals (4.5%; P < .0001). Compared with other regions, the West had a higher ED mortality rate (9.6% vs 5.1%-6.9%; P = .0038). On multivariate analysis, ED death was associated with hospital groups exhibiting both high and low transfer rates.ED death remains a significant cause for mortality for rAAAs and varies by hospital type, rural/urban location, and geographic region. Both delays in ED arrival and delays in providing definitive care may contribute to increased ED death rates, suggesting that improved regional systems of care may improve survival after rAAA.

  View details for DOI 10.1016/j.jvs.2012.02.025

  View details for Web of Science ID 000308085500010

  View details for PubMedID 22560234

• Obesity Disparities in Preventive Care: Findings From the National Ambulatory Medical Care Survey, 2005-2007 OBESITY Hernandez-Boussard, T., Ahmed, S. M., Morton, J. M. 2012; 20 (8): 1639-1644

  Abstract

  Obesity and its consequences are a major health concern. There are conflicting reports regarding utilization of preventive health-care services among obese patients. Our objective was to determine whether obese patients receive the same preventive care as normal weight patients. Weighted patient clinic visit data from the National Ambulatory Medical Care Survey (NAMCS) were analyzed for all adult patient visits with height/weight data (N = 866,415,856) from 2005 to 2007. Preventive care practice patterns were compared among different weight groups of normal, obese, and morbidly obese. Obese patients received the least number of preventive exams with a clear gradient present by weight. Obese patients were significantly less likely to receive cancer screening including breast examination (normal weight, reference, obese, odds ratio (OR), 0.8), mammogram (obese OR, 0.7), pap smear (obese OR, 0.7), pelvic exam (obese OR, 0.8), and rectal exam (obese OR, 0.7). The obese population also received less tobacco (obese OR, 0.7) and injury prevention education (obese OR, 0.7), yet significantly more diet, exercise, and weight reduction education. Significant differences in clinic practice patterns relative to normal weight patients were also evident with more physician referral (obese OR, 1.2) and less likely to see physician at the index clinic visit (obese OR, 0.8) and less likely to receive psychotherapy referral (obese OR, 0.6). Significant gaps in preventive care exist for the obese including cancer screening, tobacco cessation and injury prevention counseling, and psychological referral. Although obese patients received more weight-related education, this emphasis may have the consequence of de-emphasizing other needed preventive health measures.

  View details for DOI 10.1038/oby.2011.258

  View details for Web of Science ID 000306920900013

  View details for PubMedID 21818146

• Long-term results after accessory renal artery coverage during endovascular aortic aneurysm repair 26th Annual Meeting of the Western-Vascular-Society Greenberg, J. I., Dorsey, C., Dalman, R. L., Lee, J. T., Harris, E. J., Hernandez-Boussard, T., Mell, M. W. MOSBY-ELSEVIER. 2012: 291–97

  Abstract

  Current information regarding coverage of accessory renal arteries (ARAs) during endovascular aneurysm repair (EVAR) is based on small case series with limited follow-up. This study evaluates the outcomes of ARA coverage in a large contemporary cohort.Consecutive EVAR data from January 2004 to August 2010 were collected in a prospective database at a University Hospital. Patient and aneurysm-related characteristics, imaging studies, and ARA coverage versus preservation were analyzed. Volumetric analysis of three-dimensional reconstruction computed tomography scans was used to assess renal infarction volume extent. Long-term renal function and overall technical success of aneurysm exclusion were compared.A cohort of 426 EVARs was identified. ARAs were present in 69 patients with a mean follow-up of 27 months (range, 1 to 60 months). Forty-five ARAs were covered in 40 patients; 29 patients had intentional ARA preservation. Patient and anatomic characteristics were similar between groups except that ARA coverage patients had shorter aneurysm necks (P = .03). Renal infarctions occurred in 84% of kidneys with covered ARAs. There was no significant deterioration in long-term glomerular filtration rate when compared with patients in the control group. No difference in the rate of endoleak, secondary procedures, or the requirement for antihypertensive medications was found.This study is the largest to date with the longest follow-up relating to ARA coverage. Contrary to previous reports, renal infarction after ARA coverage is common. Nevertheless, coverage is well tolerated based upon preservation of renal function without additional morbidity. These results support the long-term safety of ARA coverage for EVAR when necessary.

  View details for DOI 10.1016/j.jvs.2012.01.049

  View details for PubMedID 22480767

• Laparoscopic vs Open Gastric Bypass Surgery Differences in Patient Demographics, Safety, and Outcomes ARCHIVES OF SURGERY Banka, G., Woodard, G., Hernandez-Boussard, T., Morton, J. M. 2012; 147 (6): 550-556

  Abstract

  To determine national outcome differences between laparoscopic Roux-en-Y gastric bypass (LRYGB) and open Roux-en-Y gastric bypass (ORYGB).Retrospective cohort study.The Nationwide Inpatient Sample.Patients undergoing ORYGB and LRYGB.Outcome measures were number of procedures performed, patient and hospital characteristics, patient complications, mortality, length of stay, resource use, and Agency for Healthcare Research and Quality Patient Safety Indicators. Both demographic and outcomes variables were compared by either t test or χ2 analysis, with regression analysis adjusting for confounding variables.The ORYGB and LRYGB cohorts consisted of 41 094 and 115 177 cases, respectively. From 2005 to 2007, LRYGB was more commonly performed than ORYGB (72% vs 28%; P < .001) and at high-volume hospitals (69% vs 61%; P < .001). A higher percentage of ORYGB compared with LRYGB patients were Medicare (9.3% vs 7.1%) and Medicaid (10.4% vs 5.9%; P < .01) beneficiaries. More ORYGB patients compared with LRYGB patients were discharged with nonroutine dispositions (7.7% vs 2.4%; P = .005), died (0.2% vs 0.1%; P < .001), and had 1 or more complications (18.7% vs 12.3%; P < .001). All Patient Safety Indicator rates were higher for ORYGB. Patients who had ORYGB compared with LRYGB also had longer median lengths of stay (3.5 vs 2.4 days; P < .001) and higher total charges ($35 018 vs $32 671; P < .001). Patients who had LRYGB had a lower odds ratio than patients who had ORYGB for both mortality (odds ratio, 0.54; P < .001) and having 1 or more complications (odds ratio, 0.66; P < .001) even after adjusting for confounding variables.In this population-based study, LRYGB provided greater safety than ORYGB even after adjusting for patient-level socioeconomic and comorbidity differences.

  View details for Web of Science ID 000305428500014

  View details for PubMedID 22786543

• Effect of Roux-en-Y gastric bypass on testosterone and prostate-specific antigen BRITISH JOURNAL OF SURGERY Woodard, G., Ahmed, S., Podelski, V., Hernandez-Boussard, T., Presti, J., Morton, J. M. 2012; 99 (5): 693-698

  Abstract

  Obese men have lower serum levels of testosterone, dehydroepiandrosterone (DHEA) and prostate-specific antigen (PSA), but an increased risk of dying from prostate cancer. The aim of this study was to examine the effect of surgically induced weight loss on serum testosterone, DHEA and PSA levels in obese men.Consecutive men undergoing Roux-en-Y gastric bypass (RYGB) participated in a prospective, longitudinal study. Main outcomes were changes were body mass index (BMI), percentage excess weight loss, serum levels of testosterone, DHEA and PSA, PSA mass and plasma volume, measured before operation and 3, 6 and 12 months later.In 64 patients, mean BMI fell from 48.2 kg/m(2) before operation to 39.2, 35.6 and 32.4 kg/m(2) at 3, 6 and 12 months after RYGB. Testosterone levels rose significantly from 259 ng/dl to 386, 452 and 520 ng/dl respectively. Serum PSA levels increased significantly from 0.51 ng/ml to 0.67 ng/ml at 12 months. There were no significant changes in DHEA or PSA mass.RYGB normalizes the serum testosterone level. PSA levels increase with weight loss and may be inversely correlated with changes in plasma volume, indicating that PSA levels may be artificially low in obese men owing to haemodilution.

  View details for DOI 10.1002/bjs.8693

  View details for Web of Science ID 000303150700016

  View details for PubMedID 22302466

• Determinants of Adverse Events in Vascular Surgery JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS Hernandez-Boussard, T., McDonald, K. M., Morton, J. M., Dalman, R. L., Bech, F. R. 2012; 214 (5): 788-797

  Abstract

  Patient safety is a national priority. Patient Safety Indicators (PSIs) monitor potential adverse events during hospital stays. Surgical specialty PSI benchmarks do not exist, and are needed to account for differences in the range of procedures performed, reasons for the procedure, and differences in patient characteristics. A comprehensive profile of adverse events in vascular surgery was created.The Nationwide Inpatient Sample was queried for 8 vascular procedures using ICD-9-CM codes from 2005 to 2009. Factors associated with PSI development were evaluated in univariate and multivariate analyses.A total of 1,412,703 patients underwent a vascular procedure and a PSI developed in 5.2%. PSIs were more frequent in female, nonwhite patients with public payers (p < 0.01). Patients at mid and low-volume hospitals had greater odds of developing a PSI (odds ratio [OR] = 1.17; 95% CI, 1.10-1.23 and OR = 1.69; 95% CI, 1.53-1.87). Amputations had highest PSI risk-adjusted rate and carotid endarterectomy and endovascular abdominal aortic aneurysm repair had lower risk-adjusted rate (p < 0.0001). PSI risk-adjusted rate increased linearly by severity of patient indication: claudicants (OR = 0.40; 95% CI, 0.35-0.46), rest pain patients (OR = 0.78; 95% CI, 0.69-0.90), ulcer (OR = 1.20; 95% CI, 1.07-1.34), and gangrene patients (OR = 1.85; 95% CI, 1.66-2.06).Patient safety events in vascular surgery were high and varied by procedure, with amputations and open abdominal aortic aneurysm repair having considerably more potential adverse events. PSIs were associated with black race, public payer, and procedure indication. It is important to note the overall higher rates of PSIs occurring in vascular patients and to adjust benchmarks for this surgical specialty appropriately.

  View details for DOI 10.1016/j.jamcollsurg.2012.01.045

  View details for Web of Science ID 000303724200009

  View details for PubMedID 22425449

• Relationship between Patient Safety and Hospital Surgical Volume HEALTH SERVICES RESEARCH Hernandez-Boussard, T., Downey, J. R., McDonald, K., Morton, J. M. 2012; 47 (2): 756-769

  Abstract

  To examine the relationship between hospital volume and in-hospital adverse events.Patient safety indicator (PSI) was used to identify hospital-acquired adverse events in the Nationwide Inpatient Sample database in abdominal aortic aneurysm, coronary artery bypass graft, and Roux-en-Y gastric bypass from 2005 to 2008.In this observational study, volume thresholds were defined by mean year-specific terciles. PSI risk-adjusted rates were analyzed by volume tercile for each procedure.Overall, hospital volume was inversely related to preventable adverse events. High-volume hospitals had significantly lower risk-adjusted PSI rates compared to lower volume hospitals (p < .05).These data support the relationship between hospital volume and quality health care delivery in select surgical cases. This study highlights differences between hospital volume and risk-adjusted PSI rates for three common surgical procedures and highlights areas of focus for future studies to identify pathways to reduce hospital-acquired events.

  View details for DOI 10.1111/j.1475-6773.2011.01310.x

  View details for Web of Science ID 000301229300012

  View details for PubMedID 22091561

• "Phantom" Publications Among Plastic Surgery Residency Applicants ANNALS OF PLASTIC SURGERY Chung, C. K., Hernandez-Boussard, T., Lee, G. K. 2012; 68 (4): 391-395

  Abstract

  Previous studies in other medical specialties have shown a significant percentage of publications represented in residency applications are not actually published. A comprehensive evaluation of applicants to plastic surgery residency over an extended period has not been previously reported in the literature. The purpose of our study was to determine the incidence of misrepresented or "phantom" publications in plastic surgery residency applicants and to identify possible predisposing characteristics.We used the Electronic Residency Application Services database to our plastic surgery residency program during a 4-year period from 2006 to 2009. Applicant demographic information and listed citations were extracted. Peer-reviewed journal article citations were verified using robust methods including PubMed, Institute for Scientific Information (ISI) Web of Knowledge, and Google. Unverifiable articles were categorized as phantom publications and then evaluated with respect to applicant demographic information and characteristics.During the 4-year study period, there were 804 applications (average, 201 applicants per year). There was a total of 4725 publications listed; of which, 1975 had been categorized as peer-reviewed journal articles. Two hundred seventy-six (14%) of peer-reviewed publications could not be verified and were categorized as phantom publications. There was an overall significant positive trend in percentage of phantom publications during the 4 application years (P = 0.005). A positive predictive factor for having phantom publications was being a foreign medical graduate (P = 0.02). A negative predictive factor for phantom publications was being a female applicant (P = 0.03). There also appeared to be a positive correlation with the number of publications listed and likelihood of phantom publications.Among plastic surgery residency applicants, we found a significant percentage of unverifiable publications. There are several possible explanations for our findings, which include the fact that plastic surgery is a highly sought-after specialty and applicants may feel the need to appear competitive to residency programs. Publications are an important aspect of the residency selection process and factors into applicant ranking, but our study suggests publications listed in plastic surgery residency applications may not necessarily be an accurate representation of actual published articles. Program directors and faculty are advised to scrutinize listed publications carefully when evaluating applicants.

  View details for DOI 10.1097/SAP.0b013e31823d2c4e

  View details for Web of Science ID 000301800600015

  View details for PubMedID 22421486

• The aching surgeon: a survey of physical discomfort and symptoms following open, laparoscopic, and robotic surgery. Journal of robotic surgery Plerhoples, T. A., Hernandez-Boussard, T., Wren, S. M. 2012; 6 (1): 65-72

  Abstract

  There is increasing interest in understanding the toll that operating takes on a surgeon's body. The effect of robotic surgery on surgeon discomfort has not been studied. We sought to document the discomfort of robotic surgery compared with open and laparoscopic surgery and to investigate the factors that affect the risk of physical symptoms. Nineteen-thousand eight-hundred and sixty-eight surgeons from all specialties trained in the use of robots were sent a 26-question online survey and 1,407 responded. One-thousand two-hundred and fifteen surgeons who practiced all three approaches were used in the analysis. Eight-hundred and seventy-one surgeons had physical discomfort or symptoms attributable to operating. Of those with symptoms, 55.4% attributed most of the symptoms to laparoscopic surgery, 36.3% to open surgery, and 8.3% to robotic surgery. A higher case load was predictive of increased symptoms for open and laparoscopic surgery, but not for robotic surgery. Robotic surgery was less likely than open or laparoscopic surgery to lead to neck, back, hip, knee, ankle, foot, and shoulder pain and less likely than laparoscopic surgery to lead to elbow and wrist pain. Robotic surgery was more likely than either open or laparoscopic surgery to lead to eye pain, and more likely than open surgery to lead to finger pain. Nearly a third (30.3%) of surgeons admit to giving consideration to their own discomfort when choosing an operative modality. Robotic surgery has promise in reducing the risk of physical discomfort for the operator. This is important as more surgeons consider their own health when choosing a surgical modality.

  View details for DOI 10.1007/s11701-011-0330-3

  View details for PubMedID 27637981

• Is Patient Safety Improving? National Trends in Patient Safety Indicators: 1998-2007 HEALTH SERVICES RESEARCH Downey, J. R., Hernandez-Boussard, T., Banka, G., Morton, J. M. 2012; 47 (1): 414-430

  Abstract

  Emphasis has been placed on quality and patient safety in medicine; however, little is known about whether quality over time has actually improved in areas such as patient safety indicators (PSIs).To determine whether national trends for hospital PSIs have improved from 1998 to 2007.Using PSI criteria from the Agency for Healthcare Research and Quality, PSIs were identified in the Nationwide Inpatient Sample (NIS) for all eligible inpatient admissions between 1998 and 2007. Joinpoint regression was used to estimate annual percentage changes (APCs) for PSIs.Annual percent change for PSIs.From 1998 to 2007, 7.6 million PSI events occurred for over 69 million hospitalizations. A total of 14 PSIs showed statistically significant trends. Seven PSIs had increasing APC: postoperative pulmonary embolism or deep vein thrombosis (8.94), postoperative physiological or metabolic derangement (7.67), postoperative sepsis (7.17), selected infections due to medical care (4.05), decubitus ulcer (3.05), accidental puncture or laceration (2.64), and postoperative respiratory failure (1.46). Seven PSIs showed decreasing APCs: birth trauma injury to neonate (-17.79), failure to rescue (-6.05), postoperative hip fracture (-5.86), obstetric trauma-vaginal without instrument (-5.69), obstetric trauma-vaginal with instrument (-4.11), iatrogenic pneumothorax (-2.5), and postoperative wound dehiscence (-1.8).This is the first study to establish national trends of PSIs during the past decade indicating areas for potential quality improvement prioritization. While many factors influence these trends, the results indicate opportunities for either emulation or elimination of current patient safety trends.

  View details for DOI 10.1111/j.1475-6773.2011.01361.x

  View details for Web of Science ID 000299041600007

  View details for PubMedID 22150789

• Halo Effect for Bariatric Surgery: Collateral Weight Loss in Patients' Family Members (vol 146, pg 1185, 2011) ARCHIVES OF SURGERY Woodard, G. A., Encarnacion, B., Peraza, J., Hernandez-Boussard, T., Morton, J. 2011; 146 (12): 1410-1410

  View details for Web of Science ID 000298256900020

• Another Use of the Mobile Device: Warm-up for Laparoscopic Surgery JOURNAL OF SURGICAL RESEARCH Plerhoples, T. A., Zak, Y., Hernandez-Boussard, T., Lau, J. 2011; 170 (2): 185-188

  Abstract

  An important facet of laparoscopic surgery is its psychomotor component. As this aspect of surgery gains attention, lessons from other psychomotor-intense fields such as athletics have led to an investigation of the benefits of "warming up" prior to entering the operating room. Practical implementation of established methods of warm-up is hampered by a reliance on special equipment and instrumentations that are not readily available. In light of emerging evidence of translatability between video-game play and operative performance, we sought to find if laparoscopic task performance improved after warming up on a mobile device balance game.Laparoscopic novices were randomized into either the intervention group (n = 20) or the control group (n = 20). The intervention group played a mobile device balance game for 10 min while the control group did no warm-up whatsoever. Assessment was performed using two tasks on the ProMIS laparoscopic simulation system: "object positioning" (where small beads are transferred between four cups) and "tissue manipulation" (where pieces of plastic are stretched over pegs). Metrics measured were time to task completion, path length, smoothness, hand dominance, and errors.The intervention group made fewer errors: object positioning task 0.20 versus 0.70, P = 0.01, tissue manipulation task 0.15 versus 0.55, P = 0.05, total errors 0.35 versus 1.25, P = 0.002. The two groups performed similarly on the other metrics.Warm-up using a mobile device balance game decreases errors on basic tasks performed on a laparoscopic surgery simulator, suggesting a practical way to warm-up prior to cases in the operating room.

  View details for DOI 10.1016/j.jss.2011.03.015

  View details for Web of Science ID 000295128600013

  View details for PubMedID 21529831

• Halo Effect for Bariatric Surgery Collateral Weight Loss in Patients' Family Members ARCHIVES OF SURGERY Woodard, G. A., Encarnacion, B., Peraza, J., Hernandez-Boussard, T., Morton, J. 2011; 146 (10): 1185-1190

  Abstract

  Bariatric surgery is an effective treatment for morbid obesity, which is increasingly recognized as a familial disease. Healthy behavior transmission may be enhanced by family relationships.To determine changes in weight and healthy behavior in patients who underwent Roux-en-Y gastric bypass surgery and their family members.Prospective, longitudinal, and multidimensional health assessment before and 1 year after index Roux-en-Y gastric bypass surgery.An academic bariatric center of excellence, from January 1, 2007, through December 31, 2009.Eighty-five participants (35 patients, 35 adult family members, and 15 children <18 years old).Roux-en-Y gastric bypass surgery and associated dietary and lifestyle counseling.Weight and expected body mass index (calculated as weight in kilograms divided by height in meters squared). Secondary outcomes were waist circumference, quality of life (36-Item Short Form or Pediatric Quality of Life Inventory), healthy behaviors, eating behaviors, and activity levels.Participants were grouped by relationship to patient for analysis with paired 2-sample t tests. Before the operation, 60% of adult family members and 73% of children of patients undergoing Roux-en-Y gastric bypass surgery were obese. At 12 months after the operation, significant weight loss was observed in obese adult family members (from 234 to 226 lb; P = .01). There was a trend for obese children to have a lower body mass index than expected for their growth curve (31.2 expected vs 29.6 observed; P = .07). Family members increased their daily activity levels (adults, from 8 to 17 metabolic equivalent task-hours, P = .005; and children, from 13 to 22, P = .04). Adult family members also had improved eating habits with less uncontrollable eating (from 35 to 28; P = .01), emotional eating (from 36 to 28; P = .04), and alcohol consumption (from 11 drinks per month to 1 drink per month; P = .009).Gastric bypass surgery may render an additional benefit of weight loss and improved healthy behavior for bariatric patients' family members.

  View details for Web of Science ID 000295942300018

  View details for PubMedID 22006878

• Readmissions after Abdominal Aortic Aneurysm Repair: Differences between Open Repair and Endovascular Aneurysm Repair Casey, K. M., Hernandez-Boussard, T., Al-Khatib, W. K., Mell, M. W., Lee, J. T. MOSBY-ELSEVIER. 2011: 590–90

  View details for Web of Science ID 000293814400073

• Under-Utilization of Transfer for Ruptured Abdominal Aortic Aneurysm (rAAA) in the Western United States Mell, M. W., Callcut, R. A., Bech, F., Delgado, K., Staudenmayer, K., Spain, D. A., Hernandez-Boussard, T. MOSBY-ELSEVIER. 2011: 590–91

  View details for Web of Science ID 000293814400076

• Doxorubicin pathways: pharmacodynamics and adverse effects PHARMACOGENETICS AND GENOMICS Thorn, C. F., Oshiro, C., Marsh, S., Hernandez-Boussard, T., McLeod, H., Klein, T. E., Altman, R. B. 2011; 21 (7): 440-446

  View details for DOI 10.1097/FPC.0b013e32833ffb56

  View details for Web of Science ID 000291633300011

  View details for PubMedID 21048526

  View details for PubMedCentralID PMC3116111

• B-type natriuretic peptide increases after gastric bypass surgery and correlates with weight loss 12th World Congress of Endoscopic Surgery (WCES) Changchien, E. M., Ahmed, S., Betti, F., Higa, J., Kiely, K., Hernandez-Boussard, T., Morton, J. SPRINGER. 2011: 2338–43

  Abstract

  Coronary artery disease is the primary cause of death in the United States, with obesity as a leading preventable risk factor. Previous studies have established the beneficial effect of Roux-en-Y gastric bypass on both weight and cardiac risk factors. Further assessment of cardiac function may be accomplished using B-type natriuretic peptide (BNP), which has demonstrated clinical utility in diagnosing congestive heart failure. This study aimed to assess changes in BNP after intentional weight loss through gastric bypass surgery.Plasma volume, weight, and BNP were measured preoperatively and at 3, 6, and 12 months postoperatively for 101 consecutive patients undergoing laparoscopic gastric bypass surgery by a single surgeon in an academic medical setting. Outcomes were compared by matched t-test. Multivariable linear regression and Pearson's correlation were used to examine predictors of pro-B-type natriuretic peptide (NT-proBNP) concentration.The concentration of BNP increased significantly from a mean preoperative level of 50.5 ng/l to postoperative levels of 73.9 ng/l at 3 months (P=0.013), 74.3 ng/l at 6 months (P<0.001), and 156.3 ng/l at 12 months (P<0.001). In addition, excess weight loss was the only statistically significant predictor of increased BNP concentration (odds ratio, 1.483; P<0.05).Gastric bypass leads to significant excess weight loss and surprisingly increased BNP concentrations. Correlation of BNP increase with weight loss suggests an additional novel mechanism for surgically induced weight loss.

  View details for DOI 10.1007/s00464-010-1565-1

  View details for Web of Science ID 000291690100039

  View details for PubMedID 21424205

• Surgery for Thoracic Outlet Syndrome: A Nationwide Perspective Vascular Annual Meeting of the Society-for-Vascular-Surgery Lee, J. T., Dua, M. M., Chandra, V., Hernandez-Boussard, T. M., Illig, K. A. MOSBY-ELSEVIER. 2011: 100S–101S

  View details for Web of Science ID 000291410700194

• Adverse events following digital replantation in the elderly. journal of hand surgery Barzin, A., Hernandez-Boussard, T., Lee, G. K., Curtin, C. 2011; 36 (5): 870-874

  Abstract

  The decision to proceed with digital replantation in the elderly can be challenging. In addition to success of the replanted part, perioperative morbidity and mortality must be considered. The purpose of this study was to compare adverse events in patients less than 65 years of age compared with those 65 years and older after digital replantation. We hypothesize that there is an increased incidence of mortality and sentinel adverse events in patients aged 65 and older.We obtained data from the Nationwide Inpatient Sample over a 10-year period from 1998 to 2007. Replantation was identified using International Classification of Diseases-9 procedure codes for finger and thumb reattachment (84.21 and 84.22). Adverse events were identified using Patient Safety Indicators (PSI) to identify adverse events occurring during hospitalization. We used the Charlson index to study medical comorbidities and bivariate statistics.During the study period 15,413 finger and thumb replantations were performed in the United States, with 616 performed on patients age 65 and older. The overall in-hospital mortality was 0.04% with no statistical difference when factoring age. For the entire group, the percentage of PSI was 0.6%, the most common being postoperative deep venous thrombosis and pulmonary embolus. Overall, there was no difference in PSI between the 2 groups. The older group had a higher rate of transfusion, 4% versus 8% (p < .05) and were more likely to have a nonroutine disposition (ie, nursing home) (p < .001). We found no correlation between the Charlson index and PSI.This study found no difference in sentinel perioperative complications or mortality when comparing replantation patients under 65 years of age and those age 65 and older. Age alone should not be an absolute contraindication to finger replantation. Instead, the patient's functional demands, type of injury, general state of health, and rehabilitative potential should drive the decision of whether to proceed with replantation.

  View details for DOI 10.1016/j.jhsa.2011.01.031

  View details for PubMedID 21489718

• Adverse Events Following Digital Replantation in the Elderly JOURNAL OF HAND SURGERY-AMERICAN VOLUME Barzin, A., Hernandez-Boussard, T., Lee, G. K., Curtin, C. 2011; 36A (5): 870-874

  Abstract

  The decision to proceed with digital replantation in the elderly can be challenging. In addition to success of the replanted part, perioperative morbidity and mortality must be considered. The purpose of this study was to compare adverse events in patients less than 65 years of age compared with those 65 years and older after digital replantation. We hypothesize that there is an increased incidence of mortality and sentinel adverse events in patients aged 65 and older.We obtained data from the Nationwide Inpatient Sample over a 10-year period from 1998 to 2007. Replantation was identified using International Classification of Diseases-9 procedure codes for finger and thumb reattachment (84.21 and 84.22). Adverse events were identified using Patient Safety Indicators (PSI) to identify adverse events occurring during hospitalization. We used the Charlson index to study medical comorbidities and bivariate statistics.During the study period 15,413 finger and thumb replantations were performed in the United States, with 616 performed on patients age 65 and older. The overall in-hospital mortality was 0.04% with no statistical difference when factoring age. For the entire group, the percentage of PSI was 0.6%, the most common being postoperative deep venous thrombosis and pulmonary embolus. Overall, there was no difference in PSI between the 2 groups. The older group had a higher rate of transfusion, 4% versus 8% (p < .05) and were more likely to have a nonroutine disposition (ie, nursing home) (p < .001). We found no correlation between the Charlson index and PSI.This study found no difference in sentinel perioperative complications or mortality when comparing replantation patients under 65 years of age and those age 65 and older. Age alone should not be an absolute contraindication to finger replantation. Instead, the patient's functional demands, type of injury, general state of health, and rehabilitative potential should drive the decision of whether to proceed with replantation.

  View details for DOI 10.1016/j.jhsa.2011.01.031

  View details for Web of Science ID 000290185700017

• Risk factors predictive of carotid artery stenting-associated subclinical microemboli. The International journal of angiology : official publication of the International College of Angiology, Inc Zhou, W., Zareie, R., Tedesco, M., Gholibeikian, S., Lane, B., Hernandez-Boussard, T., Rosen, A. 2011; 20 (1): 25-32

  Abstract

  Subclinical microemboli documented on diffusion-weighted magnetic resonance imaging (DWI) are common following carotid artery stenting (CAS) procedures despite absence of neurological symptoms. This study was to evaluate risk factors predictive of microemboli in patients undergoing protected CAS with a distal embolic protection device. All CAS patients who received pre- and postprocedural magnetic resonance imaging (MRI) evaluations for carotid interventions at a single academic institution from July 2004 to December 2008 were examined. Microemboli were defined by new hyperintensities on postoperative DWI with corresponding decreased diffusion. Risk factors including patient demographics, medical comorbidities, clinical symptoms, lesion morphologies, and perioperative information were examined, and logistic regression analyses were utilized to determine predictors of CAS-related microemboli. A total of 204 patients underwent carotid interventions (76 CAS and 128 carotid endarterectomies) during the study period; 167 of them, including 67 CAS patients, received both preoperative and postoperative MRIs. Among those who underwent protected CAS, the incidence of microemboli was 46.3% despite a relative low incidence of associated neurological symptoms (2.9%). Univariate and multivariate regression analyses showed that date of procedure (odds ratio [OR] 30.6 and p = 0.019) and preoperative transient ischemic attack symptoms (OR 9.24 and p = 0.009) were independent predictors of developing postoperative changes on DWI in the ipsilateral hemisphere, and age >76 years was predictive of having new lesions on DWI in the contralateral hemisphere (OR 6.11 and p = 0.026). Our study underscores that certain risk factors are significantly associated with CAS-related microemboli and that physician experience and patient selection are essential in improving outcome of CAS procedures.

  View details for DOI 10.1055/s-0031-1272546

  View details for PubMedID 22532767

• Impaired Alcohol Metabolism after Gastric Bypass Surgery: A Case-Crossover Trial JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS Woodard, G. A., Downey, J., Hernandez-Boussard, T., Morton, J. M. 2011; 212 (2): 209-214

  Abstract

  Severe obesity remains the leading public health crisis of the industrialized world, with bariatric surgery the only effective and enduring treatment. Poor psychological adjustment has been occasionally reported postoperatively. In addition, evidence suggests that patients can metabolize alcohol differently after gastric bypass.Preoperatively and at 3 and 6 months postoperatively, 19 Roux-en-Y gastric bypass (RYGB) patients' breath alcohol content (BAC) was measured every 5 minutes after drinking 5 oz red wine to determine peak BAC and time until sober in a case-crossover design preoperatively and at 6 months postoperatively.Patients reported symptoms experienced when intoxicated and answered a questionnaire of drinking habits. The peak BAC in patients after RYGB was considerably higher at 3 months (0.059%) and 6 months (0.088%) postoperatively than matched preoperative levels (0.024%). Patients also took considerably more time to return to sober at 3 months (61 minutes) and 6 months (88 minutes) than preoperatively (49 minutes). Postoperative intoxication was associated with lower levels of diaphoresis, flushing, and hyperactivity and higher levels of dizziness, warmth, and double vision. Postoperative patients reported drinking considerably less alcohol, fewer preferred beer, and more preferred wine than before surgery.This is the first study to match preoperative and postoperative alcohol metabolism in gastric bypass patients. Post-RYGB patients have much higher peak BAC after ingesting alcohol and require more time to become sober. Patients who drink alcohol after gastric bypass surgery should exercise caution.

  View details for DOI 10.1016/j.jamcollsurg.2010.09.020

  View details for Web of Science ID 000287466200010

  View details for PubMedID 21183366

• Declining Incidence of Neonatal Endophthalmitis in the United States AMERICAN JOURNAL OF OPHTHALMOLOGY Moshfeghi, A. A., Charalel, R. A., Hernandez-Boussard, T., Morton, J. M., Moshfeghi, D. M. 2011; 151 (1): 59-65

  Abstract

  To determine the incidence of neonatal endogenous endophthalmitis in the United States between 1998 and 2006 and to identify associated risk factors.Retrospective cohort study.We used the Nationwide Inpatient Sample database, a 20% representative sample of all hospital discharges in the United States, to help refine our understanding of this condition. International Classification of Diseases, ninth edition, codes for endophthalmitis, sepsis, and suspected endophthalmitis risk factors in hospitalized infants and neonates were searched in the database and were tracked over time. The main outcome measure was incidence of neonatal endophthalmitis over the study period.Of 3.64 million live births in 1998, 317 newborns were identified with endophthalmitis (8.71 cases per 100 000 live births). Of 4.14 million live births in 2006, only 183 newborns were identified with endophthalmitis (4.42 cases per 100 000 live births) by comparison. The incidence of endophthalmitis decreased at a rate of 6% per year (P = .01130) between 1998 and 2006. Neonates with endophthalmitis were more likely to have systemic bacteremia (odds ratio, 21.114; P < .0001), Candidemia (odds ratio, 2.356; P < .0001), a birth weight of less than 1500 g (odds ratio, 1.215; P < .0001), and retinopathy of prematurity (odds ratio, 2.052; P < .0001).We objectively validated the commonly held belief that Candidemia, bacteremia, retinopathy of prematurity, and low birth weight are significant risk factors for endophthalmitis development in infants, which seems to have had a decreasing incidence in recent years.

  View details for DOI 10.1016/j.ajo.2010.07.008

  View details for Web of Science ID 000286081200011

  View details for PubMedID 20970776

• Do Preventive Care Disparities Exist For the Obese? 28th Annual Scientific Meeting on the Obesity-Society Morton, J., Hernandez-Boussard, T. NATURE PUBLISHING GROUP. 2010: S196–S196

  View details for Web of Science ID 000283811500684

• Post-traumatic stress disorder (PTSD) is not a contraindication to gastric bypass in veterans with morbid obesity SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES Ikossi, D. G., Maldonado, J. R., Hernandez-Boussard, T., Eisenberg, D. 2010; 24 (8): 1892-1897

  Abstract

  The veteran population is routinely screened for post-traumatic stress disorder (PTSD). The prevalence of obesity in this population continues to increase. We examined whether weight loss outcomes in veterans with PTSD is comparable to results in veterans who do not suffer from PTSD, after gastric bypass. We also examined the effect of bariatric surgery on PTSD symptoms.This retrospective review of prospective data compares veterans with and without PTSD who underwent laparoscopic gastric bypass. Differences between the means of age, initial BMI, and percent excess weight loss were compared between the groups using a Student's t test. Pearson's chi(2) was used to evaluate the relationship between a diagnosis of PTSD, major depressive disorder (MDD), and other Axis I psychiatric disorders. A similar analysis was done to assess for a relationship between PTSD and obesity-related comorbidities, including diabetes mellitus (DM), hypertension (HTN), hyperlipidemia, and GERD.We identified 24 patients who had gastric bypass and a diagnosis of PTSD before surgery and compared them to those without PTSD. Both groups had a similar mean age and initial BMI. There was no significant difference between the percent excess weight lost after 1 year follow-up between the PTSD group (66%) and the non-PTSD group (72%) (p = 0.102). In assessing comorbid conditions, we found a significant association between the diagnosis of PTSD and MDD (p = 0.002), PTSD and other Axis I disorders (p = 0.004), and PTSD and GERD (p = 0.002). However, we saw no significant association between PTSD and DM (p = 0.977), HTN (p = 0.332), and obstructive sleep apnea (OSA) (p = 0.676). The severity of PTSD symptoms fluctuated in the postoperative period.Veterans with PTSD have comparable weight loss to those without PTSD after gastric bypass. In addition, surgery does not seem to have an adverse effect on PTSD symptoms, although PTSD symptomatology tends to fluctuate over time. Further study in this patient population is warranted.

  View details for DOI 10.1007/s00464-009-0866-8

  View details for Web of Science ID 000279488400015

  View details for PubMedID 20063014

• A comparison of laparoscopic and robotic assisted suturing performance by experts and novices SURGERY Chandra, V., Nehra, D., Parent, R., Woo, R., Reyes, R., Hernandez-Boussard, T., Dutta, S. 2010; 147 (6): 830-839

  Abstract

  Surgical robotics has been promoted as an enabling technology. This study tests the hypothesis that use of the robotic surgical system can significantly improve technical ability by comparing the performance of both experts and novices on a complex laparoscopic task and a robotically assisted task.Laparoscopic experts (LE) with substantial laparoscopic and robotic experience (n = 9) and laparoscopic novices (LN) (n = 20) without any robotic experience performed sequentially 10 trials of a suturing task using either robotic or standard laparoscopic instrumentation fitted to the ProMIS surgical simulator. Objective performance metrics provided by ProMIS (total task time, instrument pathlength, and smoothness) and an assessment of learning curves were analyzed.Compared with LNs, the LEs demonstrated significantly better performance on all assessment measures. Within the LE group, there was no difference in smoothness (328 +/- 159 vs 355 +/- 174; P = .09) between robot-assisted and standard laparoscopic tasks. An improvement was noted in total task time (113 +/- 41 vs 132 +/- 55 sec; P < .05) and instrument pathlengths (371 +/- 163 vs 645 +/- 269 cm; P < .05) when using the robot. This advantage in terms of total task time, however, was lost among the LEs by the last 3 trials (114 +/- 40 vs 118 +/- 49 s; P = .84), while instrument pathlength remained better consistently throughout all the trials. For the LNs, performance was significantly better in the robotic trials on all 3 measures throughout all the trials.The ProMIS surgical simulator was able to distinguish between skill levels (expert versus novice) on robotic suturing tasks, suggesting that the ProMIS is a valid tool for measuring skill in robot-assisted surgery. For all the ProMIS metrics, novices demonstrated consistently better performance on a suturing task using robotics as compared to a standard laparoscopic setup. This effect was less evident for experts who demonstrated improvements only in their economy of movement (pathlength), but not in the speed or smoothness of performance. Robotics eliminated the early learning curve for novices, which was present when they used standard laparoscopic tools. Overall, this study suggests that, when performing complex tasks such as knot tying, surgical robotics is most useful for inexperienced laparoscopists who experience an early and persistent enabling effect. For experts, robotics is most useful for improving economy of motion, which may have implications for the highly complex procedures in limited workspaces (eg, prostatectomy).

  View details for DOI 10.1016/j.surg.2009.11.002

  View details for Web of Science ID 000278532300011

  View details for PubMedID 20045162

• Early, Intermediate, and Late Effects of a Surgical Skills "Boot Camp" on an Objective Structured Assessment of Technical Skills: A Randomized Controlled Study 4th Annual Academic Surgical Congress Parent, R. J., Plerhoples, T. A., Long, E. E., Zimmer, D. M., Teshome, M., Mohr, C. J., Ly, D. P., Hernandez-Boussard, T., Curet, M. J., Dutta, S. ELSEVIER SCIENCE INC. 2010: 984–89

  Abstract

  Surgical interns enter residency with variable technical abilities and many feel unprepared to perform necessary procedures. We hypothesized that interns exposed to a preinternship intensive surgical skills curriculum would demonstrate improved competency over unexposed colleagues on a test of surgical skills and that this effect would persist throughout internship.We designed a 3-day intensive skills "boot camp" with simulation-based training on 10 topics. Interns were randomized to an intervention group (boot camp) or a control group (no boot camp). All interns completed a survey including demographic information, previous experience, and comfort with basic surgical skills. Both groups completed a clinical skills assessment focused on 4 topics: chest tube insertion, central line placement, wound closure, and the Fundamentals of Laparoscopic Surgery peg transfer task. We assessed both groups immediately (month 0), early postcurriculum (month 1), and late postcurriculum (month 6).Fifteen participants were in the intervention group and 13 were in the control group. Before boot camp, mean comfort levels were similar for the groups. All participants had minimal prior experience. Competency for chest tube insertion and central line placement were considerably higher for the boot camp group at months 0 and 1, although much of this difference disappeared by month 6. There was no substantial difference between the 2 groups in the Fundamentals of Laparoscopic Surgery peg transfer and wound closure skills.A surgical skills boot camp accelerates the learning curve for interns in basic surgical skills as measured by a technical skills examination for some skills, although these improvements diminished over time. This can augment traditional training and translate into fewer patient errors.

  View details for DOI 10.1016/j.jamcollsurg.2010.03.006

  View details for Web of Science ID 000278649100013

  View details for PubMedID 20510808

• One Year Improvements in Cardiovascular Risk Factors: a Comparative Trial of Laparoscopic Roux-en-Y Gastric Bypass vs. Adjustable Gastric Banding OBESITY SURGERY Woodard, G. A., Peraza, J., Bravo, S., Toplosky, L., Hernandez-Boussard, T., Morton, J. M. 2010; 20 (5): 578-582

  Abstract

  Coronary artery disease (CAD) is the leading cause of death in the industrialized world with obesity as a leading preventable risk factor. Roux-en-Y gastric bypass (RYGB) and laparoscopic adjustable gastric banding (LAGB) have been shown to improve certain biochemical cardiovascular risk factors (BCRFs) at 1 year post-op, however no study has directly compared the 12-month BCRF improvements of RYGB vs. LAGB.At a single academic institution (2004-2009), we measured BCRF in 838 consecutive bariatric patients (765 RYGB, 73 LAGB) pre-operatively and at 12 months post-operatively. BCRF included total cholesterol (TC), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides (Trig), Trig/HDL ratio, lipoprotein(a) (Lp(a)), homocysteine (HmC), high sensitivity C-reactive protein (hs-CRP), fasting insulin (FI), and hemoglobin A1C (Hgb A1C). Pre-op and 12-month post-op values were compared by a paired t test of equal variance.At 12 months post-op, RYGB patients had lost 77% of their excess weight and had significant improvements in TC, LDL, HDL, Trig, Trig/HDL, HmC, hs-CRP, FI, and Hgb A1C. LAGB patients lost 47.6% of their excess weight and had significant improvements in Trig, Trig/HDL, HmC, hs-CRP, and Hgb A1C. Having RYGB instead of LAGB was predictive of significantly greater improvements in TC at 12 months post-operatively.In this study, both RYGB and LAGB demonstrated significant weight loss and improvements in BCRF at 12 months post-op. RYGB produced significant improvements in a greater number of BCRFs and in some instances the 12-month post-op BCRF values were significantly lower risk in RYGB vs. LAGB patients.

  View details for DOI 10.1007/s11695-010-0088-0

  View details for Web of Science ID 000276470700007

  View details for PubMedID 20186576

• Genomic and functional analysis identifies CRKL as an oncogene amplified in lung cancer ONCOGENE Kim, Y. H., Kwei, K. A., Girard, L., Salari, K., Kao, J., Pacyna-Gengelbach, M., Wang, P., Hernandez-Boussard, T., Gazdar, A. F., Petersen, I., Minna, J. D., Pollack, J. R. 2010; 29 (10): 1421-1430

  Abstract

  DNA amplifications, leading to the overexpression of oncogenes, are a cardinal feature of lung cancer and directly contribute to its pathogenesis. To uncover such novel alterations, we performed an array-based comparative genomic hybridization survey of 128 non-small-cell lung cancer cell lines and tumors. Prominent among our findings, we identified recurrent high-level amplification at cytoband 22q11.21 in 3% of lung cancer specimens, with another 11% of specimens exhibiting low-level gain spanning that locus. The 22q11.21 amplicon core contained eight named genes, only four of which were overexpressed (by transcript profiling) when amplified. Among these, CRKL encodes an adapter protein functioning in signal transduction, best known as a substrate of the BCR-ABL kinase in chronic myelogenous leukemia. RNA-interference-mediated knockdown of CRKL in lung cancer cell lines with (but not without) amplification led to significantly decreased cell proliferation, cell-cycle progression, cell survival, and cell motility and invasion. In addition, overexpression of CRKL in immortalized human bronchial epithelial cells led to enhanced growth factor-independent cell growth. Our findings indicate that amplification and resultant overexpression of CRKL contribute to diverse oncogenic phenotypes in lung cancer, with implications for targeted therapy, and highlight a role of adapter proteins as primary genetic drivers of tumorigenesis.

  View details for DOI 10.1038/onc.2009.437

  View details for Web of Science ID 000275392400002

  View details for PubMedID 19966867

  View details for PubMedCentralID PMC3320568

• A Second Look at the Fresh Frozen Plasma: Packed Red Blood Cell Ratio in Massive Transfusion Protocols Reply JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS Riskin, D. J., Hernandez-Boussard, T., Brundage, S. I. 2010; 210 (1): 117-118

  View details for Web of Science ID 000279279800020

• Long-term radiographic outcomes of microemboli following carotid interventions 63rd Vascular Annual Meeting of the Society-for-Vascular-Surgery (SVS) Zhou, W., Dinishak, D., Lane, B., Hernandez-Boussard, T., Bech, F., Rosen, A. MOSBY-ELSEVIER. 2009: 1314–19

  Abstract

  Subclinical microemboli on diffusion-weighted magnetic resonance imaging (DWI) have been identified immediately following carotid revascularization procedures, but the clinical significance and long-term effects are largely unknown. The purpose of this study was to evaluate long-term radiographic outcomes of these DWI lesions.Patients who underwent perioperative magnetic resonance imaging (MRI) evaluations for carotid interventions at a single institution from July 2004 to December 2008 were evaluated, particularly those who had additional follow-up MRI. DWI with apparent diffusion coefficient (ADC), fluid-attenuated inversion recovery (FLAIR), and T2-weighted MRI images were compared to determine long-term effect of microemboli.One-hundred sixty-eight consecutive patients (68 carotid artery stenting [CAS] and 100 carotid endarterectomy [CEA]) who received perioperative MRI were included. All CAS were performed with an embolic protection device. The incidence of microemboli was significantly higher in the CAS group than the CEA group (46.3% and 12%, respectively, P < .05) despite a relative low incidence of procedure-associated neurologic symptoms in both groups (2.9% vs 2%). Thirty patients (16 CAS and 14 CEA) who had follow-up MRI were further analyzed and a total of 50 postoperative DWI lesions (mean size 46.57 mm(2); range 16 to 128 mm(2)) were identified among them. During a mean MRI follow-up of 10 months (range, 2 to 23 months), residual MRI abnormalities were only identified in DWI lesions larger than 60 mm(2) on postoperative MRI and on postoperative FLAIR images (n = 5, P < .001). The CEA group had fewer but larger ipsilateral distributed emboli (total 12 lesions, mean 79 mm(2)) compared with the CAS group (total 38 lesions, mean 27.5 mm(2), P < .05).The majority of microemboli do not have long-term radiographic sequelae. Size and hyperintensity on postoperative FLAIR are predictive of residual brain structure abnormality, and further neurocognitive evaluations are warranted.

  View details for DOI 10.1016/j.jvs.2009.07.105

  View details for Web of Science ID 000272860900010

  View details for PubMedID 19837533

• The Halo Effect of Bariatric Surgery: Weight Loss in Patients Family Members 27th Annual Scientific Meeting of the Obesity-Society Morton, J., Woodard, G., Encarnacion, B., Downey, J., Peraza, J., Hernandez-Boussard, T. NATURE PUBLISHING GROUP. 2009: S68–S69

  View details for Web of Science ID 000271237800075

• Incidence of Retinopathy of Prematurity in the United States: 1997 through 2005 AMERICAN JOURNAL OF OPHTHALMOLOGY Lad, E. M., Hernandez-Boussard, T., Morton, J. M., Moshfeghi, D. M. 2009; 148 (3): 451-458

  Abstract

  To determine the incidence of retinopathy of prematurity (ROP) based on a national database and to identify baseline characteristics, demographic information, comorbidities, and surgical interventions.Retrospective study based on the National Inpatient Sample from 1997 through 2005.The National Inpatient Sample was queried for all newborn infants with and without ROP. Multivariate logistic regression was used to predict risk factors for ROP.Thirty-four million live births were recorded during the study period. The total ROP incidence was 0.17% overall and 15.58% for premature infants with length of stay of more than 28 days. Our results conclusively demonstrated the importance of low birth weight as a risk for ROP development in infants with length of stay of more than 28 days, as well as association with respiratory conditions, fetal hemorrhage, intraventricular hemorrhage, and blood transfer. An interesting finding was the protective effect conferred by hypoxia, necrotizing enterocolitis, and hemolytic disease of the newborn. Infants with ROP had a higher incidence of undergoing laser photocoagulation therapy, pars plana vitrectomy, and scleral buckle surgery.The current study represents a large, retrospective analysis of newborns with ROP. The multivariate analysis emphasizes the role of birth weight in extended-stay infants, as well as respiratory conditions, fetal hemorrhage, intraventricular hemorrhage, and blood transfer.

  View details for DOI 10.1016/j.ajo.2009.04.018

  View details for PubMedID 19541285

• Massive Transfusion Protocols: The Role of Aggressive Resuscitation Versus Product Ratio in Mortality Reduction JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS Riskin, D. J., Tsai, T. C., Riskin, L., Hernandez-Boussard, T., Purtill, M., Maggio, P. M., Spain, D. A., Brundage, S. I. 2009; 209 (2): 198-205

  Abstract

  Exsanguinating hemorrhage necessitating massive blood product transfusion is associated with high mortality rates. Recent data suggest that altering the fresh frozen plasma to packed red blood cell ratio (FFP:PRBC) results in significant mortality reductions. Our purpose was to evaluate mortality and blood product use in the context of a newly initiated massive transfusion protocol (MTP).In July 2005, our American College of Surgeons-verified Level I trauma center implemented an MTP supporting a 1:1.5 FFP:PRBC ratio, improved communications, and enhanced systems flow to optimize rapid blood product availability. During the 4 years surrounding protocol implementation, we reviewed data on trauma patients directly admitted through the emergency department and requiring 10 or more units PRBCs during the first 24 hours.For the 2 years before and subsequent to MTP initiation, there were 4,223 and 4,414 trauma activations, of which 40 and 37 patients, respectively, met study criteria. The FFP:PRBC ratios were identical, at 1:1.8 and 1:1.8 (p = 0.97). Despite no change in FFP:PRBC ratio, mortality decreased from 45% to 19% (p = 0.02). Other significant findings included decreased mean time to first product: cross-matched RBCs (115 to 71 minutes; p = 0.02), FFP (254 to 169 minutes; p = 0.04), and platelets (418 to 241 minutes; p = 0.01).MTP implementation is associated with mortality reductions that have been ascribed principally to increased plasma use and decreased FFP:PRBC ratios. Our study found a significant reduction in mortality despite unchanged FFP:PRBC ratios and equivalent overall mean numbers of transfusions. Our data underscore the importance of expeditious product availability and emphasize that massive transfusion is a complex process in which product ratio and time to transfusion represent only the beginning of understanding.

  View details for DOI 10.1016/j.jamcollsurg.2009.04.016

  View details for Web of Science ID 000268747300006

  View details for PubMedID 19632596

• Molecular Profiling of Breast Cancer Cell Lines Defines Relevant Tumor Models and Provides a Resource for Cancer Gene Discovery PLOS ONE Kao, J., Salari, K., Bocanegra, M., Choi, Y., Girard, L., Gandhi, J., Kwei, K. A., Hernandez-Boussard, T., Wang, P., Gazdar, A. F., Minna, J. D., Pollack, J. R. 2009; 4 (7)

  Abstract

  Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes-luminal A, luminal B, ERBB2-associated, basal-like and normal-like-with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes.Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression.Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem/progenitor-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 multi-copy deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes.Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, cancer stem cell biology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes.

  View details for DOI 10.1371/journal.pone.0006146

  View details for Web of Science ID 000267806300015

  View details for PubMedID 19582160

  View details for PubMedCentralID PMC2702084

• Probiotics Improve Outcomes After Roux-en-Y Gastric Bypass Surgery: A Prospective Randomized Trial JOURNAL OF GASTROINTESTINAL SURGERY Woodard, G. A., Encarnacion, B., Downey, J. R., Peraza, J., Chong, K., Hernandez-Boussard, T., Morton, J. M. 2009; 13 (7): 1198-1204

  Abstract

  Roux-en-Y gastric bypass (RNYGB) surgery offers an effective and enduring treatment for morbid obesity. Gastric bypass may alter gastrointestinal (GI) flora possibly resulting in bacterial overgrowth and dysmotility. Our hypothesis was that daily use of probiotics would improve GI outcomes after RNYGB.Forty-four patients undergoing RNYGB were randomized to either a probiotic or control group; 2.4 billion colonies of Lactobacillus were administered daily postoperatively to the probiotic group. The outcomes of H(2) levels indicative of bacterial overgrowth, GI-related quality of life (GIQoL), serologies, and weight loss were measured preoperatively and at 3 and 6 months postoperatively. Categorical variables were analyzed by chi(2) test and continuous variables were analyzed by t test with a p < 0.05 for significance.At 6 months, a statistically significant reduction in bacterial overgrowth was achieved in the probiotic group with a preoperative to postoperative change of sum H(2) part per million (probiotics = -32.13, controls = 0.80). Surprisingly, the probiotic group attained significantly greater percent excess weight loss than that of control group at 6 weeks (controls = 25.5%, probiotic = 29.9%) and 3 months (38.55%, 47.68%). This trend also continued but was not significant at 6 months (60.78%, 67.15%). The probiotic group had significantly higher postoperative vitamin B12 levels than the control group. Both probiotic and control groups significantly improved their GIQoL.In this novel study, probiotic administration improves bacterial overgrowth, vitamin B12 availability, and weight loss after RNYGB. These data may provide further evidence that altering the GI microbiota can influence weight loss.

  View details for DOI 10.1007/s11605-009-0891-x

  View details for Web of Science ID 000266821800008

  View details for PubMedID 19381735

• Commitment to COT Verification Improves Patient Outcomes and Financial Performance 67th Annual Meeting of the American-Association-for-the-Surgery-of-Trauma/Meeting of the Association-for-Acute-Medicine Maggio, P. M., Brundage, S. I., Hernandez-Boussard, T., Spain, D. A. LIPPINCOTT WILLIAMS & WILKINS. 2009: 190–95

  Abstract

  After an unsuccessful American College of Surgery Committee on Trauma visit, our level I trauma center initiated an improvement program that included (1) hiring new personnel (trauma director and surgeons, nurse coordinator, orthopedic trauma surgeon, and registry staff), (2) correcting deficiencies in trauma quality assurance and process improvement programs, and (3) development of an outreach program. Subsequently, our trauma center had two successful verifications. We examined the longitudinal effects of these efforts on volume, patient outcomes and finances.The Trauma Registry was used to derive data for all trauma patients evaluated in the emergency department from 2001 to 2007. Clinical data analyzed included number of admissions, interfacility transfers, injury severity scores (ISS), length of stay, and mortality for 2001 to 2007. Financial performance was assessed for fiscal years 2001 to 2007. Data were divided into patients discharged from the emergency department and those admitted to the hospital.Admissions increased 30%, representing a 7.6% annual increase (p = 0.004), mostly due to a nearly fivefold increase in interfacility transfers. Severe trauma patients (ISS >24) increased 106% and mortality rate for ISS >24 decreased by 47% to almost half the average of the National Trauma Database. There was a 78% increase in revenue and a sustained increase in hospital profitability.A major hospital commitment to Committee on Trauma verification had several salient outcomes; increased admissions, interfacility transfers, and acuity. Despite more seriously injured patients, there has been a major, sustained reduction in mortality and a trend toward decreased intensive care unit length of stay. This resulted in a substantial increase in contribution to margin (CTM), net profit, and revenues. With a high level of commitment and favorable payer mix, trauma center verification improves outcomes for both patients and the hospital.

  View details for DOI 10.1097/TA.0b013e3181a51b2f

  View details for Web of Science ID 000267953100035

  View details for PubMedID 19590334

• Platinum pathway PHARMACOGENETICS AND GENOMICS Marsh, S., McLeod, H., Dolan, E., Shukla, S. J., Rabik, C. A., Gong, L., Hernandez-Boussard, T., Lou, X. J., Klein, T. E., Altman, R. B. 2009; 19 (7): 563-564

  View details for DOI 10.1097/FPC.0b013e32832e0ed7

  View details for Web of Science ID 000267619000011

  View details for PubMedID 19525887

• Preoperative Thrombus Volume Predicts Sac Regression After Endovascular Aneurysm Repair JOURNAL OF ENDOVASCULAR THERAPY Yeung, J. J., Hernandez-Boussard, T. M., Song, T. K., Dalman, R. L., Lee, J. T. 2009; 16 (3): 380-388

  Abstract

  To examine whether preoperative aneurysm thrombus volume correlated with abdominal aortic aneurysm (AAA) sac regression following endovascular aneurysm repair (EVAR).Clinical records and computed tomographic angiograms (CTAs) from patients undergoing EVAR from 2003 to 2008 were reviewed. Inclusion criteria for this study were available preoperative CTA images, >or=12-month follow-up with surveillance imaging, lack of re-intervention at 12 months, and treatment with commercially available devices. Patients with ruptured AAAs, those requiring an aortomonoiliac stent-graft, and clinical trial cases were excluded. Based on these criteria, satisfactory images and clinical follow-up were available in 100 patients (90 men; mean age 76.8 years, range 55-95). Preoperative CTAs were categorized as demonstrating "minimal," "moderate," or "severe" aneurysm thrombus load by 2 independent examiners blinded to clinical outcome. Percentage of the aortic cross-sectional area occluded by clot (% clot area) was calculated as [(total area) - (luminal area)]/(total area). Multivariate logistic regression analysis was performed to determine predictors of sac shrinkage at long-term follow-up.AAA thrombus was classified as minimal in 24%, moderate in 23%, and severe in 53%. Thrombus area averaged 11%+/-13%, 41%+/-14%, and 72+/-12% in each group, respectively. By multivariate analysis, minimal thrombus (OR = 1.47) and greater AAA diameter (OR = 1.3) were independent predictors of sac regression at 1, 6, and 12 months (all p<0.05). Presence of neck plaque and endoleak were also independent predictors of sac expansion (p<0.05). Patients with severe preoperative thrombus were less likely to demonstrate sac regression even in the absence of endoleak. Thrombus judgment (subjective) and percent clot area (objective) were strongly correlated (R = 0.82, p<0.05). Interobserver agreement on thrombus judgment was 86%.Thrombus burden on preoperative CTA is a strong independent predictor of sac regression following EVAR. If validated by prospective studies, relative thrombus burden should be incorporated into postoperative surveillance algorithms to define procedural success and optimize the timing and cost-effectiveness of cross-sectional imaging.

  View details for PubMedID 19642793

• Does Insurance Status Affect Gastric Bypass Surgery Outcomes? Digestive Disease Week/110th Annual Meeting of the American-Gastroenterological-Association Woodard, G., Hernandez-Boussard, T., Morton, J. W B SAUNDERS CO-ELSEVIER INC. 2009: A902–A902

  View details for Web of Science ID 000275277204504

• Bariatric Surgery Improves Musculoskeletal Quality of Life Independent of Weight Loss and Procedure Type Digestive Disease Week/110th Annual Meeting of the American-Gastroenterological-Association Bravo, S., Woodard, G., Hernandez-Boussard, T., Morton, J. W B SAUNDERS CO-ELSEVIER INC. 2009: A903–A903

  View details for Web of Science ID 000275277204506

• Relationship Between Hospital Volume, System Clinical Resources, and Mortality in Pancreatic Resection JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS Joseph, B., Morton, J. M., Hernandez-Boussard, T., Rubinfeld, I., Faraj, C., Velanovich, V. 2009; 208 (4): 520-527

  Abstract

  The relationship between hospital volume and perioperative mortality in pancreaticoduodenectomy has been well established. We studied whether associations exist between hospital volume and hospital clinical resources and between both of these factors to mortality to help explain this relationship.This two-part study reviewed publicly available hospital information from the Leapfrog Group, HealthGrades, and hospital Web sites. Hospitals were evaluated for Leapfrog ICU staffing criteria and Safe Practice Score; HealthGrades five-star rating for complex gastrointestinal procedures and operations; and presence of a general surgery residency, gastroenterology fellowship, and interventional radiology. Evaluation used trend analysis and multiple logistic regression analysis. The second part determined the mortality rate for pancreaticoduodenectomy using inpatient mortality data from the National Inpatient Sample and Leapfrog. Hospitals were categorized by low volume (< or = 10/year), high volume (> or = 11/year), strong clinical support (presence of all support factors), and weak clinical support (absence of any factor). Data were correlated by number of pancreatic resections per hospital, hospital system clinical resources, and operative mortality.As hospital volume increased, statistically significant increases occurred in the frequency of hospitals meeting Leapfrog ICU staffing criteria (p < 0.0001), Leapfrog Safe Practice Score (p = 0.0004), HealthGrades 5-star rating (p < 0.00001), general surgery residency (p < 0.00001), gastroenterology fellowship (p < 0.00001), and interventional radiology services (p < 0.00001). No significant relationships were found between resection volume and any one of the clinical support factors and perioperative death. Presence of strong clinical support was associated with lower mortality (odds ratio = 0.32; p = 0.001).System clinical resources were more influential in operative mortality for pancreatic resection. This might help explain why high-volume hospitals, low-volume surgeons in high-volume institutions, and some lower-volume hospitals with excellent clinical resources have lower perioperative mortality rates for pancreatic resection.

  View details for DOI 10.1016/j.jamcollsurg.2009.01.019

  View details for Web of Science ID 000270996800005

  View details for PubMedID 19476785

• Fate of the external carotid artery following carotid interventions. The International journal of angiology : official publication of the International College of Angiology, Inc Casey, K., Zhou, W., Tedesco, M. M., Al-Khatib, W. K., Hernandez-Boussard, T., Bech, F. 2009; 18 (4): 173-176

  Abstract

  The external carotid artery (ECA) is an important collateral pathway for cerebral blood flow. Carotid artery stenting (CAS) typically crosses the ECA, while carotid endarterectomy (CEA) includes deliberate ECA plaque removal. The purpose of the present study was to compare the long-term patency of the ECA following CAS and CEA as determined by carotid duplex ultrasound.Duplex ultrasounds and hospital records were reviewed for consecutive patients undergoing CAS between February 2002 and April 2008, and were compared with those undergoing CEA in the same time period. Preoperative and postoperative ECA peak systolic velocities were normalized to the common carotid artery (CCA) as ECA/CCA ratios. A significant (80% or greater) ECA stenosis was defined as an ECA/CCA ratio of 4.0. A change of ratio by more than 1 was defined as significant. Data were analyzed using Student's t test and χ(2) analysis.A total of 86 CAS procedures in 83 patients were performed (81 men, mean age 69.9 years). Among them, 38.4% of patients had previous CEA, 9.6% of whom had contralateral internal carotid artery occlusion. Sixty-seven CAS and 65 CEA patients with complete duplex data in the same time period were included in the analyses. There was no difference in the incidence of severe ECA stenosis on preoperative ultrasound evaluations. During a mean follow-up of 34 months (range four to 78 months), three postprocedure ECA occlusions were found in the CAS group. The likelihood of severe stenosis or occlusion following CAS was 28.3%, compared with 11% following CEA (P<0.025). However, 62% of CEA patients and 57% of CAS patients had no significant change in ECA status. Reduction in the patient's degree of ECA stenosis was observed in 9.4% of CAS versus 26.6% of CEA patients. Overall, immediate postoperative ratios of both groups were slightly improved, but there was a trend of more disease progression in the CAS group during follow-up.CAS is associated with a higher incidence of post-procedure ECA stenosis. Despite the absence of neurological symptoms, a trend toward late disease progression of ECA following CAS warrants long-term evaluation.

  View details for PubMedID 22477547

  View details for PubMedCentralID PMC2903025

• Validation of a Prehospital Trauma Triage Tool: A 10-Year Perspective JOURNAL OF TRAUMA-INJURY INFECTION AND CRITICAL CARE Purtill, M., Benedict, K., Hernandez-Boussard, T., Brundage, S. I., Kritayakirana, K., Sherck, J. P., Garland, A., Spain, D. A. 2008; 65 (6): 1253-1257

  Abstract

  Triage of the trauma patient in the field is a complex and challenging issue, especially deciding when to use aeromedical transport. The American College of Surgeons Committee on Trauma recently defined an acceptable under-triage rate [seriously injured patient not taken to a trauma center (TC)] as 5%, whereas over-triage rates may be as high as 25% to 50%. Effective utilization of prehospital helicopter transport requires both accurate assessment of patients and effective communication. The rural county adjacent to our developed trauma system uses standardized triage criteria to identify patients for direct transport to our TCs. We hypothesized these criteria accurately identify major trauma victims (MTV) and further that communication could be simplified to expedite transport.Prehospital personnel use a MAP (mechanism, anatomy, and physiology) scoring system to triage trauma patients. Patients with > or = 2 "hits" are defined as MTV. In 2004, the triage policy was changed so that MTV would be transported directly to a TC without base hospital consultation (previously required). The Emergency Medical Services (EMS) Medical Director reviewed cases transported to the TC to determine the appropriateness of triage decisions (over- and under-triage using the American College of Surgeons Committee on Trauma definitions). Data were compared before and after this policy change.For 2004 to 2006, we evaluated 676 air transports to TC and compared them to 468 in the prior 56 months. The overall transport rate increased slightly 7% to 10%. During the study period the over-triage rate was 31% compared with 21%, before the policy change. The MAP triage tool yielded a 93.8% sensitivity and a 99.5% specificity. Therefore, it determined the need for air-medical transport out of a rural environment into an established trauma system with > 90% accuracy.Prehospital personnel can accurately use a trauma triage tool to identify MTV. Eliminating base station contact, a potential for introducing communication error, did increase over-triage but still well within accepted limits. The system change also resulted in the transport of a greater proportion of minor trauma patients who later proved to have major injuries.

  View details for DOI 10.1097/TA.0b013e31818bbfc2

  View details for Web of Science ID 000261706000010

  View details for PubMedID 19077609

• Mechanical Bowel Preparation in Intestinal Surgery: A Meta-Analysis and Review of the Literature 49th Annual Meeting of the Society-for-Surgery-of-the-Alimentary-Tract/Digestive Disease Week Pineda, C. E., Shelton, A. A., Hernandez-Boussard, T., Morton, J. M., Welton, M. L. SPRINGER. 2008: 2037–44

  Abstract

  Despite several meta-analyses and randomized controlled trials showing no benefit to patients, mechanical bowel preparation (MBP) remains the standard of practice for patients undergoing elective colorectal surgery.We performed a systematic review of the literature of trials that prospectively compared MBP with no MBP for patients undergoing elective colorectal resection. We searched MEDLINE, LILACS, and SCISEARCH, abstracts of pertinent scientific meetings and reference lists for each article found. Experts in the field were queried as to knowledge of additional reports. Outcomes abstracted were anastomotic leaks and wound infections. Meta-analysis was performed using Peto Odds ratio.Of 4,601 patients (13 trials), 2,304 received MBP (Group 1) and 2,297 did not (Group 2). Anastomotic leaks occurred in 97(4.2%) patients in Group 1 and in 81(3.5%) patients in Group 2 (Peto OR = 1.214, CI 95%:0.899-1.64, P = 0.206). Wound infections occurred in 227(9.9%) patients in Group 1 and in 201(8.8%) patients in Group 2 (Peto OR = 1.156, CI 95%:0.946-1.413, P = 0.155).This meta-analysis demonstrates that MBP provides no benefit to patients undergoing elective colorectal surgery, thus, supporting elimination of routine MBP in elective colorectal surgery.In conclusion, MBP is of no benefit to patients undergoing elective colorectal resection and need not be recommended to meet "standard of care."

  View details for DOI 10.1007/s11605-008-0594-8

  View details for Web of Science ID 000260282200037

  View details for PubMedID 18622653

• Gastric Bypass Surgery Improves Markers of Aging Annual Scientific Meeting of the Obesity-Society Downey, J., Woodard, G., Hernandez-Boussard, T., Morton, J. NATURE PUBLISHING GROUP. 2008: S144–S144

  View details for Web of Science ID 000259796600335

• Disparity in Utilization, Demographics and Outcomes for Bariatric Surgeries Annual Scientific Meeting of the Obesity-Society Morton, J., Woodard, G., Downey, J., Hernandez-Boussard, T. NATURE PUBLISHING GROUP. 2008: S297–S297

  View details for Web of Science ID 000259796601370

• Genomic profiling identifies TITF1 as a lineage-specific oncogene amplified in lung cancer ONCOGENE Kwei, K. A., Kim, Y. H., Girard, L., Kao, J., Pacyna-Gengelbach, M., Salari, K., Lee, J., Choi, Y., Sato, M., Wang, P., Hernandez-Boussard, T., Gazdar, A. F., Petersen, I., Minna, J. D., Pollack, J. R. 2008; 27 (25): 3635-3640

  Abstract

  Lung cancer is a leading cause of cancer death, where the amplification of oncogenes contributes to tumorigenesis. Genomic profiling of 128 lung cancer cell lines and tumors revealed frequent focal DNA amplification at cytoband 14q13.3, a locus not amplified in other tumor types. The smallest region of recurrent amplification spanned the homeobox transcription factor TITF1 (thyroid transcription factor 1; also called NKX2-1), previously linked to normal lung development and function. When amplified, TITF1 exhibited increased expression at both the RNA and protein levels. Small interfering RNA (siRNA)-mediated knockdown of TITF1 in lung cancer cell lines with amplification led to reduced cell proliferation, manifested by both decreased cell-cycle progression and increased apoptosis. Our findings indicate that TITF1 amplification and overexpression contribute to lung cancer cell proliferation rates and survival and implicate TITF1 as a lineage-specific oncogene in lung cancer.

  View details for DOI 10.1038/sj.onc.1211012

  View details for Web of Science ID 000256468500015

  View details for PubMedID 18212743

  View details for PubMedCentralID PMC2903002

• Genomic profiling identifies GATA6 as a candidate oncogene amplified in pancreatobiliary cancer PLOS GENETICS Kwei, K. A., Bashyam, M. D., Kao, J., Ratheesh, R., Reddy, E. C., Kim, Y. H., Montgomery, K., Giacomini, C. P., Choi, Y., Chatterjee, S., Karikari, C. A., Salari, K., Wang, P., Hernandez-Boussard, T., Swarnalata, G., van de Rijn, M., Maitra, A., Pollack, J. R. 2008; 4 (5)

  Abstract

  Pancreatobiliary cancers have among the highest mortality rates of any cancer type. Discovering the full spectrum of molecular genetic alterations may suggest new avenues for therapy. To catalogue genomic alterations, we carried out array-based genomic profiling of 31 exocrine pancreatic cancers and 6 distal bile duct cancers, expanded as xenografts to enrich the tumor cell fraction. We identified numerous focal DNA amplifications and deletions, including in 19% of pancreatobiliary cases gain at cytoband 18q11.2, a locus uncommonly amplified in other tumor types. The smallest shared amplification at 18q11.2 included GATA6, a transcriptional regulator previously linked to normal pancreas development. When amplified, GATA6 was overexpressed at both the mRNA and protein levels, and strong immunostaining was observed in 25 of 54 (46%) primary pancreatic cancers compared to 0 of 33 normal pancreas specimens surveyed. GATA6 expression in xenografts was associated with specific microarray gene-expression patterns, enriched for GATA binding sites and mitochondrial oxidative phosphorylation activity. siRNA mediated knockdown of GATA6 in pancreatic cancer cell lines with amplification led to reduced cell proliferation, cell cycle progression, and colony formation. Our findings indicate that GATA6 amplification and overexpression contribute to the oncogenic phenotypes of pancreatic cancer cells, and identify GATA6 as a candidate lineage-specific oncogene in pancreatobiliary cancer, with implications for novel treatment strategies.

  View details for DOI 10.1371/journal.pgen.1000081

  View details for PubMedID 18535672

• Meta-analysis of mechanical bowel preparation for elective colon and rectal resection Digestive Disease Week Meeting/109th Annual Meeting of the American-Gastroenterological-Association Pineda, C. E., Shelton, A. A., Hernandez-Boussard, T., Morton, J. M., Welton, M. L. W B SAUNDERS CO-ELSEVIER INC. 2008: A860–A860

  View details for Web of Science ID 000255101506308

• Signal detection: A new statistical method to predict NASH in gastric bypass patients Digestive Disease Week Meeting/109th Annual Meeting of the American-Gastroenterological-Association Morton, J. M., Woodard, G. A., Hernandez-Boussard, T. W B SAUNDERS CO-ELSEVIER INC. 2008: A855–A855

  View details for Web of Science ID 000255101506282

• The pharmacogenetics and pharmacogenomics knowledge base: accentuating the knowledge NUCLEIC ACIDS RESEARCH Hernandez-Boussard, T., Whirl-Carrillo, M., Hebert, J. M., Gong, L., Owen, R., Gong, M., Gor, W., Liu, F., Truong, C., Whaley, R., Woon, M., Zhou, T., Altman, R. B., Klein, T. E. 2008; 36: D913-D918

  Abstract

  PharmGKB is a knowledge base that captures the relationships between drugs, diseases/phenotypes and genes involved in pharmacokinetics (PK) and pharmacodynamics (PD). This information includes literature annotations, primary data sets, PK and PD pathways, and expert-generated summaries of PK/PD relationships between drugs, diseases/phenotypes and genes. PharmGKB's website is designed to effectively disseminate knowledge to meet the needs of our users. PharmGKB currently has literature annotations documenting the relationship of over 500 drugs, 450 diseases and 600 variant genes. In order to meet the needs of whole genome studies, PharmGKB has added new functionalities, including browsing the variant display by chromosome and cytogenetic locations, allowing the user to view variants not located within a gene. We have developed new infrastructure for handling whole genome data, including increased methods for quality control and tools for comparison across other data sources, such as dbSNP, JSNP and HapMap data. PharmGKB has also added functionality to accept, store, display and query high throughput SNP array data. These changes allow us to capture more structured information on phenotypes for better cataloging and comparison of data. PharmGKB is available at www.pharmgkb.org.

  View details for DOI 10.1093/nar/gkm1009

  View details for Web of Science ID 000252545400160

  View details for PubMedID 18032438

  View details for PubMedCentralID PMC2238877

• Genomic profiling reveals alternative genetic pathways of prostate tumorigenesis CANCER RESEARCH Lapointe, J., Li, C., Giacomini, C. P., Salari, K., Huang, S., Wang, P., Ferrari, M., Hernandez-Boussard, T., Brooks, J. D., Pollack, J. R. 2007; 67 (18): 8504-8510

  Abstract

  Prostate cancer is clinically heterogeneous, ranging from indolent to lethal disease. Expression profiling previously defined three subtypes of prostate cancer, one (subtype-1) linked to clinically favorable behavior, and the others (subtypes-2 and -3) linked with a more aggressive form of the disease. To explore disease heterogeneity at the genomic level, we carried out array-based comparative genomic hybridization (array CGH) on 64 prostate tumor specimens, including 55 primary tumors and 9 pelvic lymph node metastases. Unsupervised cluster analysis of DNA copy number alterations (CNA) identified recurrent aberrations, including a 6q15-deletion group associated with subtype-1 gene expression patterns and decreased tumor recurrence. Supervised analysis further disclosed distinct patterns of CNA among gene-expression subtypes, where subtype-1 tumors exhibited characteristic deletions at 5q21 and 6q15, and subtype-2 cases harbored deletions at 8p21 (NKX3-1) and 21q22 (resulting in TMPRSS2-ERG fusion). Lymph node metastases, predominantly subtype-3, displayed overall higher frequencies of CNA, and in particular gains at 8q24 (MYC) and 16p13, and loss at 10q23 (PTEN) and 16q23. Our findings reveal that prostate cancers develop via a limited number of alternative preferred genetic pathways. The resultant molecular genetic subtypes provide a new framework for investigating prostate cancer biology and explain in part the clinical heterogeneity of the disease.

  View details for DOI 10.1158/0008-5472.CAN-07-0673

  View details for Web of Science ID 000249679500013

  View details for PubMedID 17875689

• The Stanford Microarray Database: implementation of new analysis tools and open source release of software NUCLEIC ACIDS RESEARCH Demeter, J., Beauheim, C., Gollub, J., Hernandez-Boussard, T., Jin, H., Maier, D., Matese, J. C., Nitzberg, M., Wymore, F., Zachariah, Z. K., Brown, P. O., Sherlock, G., Ball, C. A. 2007; 35: D766-D770

  Abstract

  The Stanford Microarray Database (SMD; http://smd.stanford.edu/) is a research tool and archive that allows hundreds of researchers worldwide to store, annotate, analyze and share data generated by microarray technology. SMD supports most major microarray platforms, and is MIAME-supportive and can export or import MAGE-ML. The primary mission of SMD is to be a research tool that supports researchers from the point of data generation to data publication and dissemination, but it also provides unrestricted access to analysis tools and public data from 300 publications. In addition to supporting ongoing research, SMD makes its source code fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD. In this article, we describe several data analysis tools implemented in SMD and we discuss features of our software release.

  View details for DOI 10.1093/nar/gkl1019

  View details for Web of Science ID 000243494600151

  View details for PubMedID 17182626

  View details for PubMedCentralID PMC1781111

• Integrating large-scale genotype and phenotype data OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY Hernandez-Boussard, T., Woon, M., Klein, T. E., Altman, R. B. 2006; 10 (4): 545-554

  Abstract

  With the completion of the Human Genome Project, a new emphasis is focusing on the sequence variation and the resulting phenotype. The number of data available from genomic studies addressing this relationship is rapidly growing. In order to analyze these data as a whole, they need to be integrated, aggregated and annotated in a timely manner. The Pharmacogenetics and Pharmacogenomics Knowledge Base PharmGKB; () assembles and disseminates these data and their associated metadata that are needed for unambiguous identification and replication. Assembling these data in a timely manner is challenging, and the scalability of these data produce major challenges for a knowledge base such as PharmGKB. However, it is only through rapid global meta-annotation of these data that we will understand the relationship between specific genotype(s) and the related phenotype. PharmGKB has confronted these challenges, and these experiences and solutions can benefit all genome communities.

  View details for Web of Science ID 000243893500009

  View details for PubMedID 17233563

• Distinct patterns of DNA copy number alteration are associated with different clinicopathological features and gene-expression subtypes of breast cancer GENES CHROMOSOMES & CANCER Bergamaschi, A., Kim, Y. H., Wang, P., Sorlie, T., Hernandez-Boussard, T., Lonning, P. E., Tibshirani, R., Borresen-Dale, A., Pollack, J. R. 2006; 45 (11): 1033-1040

  Abstract

  Breast cancer is a leading cause of cancer-death among women, where the clinicopathological features of tumors are used to prognosticate and guide therapy. DNA copy number alterations (CNAs), which occur frequently in breast cancer and define key pathogenetic events, are also potentially useful prognostic or predictive factors. Here, we report a genome-wide array-based comparative genomic hybridization (array CGH) survey of CNAs in 89 breast tumors from a patient cohort with locally advanced disease. Statistical analysis links distinct cytoband loci harboring CNAs to specific clinicopathological parameters, including tumor grade, estrogen receptor status, presence of TP53 mutation, and overall survival. Notably, distinct spectra of CNAs also underlie the different subtypes of breast cancer recently defined by expression-profiling, implying these subtypes develop along distinct genetic pathways. In addition, higher numbers of gains/losses are associated with the "basal-like" tumor subtype, while high-level DNA amplification is more frequent in "luminal-B" subtype tumors, suggesting also that distinct mechanisms of genomic instability might underlie their pathogenesis. The identified CNAs may provide a basis for improved patient prognostication, as well as a starting point to define important genes to further our understanding of the pathobiology of breast cancer. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat

  View details for DOI 10.1002/gcc.20366

  View details for Web of Science ID 000240601400005

  View details for PubMedID 16897746

• Development of FuGO: An ontology for Functional Genomics Investigations OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY Whetzel, P. L., Brinkman, R. R., Causton, H. C., Fan, L., Field, D., Fostel, J., Fragoso, G., Gray, T., Heiskanen, M., Hernandez-Boussard, T., Morrison, N., Parkinson, H., Rocca-Serra, P., Sansone, S., Schober, D., Smith, B., Stevens, R., Stoeckert, C. J., Taylor, C., White, J., Wood, A. 2006; 10 (2): 199-204

  Abstract

  The development of the Functional Genomics Investigation Ontology (FuGO) is a collaborative, international effort that will provide a resource for annotating functional genomics investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. FuGO will contain both terms that are universal to all functional genomics investigations and those that are domain specific. In this way, the ontology will serve as the "semantic glue" to provide a common understanding of data from across these disparate data sources. In addition, FuGO will reference out to existing mature ontologies to avoid the need to duplicate these resources, and will do so in such a way as to enable their ease of use in annotation. This project is in the early stages of development; the paper will describe efforts to initiate the project, the scope and organization of the project, the work accomplished to date, and the challenges encountered, as well as future plans.

  View details for Web of Science ID 000240210900016

  View details for PubMedID 16901226

• Pharmacogenomics: The relevance of emerging genotyping technologies. MLO: medical laboratory observer Hernandez-Boussard, T., Klein, T. E., Altman, R. B. 2006; 38 (3): 24-?

  View details for PubMedID 16610446

• Combined microarray analysis of small cell lung cancer reveals altered apoptotic balance and distinct expression signatures of MYC family gene amplification ONCOGENE Kim, Y. H., Girard, L., Giacomini, C. P., Wang, P., Hernandez-Boussard, T., Tibshirani, R., Minna, J. D., Pollack, J. R. 2006; 25 (1): 130-138

  Abstract

  DNA amplifications and deletions frequently contribute to the development and progression of lung cancer. To identify such novel alterations in small cell lung cancer (SCLC), we performed comparative genomic hybridization on a set of 24 SCLC cell lines, using cDNA microarrays representing approximately 22,000 human genes (providing an average mapping resolution of <70 kb). We identified localized DNA amplifications corresponding to oncogenes known to be amplified in SCLC, including MYC (8q24), MYCN (2p24) and MYCL1 (1p34). Additional highly localized DNA amplifications suggested candidate oncogenes not previously identified as amplified in SCLC, including the antiapoptotic genes TNFRSF4 (1p36), DAD1 (14q11), BCL2L1 (20q11) and BCL2L2 (14q11). Likewise, newly discovered PCR-validated homozygous deletions suggested candidate tumor-suppressor genes, including the proapoptotic genes MAPK10 (4q21) and TNFRSF6 (10q23). To characterize the effect of DNA amplification on gene expression patterns, we performed expression profiling using the same microarray platform. Among our findings, we identified sets of genes whose expression correlated with MYC, MYCN or MYCL1 amplification, with surprisingly little overlap among gene sets. While both MYC and MYCN amplification were associated with increased and decreased expression of known MYC upregulated and downregulated targets, respectively, MYCL1 amplification was associated only with the latter. Our findings support a role of altered apoptotic balance in the pathogenesis of SCLC, and suggest that MYC family genes might affect oncogenesis through distinct sets of targets, in particular implicating the importance of transcriptional repression.

  View details for DOI 10.1038/sj.onc.1208997

  View details for Web of Science ID 000234406400014

  View details for PubMedID 16116477

• Transcriptional analysis of the molecular basis of human kidney aging using cDNA microarray profiling KIDNEY INTERNATIONAL Melk, A., Mansfield, E. S., Hsieh, S. C., Hernandez-Boussard, T., Grimm, P., Rayner, D. C., Halloran, P. F., Sarwal, M. M. 2005; 68 (6): 2667-2679

  Abstract

  The molecular basis of renal aging is not completely understood.We used global gene expression monitoring by cDNA microarrays to identify age associated genes in human kidney samples. Our samples included young (8 weeks-8 years, N= 4), adult (31-46 years, N= 7), and old kidneys (71-88 years, N= 9).Old kidneys had more glomerulosclerosis, tubular atrophy, interstitial fibrosis, and fibrous intimal thickening in small arteries. We identified approximately 500 genes that were differentially expressed among the three age groups. Old kidneys appeared to have increased extracellular matrix turnover and a nonspecific inflammatory response, combined with a reduction in processes dependent on energy metabolism and mitochondrial function. Quantitative supervised bioinformatics analyses of adult and old kidney expression data correlated the expression of 255 gene profiles with renal pathology scores. Microarray class prediction analysis (PAM) identified 50 unique genes that segregated old kidneys into two distinct clusters: those more similar within age class (OO, N= 5) versus old kidneys more similar to adult kidneys (OA, N= 4). The expression of six functionally significant genes was further validated by quantitative reverse transcription-polymerase chain reaction (RT-PCR) (FN1, MMP7, TNC, SERPIN3A, BPHL, CSPG2) in the experiment group and, subsequently, confirmed independently in 17 additional old and adult age-stratified test kidney samples. The p53 inducible gene, CSPG2, performed best in separating OO kidneys from adults and OA samples in this analysis.The method described in this study using independent validation samples can be envisioned to test utility of the identified genes in assessing age-related changes that contribute to decline in renal function.

  View details for Web of Science ID 000233204300022

  View details for PubMedID 16316342

• Comparative genomic hybridization on mouse cDNA microarrays and its application to a murine lymphoma model ONCOGENE Sander, S., Bullinger, L., Karlsson, A., Giuriato, S., Hernandez-Boussard, T., Felsher, D. W., Pollack, J. R. 2005; 24 (40): 6101-6107

  Abstract

  Microarray-based formats offer a high-resolution alternative to conventional, chromosome-based comparative genomic hybridization (CGH) methods for assessing DNA copy number alteration (CNA) genome-wide in human cancer. For murine tumors, array CGH should provide even greater advantage, since murine chromosomes are more difficult to individually discern. We report here the adaptation and evaluation of a cDNA microarray-based CGH method for the routine characterization of CNAs in murine tumors, using mouse cDNA microarrays representing approximately 14,000 different genes, thereby providing an average mapping resolution of 109 kb. As a first application, we have characterized CNAs in a set of 10 primary and recurrent lymphomas derived from a Myc-induced murine lymphoma model. In primary lymphomas and more commonly in Myc-independent relapses, we identified a recurrent genomic DNA loss at chromosome 3G3-3H4, and recurrent amplifications at chromosome 3F2.1-3G3 and chromosome 15E1/E2-15F3, the boundaries of which we defined with high resolution. Further, by profiling gene expression using the same microarray platform, we identified within CNAs the relevant subset of candidate cancer genes displaying comparably altered expression, including Mcl1 (myeloid cell leukemia sequence 1), a highly expressed antiapoptotic gene residing within the chr 3 amplicon peak. CGH on mouse cDNA microarrays therefore represents a reliable method for the high-resolution characterization of CNAs in murine tumors, and a powerful approach for elucidating the molecular events in tumor development and progression in murine models.

  View details for DOI 10.1038/sj.onc.1208751

  View details for Web of Science ID 000231718100004

  View details for PubMedID 16007205

• Determination of stromal signatures in breast carcinoma PLOS BIOLOGY West, R. B., Nuyten, D. S., Subramanian, S., Nielsen, T. O., Corless, C. L., Rubin, B. P., Montgomery, K., Zhu, S., Patel, R., Hernandez-Boussard, T., Goldblum, J. R., Brown, P. O., van De Vijver, M., van de Rijn, M. 2005; 3 (6): 1101-1110

  Abstract

  Many soft tissue tumors recapitulate features of normal connective tissue. We hypothesize that different types of fibroblastic tumors are representative of different populations of fibroblastic cells or different activation states of these cells. We examined two tumors with fibroblastic features, solitary fibrous tumor (SFT) and desmoid-type fibromatosis (DTF), by DNA microarray analysis and found that they have very different expression profiles, including significant differences in their patterns of expression of extracellular matrix genes and growth factors. Using immunohistochemistry and in situ hybridization on a tissue microarray, we found that genes specific for these two tumors have mutually specific expression in the stroma of nonneoplastic tissues. We defined a set of 786 gene spots whose pattern of expression distinguishes SFT from DTF. In an analysis of DNA microarray gene expression data from 295 previously published breast carcinomas, we found that expression of this gene set defined two groups of breast carcinomas with significant differences in overall survival. One of the groups had a favorable outcome and was defined by the expression of DTF genes. The other group of tumors had a poor prognosis and showed variable expression of genes enriched for SFT type. Our findings suggest that the host stromal response varies significantly among carcinomas and that gene expression patterns characteristic of soft tissue tumors can be used to discover new markers for normal connective tissue cells.

  View details for DOI 10.1371/journal.pbio.0030187

  View details for PubMedID 15869330

• Array-based comparative genomic hybridization identifies localized DNA amplifications and homozygous deletions in pancreatic cancer NEOPLASIA Bashyam, M. D., Bair, R., Kim, Y. H., Wang, P., Hernandez-Boussard, T., Karikari, C. A., Tibshirani, R., Maitra, A., Pollack, J. R. 2005; 7 (6): 556-562

  Abstract

  Pancreatic cancer, the fourth leading cause of cancer death in the United States, is frequently associated with the amplification and deletion of specific oncogenes and tumor-suppressor genes (TSGs), respectively. To identify such novel alterations and to discover the underlying genes, we performed comparative genomic hybridization on a set of 22 human pancreatic cancer cell lines, using cDNA microarrays measuring approximately 26,000 human genes (thereby providing an average mapping resolution of <60 kb). To define the subset of amplified and deleted genes with correspondingly altered expression, we also profiled mRNA levels in parallel using the same cDNA microarray platform. In total, we identified 14 high-level amplifications (38-4934 kb in size) and 15 homozygous deletions (46-725 kb). We discovered novel localized amplicons, suggesting previously unrecognized candidate oncogenes at 6p21, 7q21 (SMURF1, TRRAP), 11q22 (BIRC2, BIRC3), 12p12, 14q24 (TGFB3), 17q12, and 19q13. Likewise, we identified novel polymerase chain reaction-validated homozygous deletions indicating new candidate TSGs at 6q25, 8p23, 8p22 (TUSC3), 9q33 (TNC, TNFSF15), 10q22, 10q24 (CHUK), 11p15 (DKK3), 16q23, 18q23, 21q22 (PRDM15, ANKRD3), and Xp11. Our findings suggest candidate genes and pathways, which may contribute to the development or progression of pancreatic cancer.

  View details for DOI 10.1593/neo.04586

  View details for Web of Science ID 000230209600002

  View details for PubMedID 16036106

  View details for PubMedCentralID PMC1501288

• Expression profiling of murine double-negative regulatory T cells suggest mechanisms for prolonged cardiac allograft survival JOURNAL OF IMMUNOLOGY Lee, B. P., Mansfield, E., Hsieh, S. C., Hernandez-Boussard, T., Chen, W. H., Thomson, C. W., Ford, M. S., Bosinger, S. E., Der, S., Zhang, Z. X., Zhang, M. X., Kelvin, D. J., Sarwal, M. M., Zhang, L. 2005; 174 (8): 4535-4544

  Abstract

  Recent studies have demonstrated that both mouse and human alpha beta TCR(+)CD3(+)NK1.1(-)CD4(-)CD8- double-negative regulatory T (DN Treg) cells can suppress Ag-specific immune responses mediated by CD8+ and CD4+ T cells. To identify molecules involved in DN Treg cell function, we generated a panel of murine DN Treg clones, which specifically kill activated syngeneic CD8+ T cells. Through serial cultivation of DN Treg clones, mutant clones arose that lost regulatory capacity in vitro and in vivo. Although all allogeneic cardiac grafts in animals preinfused with tolerant CD4/CD8 negative 12 DN Treg clones survived over 100 days, allograft survival is unchanged following infusion of mutant clones (19.5 +/- 11.1 days) compared with untreated controls (22.8 +/- 10.5 days; p < 0.001). Global gene expression differences between functional DN Treg cells and nonfunctional mutants were compared. We found 1099 differentially expressed genes (q < 0.025%), suggesting increased cell proliferation and survival, immune regulation, and chemotaxis, together with decreased expression of genes for Ag presentation, apoptosis, and protein phosphatases involved in signal transduction. Expression of 33 overexpressed and 24 underexpressed genes were confirmed using quantitative real-time PCR. Protein expression of several genes, including Fc epsilon RI gamma subunit and CXCR5, which are >50-fold higher, was also confirmed using FACS. These findings shed light on the mechanisms by which DN Treg cells down-regulate immune responses and prolong cardiac allograft survival.

  View details for Web of Science ID 000228234600014

  View details for PubMedID 15814674

• The Stanford Microarray Database accommodates additional microarray platforms and data formats NUCLEIC ACIDS RESEARCH Ball, C. A., Awad, I. A., Demeter, J., Gollub, J., Hebert, J. M., Hernandez-Boussard, T., Jin, H., Matese, J. C., Nitzberg, M., Wymore, F., Zachariah, Z. K., Brown, P. O., Sherlock, G. 2005; 33: D580-D582

  Abstract

  The Stanford Microarray Database (SMD) (http://smd.stanford.edu) is a research tool for hundreds of Stanford researchers and their collaborators. In addition, SMD functions as a resource for the entire biological research community by providing unrestricted access to microarray data published by SMD users and by disseminating its source code. In addition to storing GenePix (Axon Instruments) and ScanAlyze output from spotted microarrays, SMD has recently added the ability to store, retrieve, display and analyze the complete raw data produced by several additional microarray platforms and image analysis software packages, so that we can also now accept data from Affymetrix GeneChips (MAS5/GCOS or dChip), Agilent Catalog or Custom arrays (using Agilent's Feature Extraction software) or data created by SpotReader (Niles Scientific). We have implemented software that allows us to accept MAGE-ML documents from array manufacturers and to submit MIAME-compliant data in MAGE-ML format directly to ArrayExpress and GEO, greatly increasing the ease with which data from SMD can be published adhering to accepted standards and also increasing the accessibility of published microarray data to the general public. We have introduced a new tool to facilitate data sharing among our users, so that datasets can be shared during, before or after the completion of data analysis. The latest version of the source code for the complete database package was released in November 2004 (http://smd.stanford.edu/download/), allowing researchers around the world to deploy their own installations of SMD.

  View details for Web of Science ID 000226524300119

  View details for PubMedID 15608265

• Gene expression profiles and the TP53 mutation status are powerful prognostic markers of breast cancer 3rd International Symposium on the Molecular Biology of Breast Cancer Langerod, A., Zhao, H., Borgan, O., Nesland, J. M., Hernandez-Boussard, T., Bukholm, I. K., Karesen, R., Borresen-Dale, A. L., Jeffrey, S. S. BIOMED CENTRAL LTD. 2005: S52–S52

  View details for DOI 10.1186/bcr1174

  View details for Web of Science ID 000232330500127

• Caryoscope: An Open Source Java application for viewing microarray data in a genomic context BMC BIOINFORMATICS Awad, I. A., Rees, C. A., Hernandez-Boussard, T., Ball, C. A., Sherlock, G. 2004; 5

  Abstract

  Microarray-based comparative genome hybridization experiments generate data that can be mapped onto the genome. These data are interpreted more easily when represented graphically in a genomic context.We have developed Caryoscope, which is an open source Java application for visualizing microarray data from array comparative genome hybridization experiments in a genomic context. Caryoscope can read General Feature Format files (GFF files), as well as comma- and tab-delimited files, that define the genomic positions of the microarray reporters for which data are obtained. The microarray data can be browsed using an interactive, zoomable interface, which helps users identify regions of chromosomal deletion or amplification. The graphical representation of the data can be exported in a number of graphic formats, including publication-quality formats such as PostScript.Caryoscope is a useful tool that can aid in the visualization, exploration and interpretation of microarray data in a genomic context.

  View details for DOI 10.1186/1471-2105-5-151

  View details for Web of Science ID 000225769900002

  View details for PubMedID 15488149

  View details for PubMedCentralID PMC528725

• Gastrointestinal stromal tumors (GISTs) with KIT and PDGFRA mutations have distinct gene expression profiles ONCOGENE Subramanian, S., West, R. B., Corless, C. L., Ou, W. B., Rubin, B. P., Chu, K. M., Leung, S. Y., Yuen, S. T., Zhu, S., Hernandez-Boussard, T., Montgomery, K., Nielsen, T. O., Patel, R. M., Goldblum, J. R., Heinrich, M. C., Fletcher, J. A., van de Rijn, M. 2004; 23 (47): 7780-7790

  Abstract

  Most GISTs require oncogenic activation of the KIT or PDGFRA receptor tyrosine kinase proteins, and the genomic mechanisms of oncogene activation are heterogeneous. Notably, the kinase mutation type correlates with both tumor biology and imatinib response. For example, GISTs with KIT exon 11 mutations are typically gastric and have excellent imatinib response, whereas those with KIT exon 9 mutations generally arise in the small bowel and are less responsive to imatinib. To identify genes that might contribute to these biological differences, we carried out gene expression profiling of 26 GISTs with known KIT and PDGFRA mutational status. Expression differences were then evaluated further by RNA in situ hybridization, immunohistochemistry, and immunoblotting. Unsupervised hierarchical clustering grouped tumors with similar mutations together, but the distinction between the different groups was not absolute. Differentially expressed genes included ezrin, p70S6K, and PKCs, which are known to have key roles in KIT or PDGFRA signaling, and which might therefore contribute to the distinctive clinicopathological features in GISTs with different mutation types. These gene products could serve as highly selective therapeutic targets in GISTs containing the KIT or PDGFRA mutational types with which they are associated.

  View details for DOI 10.1038/sj.onc.1208056

  View details for PubMedID 15326474

• Apo D in soft tissue tumors: a novel marker for dermatofibrosarcoma protuberans (vol 28, pg 1063, 2004) AMERICAN JOURNAL OF SURGICAL PATHOLOGY West, R. B., Harvell, J., Linn, S. C., Lui, C. L., Prapong, W., Hernandez-Boussard, T., Montgomery, K., Nielsen, T. O., Rubin, B. P., Patel, R., Goldblum, J. R., Brown, P. O., van de Rijn, M. 2004; 28 (10): 1400-1400

  View details for Web of Science ID 000224109400023

• Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma CLINICAL CANCER RESEARCH Nielsen, T. O., Hsu, F. D., Jensen, K., Cheang, M., Karaca, G., Hu, Z. Y., Hernandez-Boussard, T., Livasy, C., Cowan, D., Dressler, L., Akslen, L. A., Ragaz, J., GOWN, A. M., Gilks, C. B., van de Rijn, M. V., Perou, C. M. 2004; 10 (16): 5367-5374

  Abstract

  Expression profiling studies classified breast carcinomas into estrogen receptor (ER)+/luminal, normal breast-like, HER2 overexpressing, and basal-like groups, with the latter two associated with poor outcomes. Currently, there exist clinical assays that identify ER+/luminal and HER2-overexpressing tumors, and we sought to develop a clinical assay for breast basal-like tumors.To identify an immunohistochemical profile for breast basal-like tumors, we collected a series of known basal-like tumors and tested them for protein patterns that are characteristic of this subtype. Next, we examined the significance of these protein patterns using tissue microarrays and evaluated the prognostic significance of these findings.Using a panel of 21 basal-like tumors, which was determined using gene expression profiles, we saw that this subtype was typically immunohistochemically negative for estrogen receptor and HER2 but positive for basal cytokeratins, HER1, and/or c-KIT. Using breast carcinoma tissue microarrays representing 930 patients with 17.4-year mean follow-up, basal cytokeratin expression was associated with low disease-specific survival. HER1 expression was observed in 54% of cases positive for basal cytokeratins (versus 11% of negative cases) and was associated with poor survival independent of nodal status and size. c-KIT expression was more common in basal-like tumors than in other breast cancers but did not influence prognosis.A panel of four antibodies (ER, HER1, HER2, and cytokeratin 5/6) can accurately identify basal-like tumors using standard available clinical tools and shows high specificity. These studies show that many basal-like tumors express HER1, which suggests candidate drugs for evaluation in these patients.

  View details for Web of Science ID 000223454600011

  View details for PubMedID 15328174

• Apo D in soft tissue tumors - A novel marker for dermatofibrosarcoma protuberans AMERICAN JOURNAL OF SURGICAL PATHOLOGY West, R. B., Harvell, J., Linn, S. C., Lui, C. L., Prapong, W., Hernandez-Boussard, T., Montgomery, K., Nielsen, T. O., Rubin, B. P., Patel, R., Goldblum, J. R., Brown, P. O., van de Rijn, M. 2004; 28 (8): 1063-1069

  Abstract

  Using gene microarray expression profiling, we previously found that apolipoprotein D (Apo D) was highly expressed in dermatofibrosarcoma protuberans (DFSP). In this study, we confirm that Apo D is highly and relatively specifically expressed in DFSP using immunohistochemistry. A tissue microarray containing 421 soft tissue tumors was constructed and stained with antibodies against Apo D and CD34. Cytoplasmic immunostaining for Apo D was found in 9 of 10 typical DFSPs. In addition, 3 of 3 Bednar tumors and 2 of 3 giant cell fibroblastomas stained in conventional sections. In contrast, Apo D was immunoreactive in only a very small subset of a diverse collection of other soft tissue tumors, including Malignant Fibrous Histiocytoma (MFH), glomus tumor, neurofibroma, and malignant peripheral nerve sheath tumors. Immunostains for Apo D were negative in conventional sections of 16 fibrous histiocytomas, and an additional 12 variants of fibrous histiocytoma. Digital images of all immunohistochemical and hematoxylin and eosin tissue microarray stains are available at the accompanying website (http://microarray-pubs.stanford.edu/tma_portal/apod/). We conclude that Apo D is strongly expressed in DFSPs and neural lesions and may be useful in differentiating DFSP from fibrous histiocytoma.

  View details for PubMedID 15252314

• Lineage-specific gene duplication and loss in human and great ape evolution. PLoS biology Fortna, A., Kim, Y., MacLaren, E., Marshall, K., Hahn, G., Meltesen, L., Brenton, M., Hink, R., Burgers, S., Hernandez-Boussard, T., Karimpour-Fard, A., Glueck, D., McGavran, L., Berry, R., Pollack, J., Sikela, J. M. 2004; 2 (7): E207-?

  Abstract

  Given that gene duplication is a major driving force of evolutionary change and the key mechanism underlying the emergence of new genes and biological processes, this study sought to use a novel genome-wide approach to identify genes that have undergone lineage-specific duplications or contractions among several hominoid lineages. Interspecies cDNA array-based comparative genomic hybridization was used to individually compare copy number variation for 39,711 cDNAs, representing 29,619 human genes, across five hominoid species, including human. We identified 1,005 genes, either as isolated genes or in clusters positionally biased toward rearrangement-prone genomic regions, that produced relative hybridization signals unique to one or more of the hominoid lineages. Measured as a function of the evolutionary age of each lineage, genes showing copy number expansions were most pronounced in human (134) and include a number of genes thought to be involved in the structure and function of the brain. This work represents, to our knowledge, the first genome-wide gene-based survey of gene duplication across hominoid species. The genes identified here likely represent a significant majority of the major gene copy number changes that have occurred over the past 15 million years of human and great ape evolution and are likely to underlie some of the key phenotypic characteristics that distinguish these species.

  View details for PubMedID 15252450

  View details for PubMedCentralID PMC449870

• Lineage-specific gene duplication and loss in human and great ape evolution PLOS BIOLOGY Fortna, A., Kim, Y., MacLaren, E., Marshall, K., Hahn, G., Meltesen, L., Brenton, M., Hink, R., Burgers, S., Hernandez-Boussard, T., Karimpour-Fard, A., Glueck, D., McGavran, L., Berry, R., Pollack, J., Sikela, J. M. 2004; 2 (7): 937-954

  View details for DOI 10.1371/journal.pbio.0020207

  View details for Web of Science ID 000222977900012

• High-resolution array-based comparative genomic hybridization for distinguishing paraffin-embedded Spitz nevi and melanomas DIAGNOSTIC MOLECULAR PATHOLOGY Harvell, J. D., Kohler, S., Zhu, S., Hernandez-Boussard, T., Pollack, J. R., van de Rijn, M. 2004; 13 (1): 22-25

  Abstract

  Distinguishing between Spitz nevus and melanoma presents a challenging task for clinicians and pathologists. Most of these lesions are submitted entirely in formalin for histologic analysis by conventional hematoxylin and eosin-stained sections, and fresh-frozen material for ancillary studies is rarely collected. Molecular techniques, such as comparative genomic hybridization (CGH), can detect chromosomal alterations in tumor DNA that differ between these 2 lesions. This study investigated the ability of high-resolution array-based CGH to serve as a diagnostic test in distinguishing Spitz nevus and melanoma using DNA isolated from formalin-fixed and paraffin-embedded samples. Two of 3 Spitz nevi exhibited no significant chromosomal alterations, while the third showed gain of the short arm of chromosome 11p. The latter finding has previously been described as characteristic of a subset of Spitz nevi. The 2 melanomas showed multiple copy number alterations characteristic of melanoma such as 1q amplification and chromosome 9 deletion. This study has shown the utility of array-based CGH as a potential molecular test in distinguishing Spitz nevus from melanoma. The assay is capable of using archival paraffin-embedded, formalin-fixed material; is technically easier to perform as compared with conventional CGH; is more sensitive than conventional CGH in being able to detect focal alterations; and can detect copy number alterations even with relatively small amounts of lesional tissue as is typical of many skin tumors.

  View details for PubMedID 15163005

• Gene expression patterns and gene copy number changes in dermatofibrosarcoma protuberans AMERICAN JOURNAL OF PATHOLOGY Linn, S. C., West, R. B., Pollack, J. R., Zhu, S., Hernandez-Boussard, T., Nielsen, T. O., Rubin, B. P., Patel, R., Goldblum, J. R., Siegmund, D., Botstein, D., Brown, P. O., Gilks, C. B., van de Rijn, M. 2003; 163 (6): 2383-2395

  Abstract

  Dermatofibrosarcoma protuberans (DFSP) is an aggressive spindle cell neoplasm. It is associated with the chromosomal translocation, t(17:22), which fuses the COL1A1 and PDGFbeta genes. We determined the characteristic gene expression profile of DFSP and characterized DNA copy number changes in DFSP by array-based comparative genomic hybridization (array CGH). Fresh frozen and formalin-fixed, paraffin-embedded samples of DFSP were analyzed by array CGH (four cases) and DNA microarray analysis of global gene expression (nine cases). The nine DFSPs were readily distinguished from 27 other diverse soft tissue tumors based on their gene expression patterns. Genes characteristically expressed in the DFSPs included PDGF beta and its receptor, PDGFRB, APOD, MEOX1, PLA2R, and PRKCA. Array CGH of DNA extracted either from frozen tumor samples or from paraffin blocks yielded equivalent results. Large areas of chromosomes 17q and 22q, bounded by COL1A1 and PDGF beta, respectively, were amplified in DFSP. Expression of genes in the amplified regions was significantly elevated. Our data shows that: 1) DFSP has a distinctive gene expression profile; 2) array CGH can be applied successfully to frozen or formalin-fixed, paraffin-embedded tumor samples; 3) a characteristic amplification of sequences from chromosomes 17q and 22q, demarcated by the COL1A1 and PDGF beta genes, respectively, was associated with elevated expression of the amplified genes.

  View details for PubMedID 14633610

• Gene expression patterns in ovarian carcinomas MOLECULAR BIOLOGY OF THE CELL Schaner, M. E., Ross, D. T., Ciaravino, G., Sorlie, T., Troyanskaya, O., Diehn, M., Wang, Y. C., Duran, G. E., Sikic, T. L., Caldeira, S., Skomedal, H., Tu, I. P., Hernandez-Boussard, T., Johnson, S. W., O'Dwyer, P. J., Fero, M. J., Kristensen, G. B., Borresen-Dale, A. L., Hastie, T., Tibshirani, R., van de Rijn, M., Teng, N. N., Longacre, T. A., Botstein, D., Brown, P. O., Sikic, B. I. 2003; 14 (11): 4376-4386

  Abstract

  We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A comparison of the gene expression patterns in the ovarian cancers to published data of gene expression in breast cancers revealed a large number of differentially expressed genes. We identified a group of 62 genes that correctly classified all 125 breast and ovarian cancer specimens. Among the best discriminators more highly expressed in the ovarian carcinomas were PAX8 (paired box gene 8), mesothelin, and ephrin-B1 (EFNB1). Although estrogen receptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estrogen receptor in breast cancers, including GATA-3, LIV-1, and X-box binding protein 1, did not show a similar pattern of coexpression in the ovarian cancers.

  View details for PubMedID 12960427

• Identification of great ape and human lineage-specific genes using cDNA array-based CGH. 53rd Annual Meeting of the American-Society-of-Human-Genetics Sikela, J., Marshall, K., Kim, Y., MacLaren, E., Hahn, G., Meltesen, L., Hink, R., Burgers, S., Hernandez-Boussard, T., Karimpour-Fard, A., Glueck, D., McGavrin, L., Berry, R., Pollack, J. CELL PRESS. 2003: 431–31

  View details for Web of Science ID 000185599701532

• The Stanford Microarray Database: data access and quality assessment tools NUCLEIC ACIDS RESEARCH Gollub, J., Ball, C. A., Binkley, G., Demeter, J., Finkelstein, D. B., Hebert, J. M., Hernandez-Boussard, T., Jin, H., Kaloper, M., Matese, J. C., Schroeder, M., Brown, P. O., Botstein, D., Sherlock, G. 2003; 31 (1): 94-96

  Abstract

  The Stanford Microarray Database (SMD; http://genome-www.stanford.edu/microarray/) serves as a microarray research database for Stanford investigators and their collaborators. In addition, SMD functions as a resource for the entire scientific community, by making freely available all of its source code and providing full public access to data published by SMD users, along with many tools to explore and analyze those data. SMD currently provides public access to data from 3500 microarrays, including data from 85 publications, and this total is increasing rapidly. In this article, we describe some of SMD's newer tools for accessing public data, assessing data quality and for data analysis.

  View details for DOI 10.1093/nar/gkg078

  View details for Web of Science ID 000181079700020

  View details for PubMedID 12519956

  View details for PubMedCentralID PMC165525

• SOURCE: a unified genomic resource of functional annotations, ontologies, and gene expression data NUCLEIC ACIDS RESEARCH Diehn, M., Sherlock, G., Binkley, G., Jin, H., Matese, J. C., Hernandez-Boussard, T., Rees, C. A., Cherry, J. M., Botstein, D., Brown, P. O., Alizadeh, A. A. 2003; 31 (1): 219-223

  Abstract

  The explosion in the number of functional genomic datasets generated with tools such as DNA microarrays has created a critical need for resources that facilitate the interpretation of large-scale biological data. SOURCE is a web-based database that brings together information from a broad range of resources, and provides it in manner particularly useful for genome-scale analyses. SOURCE's GeneReports include aliases, chromosomal location, functional descriptions, GeneOntology annotations, gene expression data, and links to external databases. We curate published microarray gene expression datasets and allow users to rapidly identify sets of co-regulated genes across a variety of tissues and a large number of conditions using a simple and intuitive interface. SOURCE provides content both in gene and cDNA clone-centric pages, and thus simplifies analysis of datasets generated using cDNA microarrays. SOURCE is continuously updated and contains the most recent and accurate information available for human, mouse, and rat genes. By allowing dynamic linking to individual gene or clone reports, SOURCE facilitates browsing of large genomic datasets. Finally, SOURCEs batch interface allows rapid extraction of data for thousands of genes or clones at once and thus facilitates statistical analyses such as assessing the enrichment of functional attributes within clusters of genes. SOURCE is available at http://source.stanford.edu.

  View details for DOI 10.1093/nar/gkg014

  View details for Web of Science ID 000181079700050

  View details for PubMedID 12519986

  View details for PubMedCentralID PMC165461

• Integrating mutation data and structural analysis of the TP53 tumor, suppressor protein HUMAN MUTATION Martin, A. C., Facchiano, A. M., Cuff, A. L., Hernandez-Boussard, T., Olivier, M., Hainaut, P., Thornton, J. M. 2002; 19 (2): 149-164

  Abstract

  TP53 encodes p53, which is a nuclear phosphoprotein with cancer-inhibiting properties. In response to DNA damage, p53 is activated and mediates a set of antiproliferative responses including cell-cycle arrest and apoptosis. Mutations in the TP53 gene are associated with more than 50% of human cancers, and 90% of these affect p53-DNA interactions, resulting in a partial or complete loss of transactivation functions. These mutations affect the structural integrity and/or p53-DNA interactions, leading to the partial or complete loss of the protein's function. We report here the results of a systematic automated analysis of the effects of p53 mutations on the structure of the core domain of the protein. We found that 304 of the 882 (34.4%) distinct mutations reported in the core domain can be explained in structural terms by their predicted effects on protein folding or on protein-DNA contacts. The proportion of "explained" mutations increased to 55.6% when substitutions of evolutionary conserved amino acids were included. The automated method of structural analysis developed here may be applied to other frequently mutated gene mutations such as dystrophin, BRCA1, and G6PD.

  View details for Web of Science ID 000173628700008

  View details for PubMedID 11793474

• The Stanford Microarray Database NUCLEIC ACIDS RESEARCH Sherlock, G., Hernandez-Boussard, T., Kasarskis, A., Binkley, G., Matese, J. C., Dwight, S. S., Kaloper, M., Weng, S., Jin, H., Ball, C. A., Eisen, M. B., Spellman, P. T., Brown, P. O., Botstein, D., Cherry, J. M. 2001; 29 (1): 152-155

  Abstract

  The Stanford Microarray Database (SMD) stores raw and normalized data from microarray experiments, and provides web interfaces for researchers to retrieve, analyze and visualize their data. The two immediate goals for SMD are to serve as a storage site for microarray data from ongoing research at Stanford University, and to facilitate the public dissemination of that data once published, or released by the researcher. Of paramount importance is the connection of microarray data with the biological data that pertains to the DNA deposited on the microarray (genes, clones etc.). SMD makes use of many public resources to connect expression information to the relevant biology, including SGD [Ball,C.A., Dolinski,K., Dwight,S.S., Harris,M.A., Issel-Tarver,L., Kasarskis,A., Scafe,C.R., Sherlock,G., Binkley,G., Jin,H. et al. (2000) Nucleic Acids Res., 28, 77-80], YPD and WormPD [Costanzo,M.C., Hogan,J.D., Cusick,M.E., Davis,B.P., Fancher,A.M., Hodges,P.E., Kondu,P., Lengieza,C., Lew-Smith,J.E., Lingner,C. et al. (2000) Nucleic Acids Res., 28, 73-76], Unigene [Wheeler,D.L., Chappey,C., Lash,A.E., Leipe,D.D., Madden,T.L., Schuler,G.D., Tatusova,T.A. and Rapp,B.A. (2000) Nucleic Acids Res., 28, 10-14], dbEST [Boguski,M.S., Lowe,T.M. and Tolstoshev,C.M. (1993) Nature Genet., 4, 332-333] and SWISS-PROT [Bairoch,A. and Apweiler,R. (2000) Nucleic Acids Res., 28, 45-48] and can be accessed at http://genome-www.stanford.edu/microarray.

  View details for Web of Science ID 000166360300039

  View details for PubMedID 11125075

• Sources of bias in the detection and reporting of p53 mutations in human cancer: analysis of the IARC p53 mutation database 2nd International Meeting on Mutation Detection Hernandez-Boussard, T., Montesano, R., Hainaut, P. ELSEVIER SCIENCE BV. 1999: 229–33

  Abstract

  p53 gene encodes a transcription factor with tumor suppressive properties and to date, somatic mutation of this gene is the most common genetic event in human cancer. A relational database has been developed to facilitate the retrieval and analysis of these mutations at the International Agency for Research on Cancer (IARC) and it currently contains information on over 8000 individual tumors and cell lines. Many factors may influence the detection and reporting of mutations, including selection of tumor samples, study design, choice of methods, and quality control. There is also concern that several biases may affect the way data appear in the literature. Minimizing these biases is an essential methodological issue in the development of mutation data-bases. In this paper, we review and discuss these main sources of bias and make recommendations to authors in order to minimize bias in mutation detection and reporting.

  View details for Web of Science ID 000078934400015

  View details for PubMedID 10084119

• Analysis of somatic mutations of the p53 gene in human cancers: A tool to generate hypotheses about the natural history of cancer Workshop on the Use of Short-and Meduim-Term Tests for Carcinogens and Data on Genetic Effects in Carcinogenic Hazard Evaluation Hernandez-Boussard, T., Montesano, R., Hainaut, P. INT AGENCY RESEARCH CANCER. 1999: 43–53

  View details for Web of Science ID 000167234600003

  View details for PubMedID 10353383

• IARC p53 mutation database: A relational database to compile and analyze p53 mutations in human tumors and cell lines HUMAN MUTATION Hernandez-Boussard, T., Rodriguez-Tome, P., Montesano, R., Hainaut, P. 1999; 14 (1): 1-8

  Abstract

  The tumor suppressor p53 gene is the most frequently mutated gene in human cancer. To date, more than 10,000 mutations have been described in the literature, and these data are available in various electronic formats on the World Wide Web. Here we describe the structure and format of the different p53 datasets maintained and curated at the International Agency for Research on Cancer (IARC) in Lyon, France. These include p53 somatic mutations (more than 10,000 entries), p53 germline mutations (144 entries), and p53 polymorphisms (13 entries), with the somatic mutations organized into a relational database using AccessTM. The main features of these datasets are (1) controlled entry with standardized format and restricted vocabulary, (2) inclusion of annotations on individual characteristics and exposures, and (3) a classification of pathologies based on the International Classification of Diseases for Oncology (ICD-O). In addition, several interfaces have been developed to analyze the data in order to produce mutation spectra, codon analyses, or visualization of the mutation with the tertiary structure of the protein. All datasets and tools for analysis are available at http://www.iarc.fr/p53/homepage.

  View details for Web of Science ID 000081207100001

  View details for PubMedID 10447253

• A specific spectrum of p53 mutations in lung cancer from smokers: Review of mutations compiled in the IARC p53 database ENVIRONMENTAL HEALTH PERSPECTIVES Hernandez-Boussard, T. M., Hainaut, P. 1998; 106 (7): 385-391

  Abstract

  Mutations in the p53 gene are common in lung cancer. Using data from the the International Agency for Research on Cancer p53 mutation database (R1), we have analyzed the distribution and nature of p53 mutations in 876 lung tumors described in the literature. These analyses confirm that G to T transitions are the predominant type of p53 mutation in lung cancer from smokers. The most frequently mutated codons include 157, 158, 179, 248, 249, and 273, and several of them (157, 248, and 273) have been shown to correspond to sites of in vitro DNA adduct formation by metabolites of polycyclic aromatic hydrocarbons (PAHs) such as benzo(a)pyrene. Furthermore, most of the base changes at codons 248, 249, and 273 in lung cancer differ from those commonly observed at these codons in other cancers reported in the database. Thus, lung cancer from smokers shows a distinct, unique p53 mutation spectrum that is not observed in lung cancer from nonsmokers. These results further strengthen the association between active smoking, exposure to PAHs, and lung cancer. They also indicate that a different pattern of mutations occurs in nonsmokers, and this observation may help to identify other agents causally involved in lung cancer in nonsmokers.

  View details for Web of Science ID 000075380700018

  View details for PubMedID 9637795

• IARC Database of p53 gene mutations in human tumors and cell lines: updated compilation, revised formats and new visualisation tools NUCLEIC ACIDS RESEARCH Hainaut, P., Hernandez, T., Robinson, A., Rodriguez-Tome, P., Flores, T., Hollstein, M., Harris, C. C., Montesano, R. 1998; 26 (1): 205-213

  Abstract

  Since 1989, about 570 different p53 mutations have been identified in more than 8000 human cancers. A database of these mutations was initiated by M. Hollstein and C. C. Harris in 1990. This database originally consisted of a list of somatic point mutations in the p 53 gene of human tumors and cell lines, compiled from the published literature and made available in a standard electronic form. The database is maintained at the International Agency for Research on Cancer (IARC) and updated versions are released twice a year (January and July). The current version (July 1997) contains records on 6800 published mutations and will surpass the 8000 mark in the January 1998 release. The database now contains information on somatic and germline mutations in a new format to facilitate data retrieval. In addition, new tools are constructed to improve data analysis, such as a Mutation Viewer Java applet developed at the European Bioinformatics Institute (EBI) to visualise the location and impact of mutations on p53 protein structure. The database is available in different electronic formats at IARC (http://www.iarc. fr/p53/homepage.htm ) or from the EBI server (http://www.ebi.ac.uk ). The IARC p53 website also provides reports on database analysis and links with other p53 sites as well as with related databases. In this report, we describe the criteria for inclusion of data, the revised format and the new visualisation tools. We also briefly discuss the relevance of p 53 mutations to clinical and biological questions.

  View details for Web of Science ID 000071778900049

  View details for PubMedID 9399837