Dr. Adams is the inaugural Stanford Medicine Innovation Professor and Professor of Epidemiology and Population Health and of Medicine (Primary Care and Outcomes Research), as well as Associate Director for Health Equity and Community Engagement in the Stanford Cancer Institute. Focusing on racial and socioeconomic disparities in chronic disease treatment outcomes, Dr. Adams' interdisciplinary research seeks to evaluate the impact of changes in drug coverage policy on access to essential medications, understand the drivers of disparities in treatment adherence among insured populations, and test strategies for maximizing the benefits of treatment outcomes while minimizing harms through informed decision-making. Prior to joining Stanford School of Medicine, Dr. Adams was Associate Director for Health Care Delivery and Policy and a Research Scientist at the Kaiser Permanente Division of Research, as well as a Professor at the Bernard J. Tyson Kaiser Permanente School of Medicine. From 2000 to 2008, she was an Assistant Professor in the Department of Population Medicine (formerly Ambulatory Care and Prevention) at Harvard Medical School and Harvard Pilgrim Health care. She received her PhD in Health Policy and an MPP in Social Policy from Harvard University. She is Vice Chair of the Board of Directors for AcademyHealth and a former recipient of the John M. Eisenberg Excellence in Mentoring Award from Agency for Healthcare Research and Quality and an invited lecturer on racial disparities in health care in the 2014/2015 National Institute of Mental Health Director’s Innovation Speaker Series.
Professor, Epidemiology and Population Health
Associate Director, Stanford Cancer Institute (2021 - Present)
Boards, Advisory Committees, Professional Organizations
Member, Healthcare Delivery Research Program Advisory Board, National Cancer Institute (2016 - Present)
Member, Examining Diversity in Diversity, Recruitment, and Retention in Aging Research Advisory Board, University of Maryland School of Pharmacy--The Patients Program (2019 - Present)
Member, Stillman College Undergraduate Biomedical Academy Advisory Board (2019 - Present)
Member/Vice Chair, AcademyHealth (2020 - Present)
BA, University of Texas at Austin, Government (1992)
MPP, John F. Kennedy School of Government, Harvard University, Social Policy (1994)
PhD, Harvard University, Health Policy (1999)
Racial Disparities in COVID-19 Testing and Outcomes : Retrospective Cohort Study in an Integrated Health System.
Annals of internal medicine
Racial disparities exist in outcomes after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.To evaluate the contribution of race/ethnicity in SARS-CoV-2 testing, infection, and outcomes.Retrospective cohort study (1 February 2020 to 31 May 2020).Integrated health care delivery system in Northern California.Adult health plan members.Age, sex, neighborhood deprivation index, comorbid conditions, acute physiology indices, and race/ethnicity; SARS-CoV-2 testing and incidence of positive test results; and hospitalization, illness severity, and mortality.Among 3 481 716 eligible members, 42.0% were White, 6.4% African American, 19.9% Hispanic, and 18.6% Asian; 13.0% were of other or unknown race. Of eligible members, 91 212 (2.6%) were tested for SARS-CoV-2 infection and 3686 had positive results (overall incidence, 105.9 per 100 000 persons; by racial group, White, 55.1; African American, 123.1; Hispanic, 219.6; Asian, 111.7; other/unknown, 79.3). African American persons had the highest unadjusted testing and mortality rates, White persons had the lowest testing rates, and those with other or unknown race had the lowest mortality rates. Compared with White persons, adjusted testing rates among non-White persons were marginally higher, but infection rates were significantly higher; adjusted odds ratios [aORs] for African American persons, Hispanic persons, Asian persons, and persons of other/unknown race were 2.01 (95% CI, 1.75 to 2.31), 3.93 (CI, 3.59 to 4.30), 2.19 (CI, 1.98 to 2.42), and 1.57 (CI, 1.38 to 1.78), respectively. Geographic analyses showed that infections clustered in areas with higher proportions of non-White persons. Compared with White persons, adjusted hospitalization rates for African American persons, Hispanic persons, Asian persons, and persons of other/unknown race were 1.47 (CI, 1.03 to 2.09), 1.42 (CI, 1.11 to 1.82), 1.47 (CI, 1.13 to 1.92), and 1.03 (CI, 0.72 to 1.46), respectively. Adjusted analyses showed no racial differences in inpatient mortality or total mortality during the study period. For testing, comorbid conditions made the greatest relative contribution to model explanatory power (77.9%); race only accounted for 8.1%. Likelihood of infection was largely due to race (80.3%). For other outcomes, age was most important; race only contributed 4.5% for hospitalization, 12.8% for admission illness severity, 2.3% for in-hospital death, and 0.4% for any death.The study involved an insured population in a highly integrated health system.Race was the most important predictor of SARS-CoV-2 infection. After infection, race was associated with increased hospitalization risk but not mortality.The Permanente Medical Group, Inc.
View details for DOI 10.7326/M20-6979
View details for PubMedID 33556278
- Preventing Diabetes in High-Risk Patients: Time for a System-Level Approach to Disease Prevention JOURNAL OF GENERAL INTERNAL MEDICINE 2019; 34 (8): 1367–68
Targeted learning with daily EHR data
STATISTICS IN MEDICINE
2019; 38 (16): 3073–90
Electronic health records (EHR) data provide a cost- and time-effective opportunity to conduct cohort studies of the effects of multiple time-point interventions in the diverse patient population found in real-world clinical settings. Because the computational cost of analyzing EHR data at daily (or more granular) scale can be quite high, a pragmatic approach has been to partition the follow-up into coarser intervals of pre-specified length (eg, quarterly or monthly intervals). The feasibility and practical impact of analyzing EHR data at a granular scale has not been previously evaluated. We start filling these gaps by leveraging large-scale EHR data from a diabetes study to develop a scalable targeted learning approach that allows analyses with small intervals. We then study the practical effects of selecting different coarsening intervals on inferences by reanalyzing data from the same large-scale pool of patients. Specifically, we map daily EHR data into four analytic datasets using 90-, 30-, 15-, and 5-day intervals. We apply a semiparametric and doubly robust estimation approach, the longitudinal Targeted Minimum Loss-Based Estimation (TMLE), to estimate the causal effects of four dynamic treatment rules with each dataset, and compare the resulting inferences. To overcome the computational challenges presented by the size of these data, we propose a novel TMLE implementation, the "long-format TMLE," and rely on the latest advances in scalable data-adaptive machine-learning software, xgboost and h2o, for estimation of the TMLE nuisance parameters.
View details for DOI 10.1002/sim.8164
View details for Web of Science ID 000473655400011
View details for PubMedID 31025411
Disparities in knowledge and use of tobacco treatment among smokers in California following healthcare reform.
Preventive medicine reports
2019; 14: 100847
The Affordable Care Act (ACA) promised to narrow smoking disparities by expanding access to healthcare and mandating comprehensive coverage for tobacco treatment starting in 2014. We examined whether two years after ACA implementation disparities in receiving clinician advice to quit and smokers' knowledge and use of treatment resources remained. We conducted telephone interviews in 2016 with a stratified random sample of self-reported smokers newly enrolled in the Kaiser Permanente Northern California's (KPNC) integrated healthcare delivery system in 2014 (N = 491; 50% female; 53% non-white; 6% Spanish language). We used Poisson regression with robust standard errors to test whether sociodemographics, insurance type, comorbidities, smoking status in 2016 (former, light/nondaily [<5 cigarettes per day], daily), and preferred language (English or Spanish) were associated with receiving clinician advice to quit and knowledge and use of tobacco treatment. We included an interaction between smoking status and language to test whether the relation between smoking status and key outcomes varied with preferred language. Overall, 80% of respondents received clinician advice to quit, 84% knew that KPNC offers cessation counseling, 54% knew that cessation pharmacotherapy is free, 54% used pharmacotherapy, and 6% used counseling. In multivariate models, Spanish-speaking light/nondaily smokers had significantly lower rates of all outcomes, while there was no association with other demographic and clinical characteristics. Following ACA implementation, most smokers newly enrolled in KPNC received clinician advice to quit and over half used pharmacotherapy, yet counseling utilization was low. Spanish-language outreach efforts and treatment services are recommended, particularly for adults who are light/nondaily smokers.
View details for PubMedID 31024786
Clinical Response to Real-Time Patient-Reported Diabetic Peripheral Neuropathy Symptoms.
The Permanente journal
To assess clinician response to real-time patient-reported data about diabetic peripheral neuropathy (DPN) symptoms, we analyzed DPN diagnosis and treatment patterns after administration of a 4-question symptom questionnaire in a large vertically integrated health care system.Retrospective cohort study to analyze data from 160,852 patients screened for DPN symptoms from April 2012 to March 2014. Electronic medical record data were used to study changes in DPN diagnosis, treatment initiation, and treatment intensification. We used logistic regression to study the association of patient characteristics with the odds of clinical response.Of patients queried, 50,684 (31.5%) reported symptoms. Patients reporting DPN symptoms experienced a greater increase in new DPN diagnoses (16 percentage points; p < 0.0001) and medication use (4 percentage points; p < 0.0001) compared with those denying symptoms. Among patients reporting symptoms, women and nonwhite patients were less likely to receive a DPN diagnosis, whereas older patients were more likely to receive a DPN diagnosis. Overall, patients who were older, were Asian (hazard ratio = 0.67, 95% confidence interval = 0.63-0.77), and had lower socioeconomic status (hazard ratio = 0.89, 95% confidence interval = 0.80-0.99) were less likely to be treated. However, these racial and socioeconomic differences were not statistically significant for patients with preexisting DPN diagnoses.Patients' real-time reports of DPN symptoms were associated with increased clinical activity. Patient- and clinician-level factors associated with the likelihood of receiving a DPN diagnosis need further study because a formal diagnosis may be associated with more equitable treatment.
View details for DOI 10.7812/TPP/18-180
View details for PubMedID 31050645
View details for PubMedCentralID PMC6499113
Automated symptom and treatment side effect monitoring for improved quality of life among adults with diabetic peripheral neuropathy in primary care: a pragmatic, cluster, randomized, controlled trial
2019; 36 (1): 52–61
To evaluate the effectiveness of automated symptom and side effect monitoring on quality of life among individuals with symptomatic diabetic peripheral neuropathy.We conducted a pragmatic, cluster randomized controlled trial (July 2014 to July 2016) within a large healthcare system. We randomized 1834 primary care physicians and prospectively recruited from their lists 1270 individuals with neuropathy who were newly prescribed medications for their symptoms. Intervention participants received automated telephone-based symptom and side effect monitoring with physician feedback over 6 months. The control group received usual care plus three non-interactive diabetes educational calls. Our primary outcomes were quality of life (EQ-5D) and select symptoms (e.g. pain) measured 4-8 weeks after starting medication and again 8 months after baseline. Process outcomes included receiving a clinically effective dose and communication between individuals with neuropathy and their primary care provider over 12 months. Interviewers collecting outcome data were blinded to intervention assignment.Some 1252 participants completed the baseline measures [mean age (sd): 67 (11.7), 53% female, 57% white, 8% Asian, 13% black, 20% Hispanic]. In total, 1179 participants (93%) completed follow-up (619 control, 560 intervention). Quality of life scores (intervention: 0.658 ± 0.094; control: 0.653 ± 0.092) and symptom severity were similar at baseline. The intervention had no effect on primary [EQ-5D: -0.002 (95% CI -0.01, 0.01), P = 0.623; pain: 0.295 (-0.75, 1.34), P = 0.579; sleep disruption: 0.342 (-0.18, 0.86), P = 0.196; lower extremity functioning: -0.079 (-1.27, 1.11), P = 0.896; depression: -0.462 (-1.24, 0.32); P = 0.247] or process outcomes.Automated telephone monitoring and feedback alone were not effective at improving quality of life or symptoms for people with symptomatic diabetic peripheral neuropathy.ClinicalTrials.gov (NCT02056431).
View details for DOI 10.1111/dme.13840
View details for Web of Science ID 000454409900006
View details for PubMedID 30343489
View details for PubMedCentralID PMC7236318
Patterns of medication adherence in a multi-ethnic cohort of prevalent statin users diagnosed with breast, prostate, or colorectal cancer
JOURNAL OF CANCER SURVIVORSHIP
2018; 12 (6): 794–802
To investigate the implications of a cancer diagnosis on medication adherence for pre-existing comorbid conditions, we explored statin adherence patterns prior to and following a new diagnosis of breast, colorectal, or prostate cancer among a multi-ethnic cohort.We identified adults enrolled at Kaiser Permanente Northern California who were prevalent statin medication users, newly diagnosed with breast, colorectal, or prostate cancer between 2000 and 2012. Statin adherence was measured using the proportion of days covered (PDC) during the 2-year pre-cancer diagnosis and the 2-year post-cancer diagnosis. Adherence patterns were assessed using generalized estimating equations, for all cancers combined and stratified by cancer type and race/ethnicity, adjusted for demographic, clinical, and tumor characteristics.Among 10,177 cancer patients, statin adherence decreased from pre- to post-cancer diagnosis (adjusted odds ratio (ORadj):0.91, 95% confidence interval (95% CI):0.88-0.94). Statin adherence decreased from pre- to post-cancer diagnosis among breast (ORadj:0.94, 95% CI:0.90-0.99) and colorectal (ORadj:0.79, 95% CI:0.74-0.85) cancer patients. No difference in adherence was observed among prostate cancer patients (ORadj:1.01, 95% CI:0.97-1.05). Prior to cancer diagnosis, adherence to statins was generally higher among non-Hispanic whites and multi-race patients than other groups. However, statin adherence after diagnosis decreased only among these two populations (ORadj:0.85, 95% CI:0.85-0.92 and ORadj:0.86, 95% CI:0.76-0.97), respectively.We found substantial variation in statin medication adherence following diagnosis by cancer type and race/ethnicity among a large cohort of prevalent statin users in an integrated health care setting.Improving our understanding of comorbidity management and polypharmacy across diverse cancer patient populations is warranted to develop tailored interventions that improve medication adherence and reduce disparities in health outcomes.
View details for DOI 10.1007/s11764-018-0716-6
View details for Web of Science ID 000449874500008
View details for PubMedID 30338462
View details for PubMedCentralID PMC6238633
Evaluating the Impact of Eliminating Copayments for Tobacco Cessation Pharmacotherapy
2018; 56 (11): 912–18
We examined the impact of the Affordable Care Act-mandated elimination of tobacco cessation pharmacotherapy (TCP) copayments on patient use of TCP, overall and by income.Electronic health record data captured any and combination (eg, nicotine gum plus patch) TCP use among adult smokers newly enrolled in Kaiser Permanente Northern California (KPNC). KPNC eliminated TCP copayments in 2015. We included current smokers newly enrolled in the first 6 months of 2014 (before copayment elimination, N=16,199) or 2015 (after elimination, N=16,469). Multivariable models estimated 1-year changes in rates of any TCP fill, and of combination TCP fill, and tested for differences by income (<$50k, $50≥75k, ≥$75k). Through telephone surveys in 2016 with a subset of smokers newly enrolled in 2014 (n=306), we assessed barriers to TCP use, with results stratified by income.Smokers enrolled in KPNC in 2015 versus 2014 were more likely to have a TCP fill (9.1% vs. 8.2%; relative risk, 1.19; 95% confidence interval, 1.11-1.27), and combination TCP fill, among those with any fill (42.3% vs. 37.9%; relative risk, 1.12; 95% confidence interval, 1.02-1.23); findings were stronger for low-income smokers. Low-income patients (<$50k) were less likely to report that clinicians discussed smoking treatments with them (58%) compared with higher income smokers ($50≥75k, 67%; ≥$75k, 83%), and were less aware that TCP was free (40% vs. 53% and 69%, respectively, P-values<0.05).The Affordable Care Act's copayment elimination was associated with a modest increase in TCP use and a greater effect among low-income smokers. Uptake may have been enhanced if promoted to patients directly and via providers.
View details for PubMedID 30234768
Examining the role of access to care: Racial/ethnic differences in receipt of resection for early-stage non-small cell lung cancer among integrated system members and non-members
2018; 125: 51–56
To examine the role of uniform access to care in reducing racial/ethnic disparities in receipt of resection for early stage non-small cell lung cancer (NSCLC) by comparing integrated health system member patients to demographically similar non-member patients.Using data from the California Cancer Registry, we conducted a retrospective cohort study of patients from four racial/ethnic groups (White, Black, Hispanic, Asian/Pacific Islander), aged 21-80, with a first primary diagnosis of stage I or II NSCLC between 2004 and 2011, in counties served by Kaiser Permanente Northern California (KPNC) at diagnosis. Our cohort included 1565 KPNC member and 4221 non-member patients. To examine the relationship between race/ethnicity and receipt of surgery stratified by KPNC membership, we used modified Poisson regression to calculate risk ratios (RR) adjusted for patient demographic and tumor characteristics.Black patients were least likely to receive surgery regardless of access to integrated care (64-65% in both groups). The magnitude of the black-white difference in the likelihood of surgery receipt was similar for members (RR: 0.82, 95% CI: 0.73-0.93) and non-members (RR: 0.86, 95% CI: 0.80-0.94). Among members, roughly equal proportions of Hispanic and White patients received surgery; however, among non-members, Hispanic patients were less likely to receive surgery (non-members, RR: 0.93, 95% CI: 0.86-1.00; members, RR: 0.98, 95% CI: 0.89-1.08).Disparities in surgical treatment for NSCLC were not reduced through integrated health system membership, suggesting that factors other than access to care (e.g., patient-provider communication) may underlie disparities. Future research should focus on identifying such modifiable factors.
View details for DOI 10.1016/j.lungcan.2018.09.006
View details for Web of Science ID 000450378500008
View details for PubMedID 30429038
View details for PubMedCentralID PMC6242353
Disparities in Prostate, Lung, Breast, and Colorectal Cancer Survival and Comorbidity Status among Urban American Indians and Alaskan Natives
2017; 77 (23): 6770–76
Cancer is the second leading cause of death among American Indians and Alaskan Natives (AIAN), although cancer survival information in this population is limited, particularly among urban AIAN. In this retrospective cohort study, we compared all-cause and prostate, breast, lung, and colorectal cancer-specific mortality among AIAN (n = 582) and non-Hispanic white (NHW; n = 82,696) enrollees of Kaiser Permanente Northern California (KPNC) diagnosed with primary invasive breast, prostate, lung, or colorectal cancer from 1997 to 2015. Tumor registry and other electronic health records provided information on sociodemographic, comorbidity, tumor, clinical, and treatment characteristics. Cox regression models were used to estimate adjusted survival curves and hazard ratios (HR) with 95% confidence intervals (CI). AIAN had a significantly higher comorbidity burden compared with NHW (P < 0.05). When adjusting for patient, disease characteristics, and Charlson comorbidity scores, all-cause mortality and cancer-specific mortality were significantly higher for AIAN than NHW patients with breast cancer (HR, 1.47; 95% CI, 1.13-1.92) or with prostate cancer (HR, 1.87; 95% CI, 1.14-3.06) but not for AIAN patients with lung and colorectal cancer. Despite approximately equal access to preventive services and cancer care in this setting, we found higher mortality for AIAN than NHW with some cancers, and a greater proportion of AIAN cancer patients with multiple comorbid conditions. This study provides severely needed information on the cancer experience of the 71% of AIANs who live in urban areas and access cancer care outside of the Indian Health Services, from which the vast majority of AIAN cancer information comes. Cancer Res; 77(23); 6770-6. ©2017 AACR.
View details for DOI 10.1158/0008-5472.CAN-17-0429
View details for Web of Science ID 000416854100025
View details for PubMedID 29187399
View details for PubMedCentralID PMC5728425
Effects of Transitioning to Medicare Part D on Access to Drugs for Medical Conditions among Dual Enrollees with Cancer
VALUE IN HEALTH
2017; 20 (10): 1345–54
To evaluate the impact of transitioning from Medicaid to Medicare Part D drug coverage on the use of noncancer treatments among dual enrollees with cancer.We leveraged a representative 5% national sample of all fee-for-service dual enrollees in the United States (2004-2007) to evaluate the impact of the removal of caps on the number of reimbursable prescriptions per month (drug caps) under Part D on 1) prevalence and 2) average days' supply dispensed for antidepressants, antihypertensives, and lipid-lowering agents overall and by race (white and black).The removal of drug caps was associated with increased use of lipid-lowering medications (days' supply 3.63; 95% confidence interval [CI] 1.57-5.70). Among blacks in capped states, we observed increased use of lipid-lowering therapy (any use 0.08 percentage points; 95% CI 0.05-0.10; and days' supply 4.01; 95% CI 2.92-5.09) and antidepressants (days' supply 2.20; 95% CI 0.61-3.78) and increasing trends in antihypertensive use (any use 0.01 percentage points; 95% CI 0.004-0.01; and days' supply 1.83; 95% CI 1.25-2.41). The white-black gap in the use of lipid-lowering medications was immediately reduced (-0.09 percentage points; 95% CI -0.15 to -0.04). We also observed a reversal in trends toward widening white-black differences in antihypertensive use (level -0.08 percentage points; 95% CI -0.12 to -0.05; and trend -0.01 percentage points; 95% CI -0.02 to -0.01) and antidepressant use (-0.004 percentage points; 95% CI -0.01 to -0.0004).Our findings suggest that the removal of drug caps under Part D had a modest impact on the treatment of hypercholesterolemia overall and may have reduced white-black gaps in the use of lipid-lowering and antidepressant therapies.
View details for DOI 10.1016/j.jval.2017.05.023
View details for Web of Science ID 000419245600014
View details for PubMedID 29241894
View details for PubMedCentralID PMC5734096
Association of the Affordable Care Act With Smoking and Tobacco Treatment Utilization Among Adults Newly Enrolled in Health Care
2017; 55 (5): 535–41
To examine rates of smoking and tobacco treatment utilization by insurance coverage status (Medicaid, commercial, exchange) among newly enrolled patients in the post Affordable Care Act (ACA) era.We examined new members who enrolled in Kaiser Permanente Northern California through Medicaid, the California exchange, or nonexchange commercial plans (N=122,298) in the first 6 months of 2014 following ACA implementation. We compared these groups on smoking prevalence and tested whether smokers in each group differed on sociodemographic characteristics and in their utilization of tobacco treatment (pharmacotherapy and counseling) in 2014.Smoking prevalence was higher among Medicaid (22%) than exchange (13%) or commercial (12%) patients (P<0.0001). Controlling for key sociodemographic and clinical characteristics, Medicaid (odds ratio, 1.49; 95% confidence interval, 1.29-1.73) smokers had greater odds of tobacco treatment use than commercial smokers. Other groups at risk for underuse included men, younger patients, Asians, and Latinos.In this cohort of newly enrolled patients after ACA implementation, Medicaid patients were more likely to be smokers compared with exchange and commercial patients, but they were also more likely to use tobacco treatment. Low tobacco treatment use among exchange and commercial plan smokers, as well as younger men, Asians and Latinos poses a significant obstacle to improving public health and additional targeted outreach strategies may be needed to engage these patients with available health services.
View details for DOI 10.1097/MLR.0000000000000712
View details for Web of Science ID 000401330800014
View details for PubMedID 28288073
View details for PubMedCentralID PMC5407463
Identification of the Joint Effect of a Dynamic Treatment Intervention and a Stochastic Monitoring Intervention Under the No Direct Effect Assumption
JOURNAL OF CAUSAL INFERENCE
2017; 5 (1)
The management of chronic conditions is characterized by frequent re-assessment of therapy decisions in response to the patient's changing condition over the course of the illness. Evidence most suitable to inform care thus often concerns the contrast of adaptive treatment strategies that repeatedly personalize treatment decisions over time using the latest accumulated data available from the patient's previous clinic visits such as laboratory exams (e.g., hemoglobin A1c measurements in diabetes care). The frequency at which such information is monitored implicitly defines the causal estimand that is typically evaluated in an observational or randomized study of such adaptive treatment strategies. Analytic control of monitoring with standard estimation approaches for time-varying interventions can therefore not only improve study generalizibility but also inform the optimal timing of clinical surveillance. Valid inference with these estimators requires the upholding of a positivity assumption that can hinder their applicability. To potentially weaken this requirement for monitoring control, we introduce identifiability results that will facilitate the derivation of alternate estimators of effects defined by general joint treatment and monitoring interventions in the context of time-to-event outcomes. These results are developed based on the nonparametric structural equation modeling framework using a no direct effect assumption originally introduced in a prior paper that inspired this work. The relevance and scope of the results presented here are illustrated with examples in diabetes comparative effectiveness research.
View details for DOI 10.1515/jci-2016-0015
View details for Web of Science ID 000405994900005
View details for PubMedID 29238650
View details for PubMedCentralID PMC5724814
A Learning Behavioral Health Care System: Opportunities to Enhance Research
2016; 67 (9): 1019–22
Sweeping changes in health care financing combined with the increased use of technology across health care systems are making it possible to address long-standing challenges to the behavioral health services delivery system. This Open Forum outlines opportunities and challenges facing health services researchers in this rapidly changing landscape. Inspired by a 2012 report by the Institute of Medicine, the authors discuss innovative research endeavors, promising study designs, and challenges involved in integrating high-impact behavioral health services research within a learning behavioral health care framework. The Open Forum concludes with a discussion of the critical next steps in this process: building consensus around common metrics for high-quality care, relevant outcomes, and contextual factors; connecting researchers to community and clinical settings; creating a data commons to pool information across sites; and designing and evaluating evidence-based decision support tools to drive improved care and outcomes.
View details for DOI 10.1176/appi.ps.201500180
View details for Web of Science ID 000388267600014
View details for PubMedID 27133723
The Diabetes Telephone Study: Design and challenges of a pragmatic cluster randomized trial to improve diabetic peripheral neuropathy treatment
2016; 13 (3): 286–93
Challenges to effective pharmacologic management of symptomatic diabetic peripheral neuropathy include the limited effectiveness of available medicines, frequent side effects, and the need for ongoing symptom assessment and treatment titration for maximal effectiveness. We present here the rationale and implementation challenges of the Diabetes Telephone Study, a randomized trial designed to improve medication treatment, titration, and quality of life among patients with symptomatic diabetic peripheral neuropathy.We implemented a pragmatic cluster randomized controlled trial to test the effectiveness of an automated interactive voice response tool designed to provide physicians with real-time patient-reported data about responses to newly prescribed diabetic peripheral neuropathy medicines. A total of 1834 primary care physicians treating patients in the diabetes registry at Kaiser Permanente Northern California were randomized into the intervention or control arm. In September 2014, we began identification and recruitment of patients assigned to physicians in the intervention group who receive three brief interactive calls every 2 months after a medication is prescribed to alleviate diabetic peripheral neuropathy symptoms. These calls provide patients with the opportunity to report on symptoms, side effects, self-titration of medication dose and overall satisfaction with treatment. We plan to compare changes in self-reported quality of life between the intervention group and patients in the control group who receive three non-interactive automated educational phone calls.Successful implementation of this clinical trial required robust stakeholder engagement to help tailor the intervention and to address pragmatic concerns such as provider time constraints. As of 27 October 2015, we had screened 2078 patients, 1447 of whom were eligible for participation. We consented and enrolled 1206 or 83% of those eligible. Among those enrolled, 53% are women and the mean age is 67 (standard deviation = 12) years. The racial ethnic make-up is 56% White, 8% Asian, 13% Black or African American, and 19% Hispanic or Latino.Innovative strategies are needed to guide improvements in healthcare delivery for patients with symptomatic diabetic peripheral neuropathy. This trial aims to assess whether real-time collection and clinical feedback of patient treatment experiences can reduce patient symptom burden. Implementation of a clinical trial closely involving clinical care required researchers to partner with clinicians. If successful, this intervention provides a critical information feedback loop that would optimize diabetic peripheral neuropathy medication titration through widely available interactive voice response technology.
View details for DOI 10.1177/1740774516631530
View details for Web of Science ID 000375689500006
View details for PubMedID 27034455
View details for PubMedCentralID PMC7261503
Effects of Eliminating Drug Caps on Racial Differences in Antidepressant Use Among Dual Enrollees With Diabetes and Depression
2015; 37 (3): 597–609
Black patients with diabetes are at greater risk of underuse of antidepressants even when they have equal access to health insurance. This study aimed to evaluate the impact of removing a significant financial barrier to prescription medications (drug caps) on existing black-white disparities in antidepressant treatment rates among patients with diabetes and comorbid depression.We used an interrupted time series with comparison series design and a 5% representative sample of all fee-for-service Medicare and Medicaid dual enrollees to evaluate the removal of drug caps on monthly antidepressant treatment rates. We evaluated the impact of drug cap removal on racial gaps in treatment by modeling the month-to-month white-black difference in use within age strata (younger than 65 years of age or 65 years of age or older). We compared adult dual enrollees with diabetes and comorbid depression living in states with strict drug caps (n = 221) and those without drug caps (n = 1133) before the policy change. Our primary outcome measures were the proportion of patients with any antidepressant use per month and the mean standardized monthly doses (SMDs) of antidepressants per month.The removal of drug caps in strict drug cap states was associated with a sudden increase in the proportion of patients treated for depression (4 percentage points; 95% CI, 0.03-0.05, P < 0.0001) and in the intensity of antidepressant use (SMD: 0.05; 95% CI, 0.03-0.07, P < 0.001). Although antidepressant treatment rates increased for both white and black patients, the white-black treatment gap increased immediately after Part D (0.04 percentage points; 95% CI, 0.01-0.08) and grew over time (0.04 percentage points per month; 95% CI, 0.002-0.01; P < 0.001).Policies that remove financial barriers to medications may increase depression treatment rates among patients with diabetes overall while exacerbating treatment disparities. Tailored outreach may be needed to address nonfinancial barriers to mental health services use among black patients with diabetes.
View details for DOI 10.1016/j.clinthera.2014.12.011
View details for Web of Science ID 000353252300014
View details for PubMedID 25620439
View details for PubMedCentralID PMC4390474
Changes in Use of Lipid-lowering Medications Among Black and White Dual Enrollees With Diabetes Transitioning From Medicaid to Medicare Part D Drug Coverage
2014; 52 (8): 695–703
The use of lipid-lowering agents is suboptimal among dual enrollees, particularly blacks.To determine whether the removal of restrictive drug caps under Medicare Part D reduced racial differences among dual enrollees with diabetes.An interrupted time series with comparison series design (ITS) cohort study.A total of 8895 black and white diabetes patients aged 18 years and older drawn from a nationally representative sample of fee-for-service dual enrollees (January 2004-December 2007) in states with and without drug caps before Part D.We examined the monthly (1) proportion of patients with any use of lipid-lowering therapies; and (2) intensity of use. Stratification measures included age (less than 65, 65 y and older), race (white vs. black), and sex.At baseline, lipid-lowering drug use was higher in no drug cap states (drug cap: 54.0% vs. nondrug cap: 66.8%) and among whites versus blacks (drug cap: 58.5% vs. 44.9%, no drug cap: 68.4% vs. 61.9%). In strict drug cap states only, Part D was associated with an increase in the proportion with any use [nonelderly: +0.07 absolute percentage points (95% confidence interval, 0.06-0.09), P<0.001; elderly: +0.08 (0.06-0.10), P<0.001] regardless of race. However, we found no evidence of a change in the white-black gap in the proportion of users despite the removal of a significant financial barrier.Medicare Part D was associated with increased use of lipid-lowering drugs, but racial gaps persisted. Understanding non-coverage-related barriers is critical in maximizing the potential benefits of coverage expansions for disparities reduction.
View details for DOI 10.1097/MLR.0000000000000159
View details for Web of Science ID 000339332900005
View details for PubMedID 24988304
View details for PubMedCentralID PMC4135389
- The Top Patient Safety Strategies That Can Be Encouraged for Adoption Now ANNALS OF INTERNAL MEDICINE 2013; 158 (5): 365-+
Health System Factors and Antihypertensive Adherence in a Racially and Ethnically Diverse Cohort of New Users
JAMA INTERNAL MEDICINE
2013; 173 (1): 54–61
The purpose of this study was to identify potential health system solutions to suboptimal use of antihypertensive therapy in a diverse cohort of patients initiating treatment.Using a hypertension registry at Kaiser Permanente Northern California, we conducted a retrospective cohort study of 44 167 adults (age, ≥18 years) with hypertension who were new users of antihypertensive therapy in 2008. We used multivariate logistic regression analysis to model the relationships between race/ethnicity, specific health system factors, and early nonpersistence (failing to refill the first prescription within 90 days) and nonadherence (<80% of days covered during the 12 months following the start of treatment), respectively, controlling for sociodemographic and clinical risk factors.More than 30% of patients were early nonpersistent and 1 in 5 were nonadherent to therapy. Nonwhites were more likely to exhibit both types of suboptimal medication-taking behavior compared with whites. In logistic regression models adjusted for sociodemographic, clinical, and health system factors, nonwhite race was associated with early nonpersistence (black: odds ratio, 1.56 [95% CI, 1.43-1.70]; Asian: 1.40 [1.29-1.51]; Hispanic: 1.46 [1.35-1.57]) and nonadherence (black: 1.55 [1.37-1.77]; Asian: 1.13 [1.00-1.28]; Hispanic: 1.46 [1.31-1.63]). The likelihood of early nonpersistence varied between Asians and Hispanics by choice of first-line therapy. In addition, racial and ethnic differences in nonadherence were appreciably attenuated when medication co-payment and mail-order pharmacy use were accounted for in the models.Racial/ethnic differences in medication-taking behavior occur early in the course of treatment. However, health system strategies designed to reduce patient co-payments, ease access to medications, and optimize the choice of initial therapy may be effective tools in narrowing persistent gaps in the use of these and other clinically effective therapies.
View details for DOI 10.1001/2013.jamainternmed.955
View details for Web of Science ID 000317238800013
View details for PubMedID 23229831
View details for PubMedCentralID PMC5105889
Advancing the Science of Patient Safety
ANNALS OF INTERNAL MEDICINE
2011; 154 (10): 693-W248
Despite a decade's worth of effort, patient safety has improved slowly, in part because of the limited evidence base for the development and widespread dissemination of successful patient safety practices. The Agency for Healthcare Research and Quality sponsored an international group of experts in patient safety and evaluation methods to develop criteria to improve the design, evaluation, and reporting of practice research in patient safety. This article reports the findings and recommendations of this group, which include greater use of theory and logic models, more detailed descriptions of interventions and their implementation, enhanced explanation of desired and unintended outcomes, and better description and measurement of context and of how context influences interventions. Using these criteria and measuring and reporting contexts will improve the science of patient safety.
View details for DOI 10.1059/0003-4819-154-10-201105170-00011
View details for Web of Science ID 000290620300019
View details for PubMedID 21576538
Reliability of new measures of cost-related medication nonadherence
2008; 46 (4): 444–48
Although several national studies have attempted to measure medication nonadherence due to cost in cross-sectional studies of the elderly and disabled, little information exists on the psychometric properties of these measures over time.Examine the test-retest reliability of several recently published measures of cost-related medication nonadherence, among elderly community.We developed a questionnaire and tested the reliability of measures of cost-related medication nonadherence and general cost-reduction strategies in a sample of 185 elderly in eastern Massachusetts surveyed twice (1-2 months apart). General and medicine-specific cost-related nonadherence measures included: failure to fill or delayed refilling of a prescription due to its cost, skipping doses, or taking smaller doses to make a medicine last longer. We also tested the reliability of reported drug cost-reduction strategies, such as: using generic drugs; purchasing prescriptions via mail/internet or from outside the United States; receiving prescription samples from a doctor; and spending less on food, heat, or other basic needs to afford medicines. We used the McNemar test, a matched pair chi analysis, and Kappa statistics to examine the association of responses within patients between identical items asked at 2 points in time.Kappa statistics for test-retest reliability ranged from 0.6 to 0.9 for all but one measure of cost-related nonadherence, and McNemar test statistics indicated no systematic change in the measures over time.The estimated test-retest reliability of the measures of cost-related medication nonadherence were generally high. The measures have been integrated into the nationally representative Medicare Current Beneficiary Survey (MCBS), an ongoing national panel survey of Medicare beneficiaries, which will allow researchers and policymakers to identify changes in cost-related nonadherence among disabled and elderly Medicare beneficiaries.
View details for DOI 10.1097/MLR.0b013e31815dc59a
View details for Web of Science ID 000254571100016
View details for PubMedID 18362826