Dr. Kathleen Kan is a fellowship-trained pediatric urologist with a clinical practice based at LPCH and additional outreach programs in the South Bay. Her current practice includes general, endoscopic and complex reconstructive procedures and a clinical counseling interest in kidney stone disease and differences in sexual differentiation. She currently serves as the Associate Program Director of the Urology residency program.
Her current research is focused on understanding why health elementary schoolchildren develop new bladder and bowel problems.
- Pediatric Urology
Clinical Assistant Professor, Urology
Board Certification: American Board of Urology, Pediatric Urology (2021)
Medical Education: Icahn School of Medicine at Mount Sinai (2012) NY
Fellowship: Stanford University Dept of Urology (2019) CA
Residency: Icahn School of Medicine at Mount Sinai Urology Residency (2017) NY
Internship: Icahn School of Medicine at Mount Sinai Hospital General Surgery Residency (2013) NY
M.D., Icahn School of Medicine at Mount Sinai
B.A., Columbia University - Columbia College, Anthropology
Curriculum and Instruction
Equity in Education
Parents and Family Issues
Independent Studies (4)
- Community Health and Prevention Research Master's Thesis Writing
CHPR 399 (Win, Spr, Sum)
- Curricular Practical Training and Internship
CHPR 290 (Win, Spr)
- Directed Reading
CHPR 299 (Spr)
- Medical Scholars Research
UROL 370 (Sum)
- Community Health and Prevention Research Master's Thesis Writing
Graduate and Fellowship Programs
Pediatric Urology (Fellowship Program)
- Reply by Authors. The Journal of urology 2021: 101097JU000000000000231202
De Novo Urinary Storage Symptoms are Common after Radical Prostatectomy: Incidence, Natural History and Predictors.
The Journal of urology
INTRODUCTION: After RP, clinical complaints of new onset storage symptoms may be related to anastomotic strictures or as accommodation for stress urinary incontinence; however, a subgroup of men will experience de novo storage symptoms in the absence of stricture or stress urinary incontinence. As therapies for OAB have improved, we sought to assess the prevalence, natural history, and risk factors of de novo storage dysfunction in continent men.METHODS: We retrospectively analyzed urinary symptom questionnaires completed by patients who were continent prior to RP and did not have post-operative anastomotic strictures at our institution from 2002-2019. De novo storage dysfunction, assessed as new onset or worsening urgency or frequency was assessed at 6, 12, 18 and 24 months after RP and association between it and patient and preoperative factors determined.RESULTS: A total of 2619 patients were included in the final analysis. An initial 34% of patients reported de novo storage symptoms at 6 months, which decreased to 26% at later follow-up. We found evidence that minimally invasive surgery and nonwhite race were associated with reporting worsening symptoms. The association between post-operative hematoma and worsening symptoms was less conclusive but was of clear clinical relevance (OR 3.15; 95% CI 1.04, 9.54; p-value=0.042).CONCLUSION: A significant number of RP patients experience de novo storage symptoms. Patients who underwent MIS surgery are at higher risk. At risk patients should be counseled on the incidence of de novo storage symptoms and offered early treatment per OAB guidelines.
View details for DOI 10.1097/JU.0000000000002312
View details for PubMedID 34694923
TIME TO SPONTANEOUS RESOLUTION IN INFANT STONE DISEASE
LIPPINCOTT WILLIAMS & WILKINS. 2021: E831
View details for Web of Science ID 000693689000163
- Comparison of orthogonal NLP methods for clinical phenotyping and assessment of bone scan utilization among prostate cancer patients JOURNAL OF BIOMEDICAL INFORMATICS 2019; 94
Comparison of Orthogonal NLP Methods for Clinical Phenotyping and Assessment of Bone Scan Utilization among Prostate Cancer Patients.
Journal of biomedical informatics
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
Clinical and Metabolic Correlates of Calcium Oxalate Stone Subtypes: Implications for Etiology and Management.
Journal of endourology
Calcium oxalate (CaOx) is the predominate component within renal calculi and can be divided into two subtypes: CaOx-monohydrate (COM) and CaOx-dihydrate (COD). COM and COD form in differing urinary environments which suggest differential underlying metabolic abnormalities associated with each subtype. We compared clinical and metabolic findings in CaOx stone-formers to delineate factors differentiating COD and COM stone formers and the implication this holds in terms of etiology and treatment.We identified CaOx stone-formers that had passed their stones or had undergone endoscopic extraction between October 2014 and December 2018. Only patients who had a predominant subtype (≥ 80% COM or COD) and who had a 24-hour urine evaluation prior to medical management were included. Clinical and metabolic factors were compared in the two subgroups.Out of 157 stone-formers, 121 were COM and 36 were COD. COD formers were younger than COM formers with a mean age of 53±16 vs 59±15, respectively (p=0.038). There were no observable differences in gender, BMI, HTN, DM, or HLD. COM formers exhibited higher rates of hypocitraturia and hyperoxaluria, p= 0.022 and p=0.018, respectively. Conversely, COD formers had significantly higher rates of hypercalciuria (47% vs. 28%, p=0.012). Multivariate analysis found hypercalciuria to independently predict COD (p=0.043) and hyperoxaluria to predict COM stones (p=0.016).COM formers are more likely to have hyperoxaluria, hypocitraturia, and elevated urinary oxalate levels compared to COD formers. COD formers exhibited higher incidence of hypercalciuria. These data suggest that all CaOx stones are not alike, and that distinct metabolic and clinical etiological differences exist that may guide future management and prevention.
View details for DOI 10.1089/end.2019.0245
View details for PubMedID 31154910
Is it possible to automatically assess pretreatment digital rectal examination documentation using natural language processing? A single-centre retrospective study.
2019; 9 (7): e027182
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
An Automated Feature Engineering for Digital Rectal Examination Documentation using Natural Language Processing.
AMIA ... Annual Symposium proceedings. AMIA Symposium
2018; 2018: 288–94
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