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Large practice networks have access to EHR data that can be used to drive important improvements in population health. However, missing data often limit improvement efforts. Our goal was to determine the proportion of patients in a cohort of small primary care practices who lacked cholesterol data to calculate ASCVD risk scores and then gauge the extent that imputation can accurately identify individuals already at high risk. 219 practices enrolled [...]

Rule-base clinical decision support alerts are known to malfunction, but tools for discovering malfunctions are limited.

Accurate and efficient identification of complex chronic conditions in the electronic health record (EHR) is an important but challenging task that has historically relied on tedious clinician review and oversimplification of the disease. Here we adapt methods that allow for automated "noisy labeling" of positive and negative controls to create a "silver standard" for machine learning to automate identification of systemic lupus erythematosus (SLE). Our final model, which includes both [...]

Conduct a cluster analysis of inpatient portal (IPP) users from an academic medical center to improve understanding of who uses these portals and how.

Across recent decades, profound changes in the practice of medicine have been accompanied by parallel developments in the daily mental efforts of medical professionals. Using visual metaphors and hand-drawn illustrations, the author explores the evolution of one physician's brain over the past 25 years. At the completion of training, the patient-practitioner relationship, medical knowledge, and care decisions dominated clinician thought, time, and effort. During the 1990's, the growing constraints of [...]

This study evaluates whether a web-based educational program for patients who read their mental health notes online improves patient-clinician communication and increases patient activation.

Querying electronic health records (EHRs) to find patients meeting study criteria is an efficient method of identifying potential study participants. We aimed to measure the effectiveness of EHR-driven recruitment in the context of ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness)-a pragmatic trial aiming to recruit 15 000 patients.

Lesbian, gay, bisexual, transgender, and queer (LGBTQ) people experience significant health disparities across the life course and require health care that addresses their unique needs. Collecting information on the sexual orientation and gender identity (SO/GI) of patients and entering SO/GI data in electronic health records has been recommended by the Institute of Medicine, the Joint Commission, and the Health Resources and Services Administration as fundamental to improving access to and [...]

We describe and evaluate the mapping of computerized tomography (CT) terms from 40 hospitals participating in a health information exchange (HIE) to a standard terminology.

We developed and validated an algorithm that uses combinations of extractable electronic-health-record (EHR) indicators (diagnosis codes, orders for laboratories, medications, and referrals) that denote widely-recommended clinician practice behaviors: attention to overweight/obesity/body mass index alone (BMI Alone), with attention to hypertension/other comorbidities (BMI/Medical Risk), or neither (No Attention). Data inputs used for each EHR indicator were refined through iterative chart review to identify and resolve modifiable coding errors. Validation was performed [...]