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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 [...]

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 [...]

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.

Personal health records (PHRs) offer patients a portal to view lab results, communicate with their doctors, and refill medications. Expanding PHR access to mobile devices could increase patients' engagement with their PHRs. We examined whether access to a mobile-optimized PHR changed the frequency and timeliness of PHR use among adult patients with diabetes in an integrated delivery system. Among patients originally using the PHR only by computer, PHR use frequency [...]

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

The prevalence of moderate or complex (moderate-complex) congenital heart defects (CHDs) among adults is increasing due to improved survival, but many patients experience lapses in specialty care or their CHDs are undocumented in the medical system. There is, to date, no efficient approach to identify this population.

Assess information integrity (concordance and completeness of documented exam indications from the electronic health record [EHR] imaging order requisition, compared to EHR provider notes), and assess potential impact of indication inaccuracies on exam planning and interpretation.

Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the complexity of PSG signals and physiological heterogeneity between patients. Deep neural networks, which have recently achieved expert-level performance for other complex medical tasks, are ideally suited to PSG scoring, given sufficient training data.