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An electronic clinical decision support (CDS) alert can provide real-time provider support to offer pre-exposure prophylaxis (PrEP) to youth at risk for human immunodeficiency virus (HIV). The purpose of this study was to evaluate provider utilization of a PrEP CDS alert in a large academic-community pediatric network and assess the association of the alert with PrEP prescribing rates.

Informed decision aids provide information in the context of the patient's values and improve informed decision making (IDM). To overcome barriers that interfere with IDM, our team developed an innovative iPad-based application (aka "app") to help patients make informed decisions about colorectal cancer screening. The app assesses patients' eligibility for screening, educates them about their options, and empowers them to request a test via the interactive decision aid.

Developing a diverse informatics workforce broadens the research agenda and ensures the growth of innovative solutions that enable equity-centered care. The American Medical Informatics Association (AMIA) established the AMIA First Look Program in 2017 to address workforce disparities among women, including those from marginalized communities. The program exposes women to informatics, furnishes mentors, and provides career resources. In 4 years, the program has introduced 87 undergraduate women, 41% members of [...]

Guidance is needed on studying engagement and treatment effects in digital health interventions, including levels required for benefit. We evaluated multiple analytic approaches for understanding the association between engagement and clinical outcomes.

To characterize variation in clinical documentation production patterns, how this variation relates to individual resident behavior preferences, and how these choices relate to work hours.

Hospital-acquired infections (HAIs) are associated with significant morbidity, mortality, and prolonged hospital length of stay. Risk prediction models based on pre- and intraoperative data have been proposed to assess the risk of HAIs at the end of the surgery, but the performance of these models lag behind HAI detection models based on postoperative data. Postoperative data are more predictive than pre- or interoperative data since it is closer to the [...]

Frailty is a prevalent risk factor for adverse outcomes among patients with chronic lung disease. However, identifying frail patients who may benefit from interventions is challenging using standard data sources. We therefore sought to identify phrases in clinical notes in the electronic health record (EHR) that describe actionable frailty syndromes.

Clinical registries-structured databases of demographic, diagnosis, and treatment information-play vital roles in retrospective studies, operational planning, and assessment of patient eligibility for research, including clinical trials. Registry curation, a manual and time-intensive process, is always costly and often impossible for rare or underfunded diseases. Our goal was to evaluate the feasibility of natural language inference (NLI) as a scalable solution for registry curation.