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To demonstrate the application of the Large-scale Evidence Generation and Evaluation across a Network of Databases (LEGEND) principles described in our companion article to hypertension treatments and assess internal and external validity of the generated evidence.

Recent health care developments include connected health interventions to improve chronic disease management and/or promote actions reducing aggravating risk factors for conditions such as cardiovascular diseases. Adherence is one of the main challenges for ensuring the correct use of connected health interventions over time.

An electronic pathway for the management of adhesive small bowel obstruction (SBO) was built and implemented on top of the electronic health record. The aims of this study are to describe the development of the electronic pathway and to report early outcomes.

With the increased usage of dashboard reporting systems to monitor and track patient panels by clinical users, developers must ensure that the information displays they produce are accurate and intuitive. When evaluating usability of a clinical dashboard among potential end users, developers oftentimes rely on methods such as questionnaires as opposed to other, more time-intensive strategies that incorporate direct observation.

To measure US hospitals' adoption of electronic health record (EHR) functions that support care for older adults, focusing on structured documentation of the 4Ms (What Matters, Medication, Mentation, and Mobility) and electronic health information exchange/communication with patients, caregivers, and long-term care providers.

An area deprivation index (ADI) is a geographical measure that accounts for socioeconomic factors (e.g., crime, health, and education). The state of Ohio developed an ADI associated with infant mortality: Ohio Opportunity Index (OOI). However, a powerful tool to present this information effectively to stakeholders was needed.

The study sought to evaluate a novel electronic health record (EHR) add-on application for chronic disease management that uses an integrated display to decrease user cognitive load, improve efficiency, and support clinical decision making.

To mine Twitter and quantitatively analyze COVID-19 symptoms self-reported by users, compare symptom distributions across studies, and create a symptom lexicon for future research.

We introduce fold-stratified cross-validation, a validation methodology that is compatible with privacy-preserving federated learning and that prevents data leakage caused by duplicates of electronic health records (EHRs).