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Well-functioning clinical decision support (CDS) can facilitate provider workflow, improve patient care, promote better outcomes, and reduce costs. However, poorly functioning CDS may lead to alert fatigue, cause providers to ignore important CDS interventions, and increase provider dissatisfaction.

Hospital electronic health record (EHR) data are increasingly being called upon for research purposes, yet only recently has it been tested to examine its reliability. Studies that have examined reliability of EHR data for research purposes have varied widely in methods used and field of inquiry, with little reporting of the reliability of perinatal and obstetric variables in the current literature.

Medication alert overrides remain persistently high over the past decade, influenced by factors such as "alert fatigue" and lack of provider acceptance.

Recent advances in computer vision and wearable technology have created an opportunity to introduce mobile therapy systems for autism spectrum disorders (ASD) that can respond to the increasing demand for therapeutic interventions; however, feasibility questions must be answered first.

Identifying pneumonia using diagnosis codes alone may be insufficient for research on clinical decision making. Natural language processing (NLP) may enable the inclusion of cases missed by diagnosis codes.

This article presents and describes our methods in developing a novel strategy for recruitment of underrepresented, community-based participants, for pragmatic research studies leveraging routinely collected electronic health record (EHR) data.

Patient portals specifically designed for the inpatient setting have significant potential to improve patient care. However, little is known about how the users of this technology, the patients, may interact with the inpatient portals. As a result, hospitals have limited ability to design approaches that support patient use of the portal.

Mobile stroke units (MSUs) reduce time to thrombolytic therapy in acute ischemic stroke. These units are widely used, but the clinical information systems underlying MSU operations are understudied.