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The rapid, large-scale deployment of new health technologies can introduce challenges to clinicians who are already under stress. The novel coronavirus disease 19 (COVID-19) pandemic transformed health care in the United States to include a telehealth model of care delivery. Clarifying paths through which telehealth technology use is associated with change in provider well-being and interest in sustaining virtual care delivery can inform planning and optimization efforts.

Clinicians need health information technology (IT) that better supports their work. Currently, most health IT is designed to support individuals; however, more and more often, clinicians work in cross-functional teams. Trauma is one of the leading preventable causes of children's death. Trauma care by its very nature is team based but due to the emergent nature of trauma, critical clinical information is often missed in the transition of these patients [...]

The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pandemic threatened to oversaturate hospitals worldwide, necessitating rapid patient discharge to preserve capacity for the most severe cases. This need, as well as the high risk of SARS-CoV-2 transmission, led many hospitals to implement remote patient monitoring (RPM) programs for SARS-CoV-2 positive patients in an effort to provide care that was safe and preserve scarce resources.

One key aspect of a learning health system (LHS) is utilizing data generated during care delivery to inform clinical care. However, institutional guidelines that utilize observational data are rare and require months to create, making current processes impractical for more urgent scenarios such as those posed by the COVID-19 pandemic. There exists a need to rapidly analyze institutional data to drive guideline creation where evidence from randomized control trials are [...]

Electronic health (eHealth) usability evaluations of rapidly developed eHealth systems are difficult to accomplish because traditional usability evaluation methods require substantial time in preparation and implementation. This illustrates the growing need for fast, flexible, and cost-effective methods to evaluate the usability of eHealth systems. To address this demand, the present study systematically identified and expert-validated rapidly deployable eHealth usability evaluation methods.

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.

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.