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Interruptive alerts in clinical decision support (CDS) systems are intended to guide clinicians in making informed decisions and adhering to best practices. However, these alerts can often become a source of frustration, contributing to alert fatigue and clinician burnout. Traditionally, an alert's burden is often assessed by evaluating the total number of times it is seen by end-users, which can overlook the true impact of highly interruptive workflows. This study [...]

Patient portals bridge patient and provider communications but exacerbate physician and nursing burnout. Large language models (LLMs) can generate message responses that are viewed favorably by health care professionals/providers (HCPs); however, these studies have not included diverse message types or new prompt-engineering strategies.Our goal is to investigate and compare the quality and precision of GPT-generated message responses versus real doctor responses across the spectrum of message types within a patient [...]

Registered nurses increasingly work in remote care and digital interaction roles, offering flexibility and expansion of their scope of practice. These roles may expose nurses to digital compassion fatigue, a phenomenon proposed to be characterized by the negative psychological and emotional impact of caring for patients remotely through the use of technology.The first objective of this work is to propose the phenomenon of "digital compassion fatigue" as a potentially further [...]

While computerized provider order entry (CPOE) has become standard for medication, laboratory, referral, and imaging ordering, use in surgical case requests has not been well-described. At a large county hospital, many surgical clinics used a variety of workflows for case requests, leading to data duplication and data storage outside of the electronic health record (EHR).We hypothesized that a provider-entered order-based case request (OBCR) tool would improve data entry efficiency and [...]

To quantify differences between (1) stratifying patients by predicted disease onset risk alone and (2) stratifying by predicted disease onset risk and severity of downstream outcomes. We perform a case study of predicting sepsis.

screening is a labor-intensive component of systematic review involving repetitive application of inclusion and exclusion criteria on a large volume of studies. We aimed to validate large language models (LLMs) used to automate abstract screening.

To measure hospital engagement in interoperable exchange of health-related social needs (HRSN) data.

The objective of this work is to demonstrate the value of simulation testing for rapidly evaluating artificial intelligence (AI) products.

We conducted a scoping review to identify barriers to telehealth use and uptake from the perspective of patient, provider, and system that were documented in the literature. In addition to identifying and categorizing the barriers, we aimed to assess how barriers differed for studies conducted during the COVID-19 pandemic, as well as how barriers differed between the United States vs internationally based studies.