Provider Burden


Artificial Intelligence and Human Factors in Healthcare Quality & Safety

Description

Using a conference model, this study convenes a multidisciplinary group of experts to explore the integration of human factors engineering approaches in the implementation of artificial intelligence in healthcare, providing an opportunity for ongoing collaboration and research to disseminate knowledge and implement best practices that enhance efficiency, prevent provider burnout, and ultimately improve healthcare quality, safety, and value.

Grant Number
R13 HS030350
Principal Investigator(s)

Assessing the Effects of EHR Optimization Interventions in Primary Care

Description

This research evaluates the adoption and impact of three electronic health record-optimization interventions—scribes, advanced team-based inbox management, and artificial intelligence-assisted messaging support—on primary care physicians' time, wellbeing, and patient outcomes, with the goal of identifying effective strategies to improve physician satisfaction and care quality and to reduce healthcare costs.

Grant Number
R01 HS029470
Principal Investigator(s)

Improving Pediatric Donor Heart Utilization with Predictive Analytics

Description

This study aims to optimize the use of donor hearts for infants and children awaiting heart transplantation by developing predictive models to assess in real-time the potential for transplant success and to evaluate risk. Researchers plan to display these data through intuitive visualizations on a custom-built interface to reduce clinicians’ cognitive burden, enhance decision making confidence, and help ensure the best donor match for pediatric patients.

Grant Number
R21 HS029548
Principal Investigator(s)

Meaningful Drug Interaction Alerts

Description

This research developed algorithms for eight key drug-drug interactions (DDI) to inform the building of contextualized DDI alerts; developed and tested three DDI-clinical decision support (CDS) apps; and disseminated the information and algorithms via the DDI-CDS.org website, webinars, and publications.

Grant Number
R01 HS025984
Principal Investigator(s)

Health Information Technology in Heart Failure Care

Description

This research evaluated the implementation and effectiveness of a clinical decision support tool designed to support the delivery of recommended care to hospitalized patients with heart failure, regardless of the reason for hospitalization.

Grant Number
K08 HS023683
Principal Investigator(s)