Physician Assistant


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)

Machine-Learning Prediction Model for Personalized Urinary Tract Infection Care in Children

Description

The study will develop and implement a validated machine learning model to optimize voiding cystourethrogram timing and use for diagnosing vesicoureteral reflux (VUR) in children, aiming to reduce the significant health and economic impacts of VUR and recurrent febrile urinary tract infections (fUTIs) by standardizing practices, minimizing unnecessary procedures, and ensuring timely diagnosis for those at highest risk, ultimately seeking to prevent renal injury from fUTIs.

Grant Number
K08 HS029526
Principal Investigator(s)

Survey-based work system assessment to facilitate large-scale dissemination of healthcare quality improvement programs.

Principal Investigator

An analysis of primary care clinician communication about risk, benefits, and goals related to chronic opioid therapy.

Principal Investigator

Health Information Technology and Provider Communication

Description
This is a questionnaire designed to be completed by physicians, nurse practitioners, and physician assistants in a perioperative/operative and hospital setting. The tool includes questions to assess the current state of health information technology including clinical documentation, computerized provider order entry systems, clinical decision support systems, hardware, mobile devices, secure messaging, text messaging, and EHRs/EMR.
Year of Survey

Scaling E.Q.U.I.P.P.E.D. Clinical Decision Support

Description

This research successfully adapted and evaluated scaling of the Enhancing Quality of Prescribing Practices for Older Adults Discharged from the Emergency Department medication safety program to an additional commercial electronic health record and added additional sites, finding a significant reduction in potentially inappropriate medication prescribing in the emergency department setting. 

Grant Number
R18 HS026877
Principal Investigator(s)

Association of electronic health record design and use factors with clinician stress and burnout.

Principal Investigator

Comparison of a prototype for indications-based prescribing with 2 commercial prescribing systems.

Principal Investigator