Burnout

Grand Rounds January 30, 2026: A Pragmatic Randomized Controlled Trial of Ambient Artificial Intelligence to Improve Health Practitioner Well-Being (Majid Afshar, MD, MS; Mary Ryan Baumann, PhD)

Posted on by Sophia Ramirez

Speakers

Majid Afshar, MD, MS
Associate Professor
Director, Learning Health Systems
Departments of Medicine and Biostatistics & Medical Informatics
University of Wisconsin-Madison

Mary Ryan Baumann, PhD
Assistant Professor
Departments of Population Health Sciences and Biostatistics & Medical Informatics
University of Wisconsin-Madison

Keywords

Artificial Intelligence; Burnout; Provider Well-Being; Learning Health System

Key Points

  • Documentation in the Electronic Health Record (EHR) is a driver of clinician burnout; it can reduce their capacity to connect with patients during an appointment and spill over into daily life, i.e. “work outside of work.” The research team sought to assess whether the use of an ambient Artificial Intelligence (AI) scribe could improve clinician well-being by automating the documentation process.
  • The stepped-wedge, individually randomized trial took place over 24 weeks at UW Health. 66 providers across various specialties were randomized to receive access to ambient AI at Week 1, Week 7, or Week 13. The primary endpoint was physician well-being, measured by the Professional Fulfillment subscale and a burnout composite.
  • The research team found a 20% reduction in burnout and a trend towards improvement in professional fulfillment. These effects were sustained over the course of the trial. Use of the technology also decreased “work outside of work” by an average of 30 minutes and “time in notes” by 21 minutes.

Discussion Themes

Qualitative interviews found that patients of the clinicians in the trial appreciated the reduced computer interaction and felt that communication was clearer and more open.

The research team worked with the EHR company to develop a rubric for evaluating the AI-generated notes for accuracy, i.e. the presence of AI hallucinations or falsifications.

Following the trial’s success, UW Health scaled the project from 66 to over 600 licenses. An operational dashboard was developed for real-time monitoring of utilization and documentation metrics to ensure sustained performance and coding compliance.

Grand Rounds December 19, 2025: Use of Ambient AI Scribes to Reduce Administrative Burden and Professional Burnout: Lessons Learned and Future Directions (Kristine Olson, MD, MSc; Daniella Meeker, PhD; Lee H. Schwamm, MD)

Posted on by terren.green@duke.edu

Speakers

Lee H. Schwamm, MD
Sr Vice President and Chief Digital Health Officer
Yale New Haven Health System
Associate Dean, Digital Strategy & Transformation,
Professor of Neurology and of Biomedical Informatics and Data Sciences
Yale School of Medicine

Kristine Olson, MD, MSc
Assistant Clinical Professor
Department of Medicine, Yale School of Medicine

Daniella Meeker, PhD
Associate Professor of Biomedical Informatics and Data Science, Yale School of Medicine
Chief Research Information Officer, Yale New Haven Health System

Keywords

Ambient AI scribe, Ambulatory clinics, Burnout, Clinical notes, Electronic health record.

Key Points

  • Physicians in clinic-based ambulatory care spend more than half of the workday documenting patient care in the electronic health record leading to burnout.
  • Both human and older technology ambient scribes have been shown to reduce burnout in single center studies.
  • From February to October 2024, researchers from the Yale University conducted a multi-center study in 6 health systems enrolling 263 medical professionals in ambulatory clinics to determine if an ambient scribe system reduced provider burnout.
  • After patient selection and obtaining consent, the Abridge ambient AI scribe (Abridge AI, Inc) generated a standard medical note of the patient visit while a secure online portal allowed for later viewing and editing. The transcript was imported into the clinic’s EHR note template, after which audio was deleted.
  • The researchers worked with Abridge to modify an existing client satisfaction survey, including 1 item from the mini-Z burnout metric and 3 items from the NASA Task Load Index, to capture change in physician burnout. Participants completed the survey before and after the 30-day intervention.
  • Analysis of the survey found that the ambient AI scribe reduced burnout from 51.9% to
    38.8% – a statistically significant reduction of burnout by 70% in 30 days. Significant improvements were also seen in the cognitive task load required to complete patient documentation. Focus on patients also increased.

Discussion Themes

The study team approached this project as an evaluation of an existing deployment of ambient AI to provide a measure of the ambient AI’s impact due to the perceived crisis around the burden of the electronic health record (EHR) and the need to increase patient access to providers by freeing up provider time. A step-wedge approach may be the best design approach for a study of this nature.

Ambient AI improves the quality of notes in several ways. The billable level of the notes improves, and the transcript provides transparent auditability.

Certain specialties are not seeing as much impact from the ambient AI assisted notes, such as pediatricians examining a non-verbal young child or baby. The physician in this case must learn to verbalize information they gather during their exam in order for the ambient AI to capture this information in the notes.

Patients may benefit from ambient AI as well. Providers may have greater focus and attention on the patient. Providers may capture more information and be able to provide better care.

 

Read more about this ambient AI study.