Ambient Artificial Intelligence Scribes: Physician Burnout and Perspectives on Usability and Documentation Burden

Overview

Journal J Am Med Inform Assoc

Publisher Oxford University Press

Specialty Medical Informatics

Date 2024 Dec 10

PMID 39657021

Authors

Shreya J Shah

Anna Devon-Sand

Stephen P Ma

Yejin Jeong

Trevor Crowell

Margaret Smith

April S Liang

Clarissa Delahaie

Caroline Hsia

Tait Shanafelt

Michael A Pfeffer

Christopher Sharp

Steven Lin

Patricia Garcia

Affiliations

Soon will be listed here.

Abstract

Objective: This study evaluates the pilot implementation of ambient AI scribe technology to assess physician perspectives on usability and the impact on physician burden and burnout.

Materials And Methods: This prospective quality improvement study was conducted at Stanford Health Care with 48 physicians over a 3-month period. Outcome measures included burden, burnout, usability, and perceived time savings.

Results: Paired survey analysis (n = 38) revealed large statistically significant reductions in task load (-24.42, p <.001) and burnout (-1.94, p <.001), and moderate statistically significant improvements in usability scores (+10.9, p <.001). Post-survey responses (n = 46) indicated favorable utility with improved perceptions of efficiency, documentation quality, and ease of use.

Discussion: In one of the first pilot implementations of ambient AI scribe technology, improvements in physician task load, burnout, and usability were demonstrated.

Conclusion: Ambient AI scribes like DAX Copilot may enhance clinical workflows. Further research is needed to optimize widespread implementation and evaluate long-term impacts.

Citing Articles

Hot topics in artificial intelligence.

Bakken S, Poon E J Am Med Inform Assoc. 2025; 32(2):265-267.

PMID: 39836895 PMC: 11756649. DOI: 10.1093/jamia/ocae324.

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