Ambient artificial intelligence scribes: physician burnout and perspectives on usability and documentation burden
Shreya Shah, Anna Devon-Sand, P. Stephen, Yejin Jeong, Trevor Crowell, Margaret Smith, April S. Liang, Clarissa Delahaie, Caroline Hsia, Tait D. Shanafelt, Michael A. Pfeffer, Christopher Sharp, Steven Lin, Patricia García
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.