The widespread adoption of EHRs following the HITECH Act has increased the clinician documentation burden, contributing to burnout. Emerging technologies, such as ambient listening tools powered by generative AI, offer real-time, scribe-like documentation capabilities to reduce physician workload. This study evaluates the impact of ambient listening tools implemented at UCI Health by analyzing EPIC Signal data to assess changes in note length and time spent on notes. Results show significant reductions in note-taking time and an increase in note length, particularly during the first-month post-implementation. Findings highlight the potential of AI-powered documentation tools to improve clinical efficiency. Future research should explore adoption barriers, long-term trends, and user experiences to enhance the scalability and sustainability of ambient listening technology in clinical practice.
@article{arxiv.2504.13879,
title = {Ambient Listening in Clinical Practice: Evaluating EPIC Signal Data Before and After Implementation and Its Impact on Physician Workload},
author = {Yawen Guo and Di Hu and Jiayuan Wang and Kai Zheng and Danielle Perret and Deepti Pandita and Steven Tam},
journal= {arXiv preprint arXiv:2504.13879},
year = {2025}
}
Comments
In: Proceedings of the 20th World Congress on Health and Biomedical Informatics (MEDINFO 25)