Ambient Listening in Clinical Practice: Evaluating EPIC Signal Data Before and After Implementation and Its Impact on Physician Workload

April 02, 2025 Β· Declared Dead Β· πŸ› Studies in Health Technology and Informatics

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Authors Yawen Guo, Di Hu, Jiayuan Wang, Kai Zheng, Danielle Perret, Deepti Pandita, Steven Tam arXiv ID 2504.13879 Category cs.HC: Human-Computer Interaction Citations 4 Venue Studies in Health Technology and Informatics Last Checked 4 months ago
Abstract
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.
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