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◆ Applied clinical informatics2026-08-19

Large-Scale Implementation of Ambient AI Documentation and Its Effects on EHR Efficiency and Clinician Well-Being.

Andrew Svetly, Elie Razzouk, Mary McLean, Kenneth Frye, Andrew Little, Lana Massaro, Cheyenne Quailey, Conner Svetly, Aatish Patel, Jesus Montiel

一句话结论 · In one sentence

Deployment of ambient AI documentation technology at scale was associated with improvements in documentation efficiency, substantial reductions in manual input, and improved provider well-being, supporting its potential to meaningfully alleviate documentation burden.

原始摘要(英文原文)· Original abstract
BACKGROUND: Ambient clinical documentation tools are increasingly used to reduce administrative burden and improve provider experience. However, evidence describing their effects at scale across large, multi-site health systems remains limited. OBJECTIVES: To evaluate the effect of Dragon Ambient eXperience (DAX) Copilot on documentation efficiency, note composition practices, and provider well-being across a multi-state health system. METHODS: Due to rolling registration and training, we conducted a retrospective index-date-aligned pre-post analysis of objective EHR activity metrics, supplemented by a post-implementation survey. Physicians and advanced practice providers (APPs) in ambulatory settings between June 2024 and November 2025 were included. Epic Signal data were analyzed for each provider over the 8 months before and after DAX activation. Metrics included active time in notes per appointment, proportion of note content originating from manual typing, copy/paste, or conventional voice recognition, and average note length. Surveys were administered 45 days post-activation to assess satisfaction, burnout, intent to remain with the organization, and work-life balance. RESULTS: A total of 210 providers met the inclusion criteria, defined as generating ≥25% of total note content using ambient voice technology and having at least 16 months of Signal Data (8 months pre- and 8 months post-intervention). Compared with the pre-implementation period, active note time decreased significantly (5.54 to 4.09 minutes per appointment; 26.2% reduction; p<0.001). Despite a +28.8% increase in note length, manual documentation behaviors declined substantially, including typing (-51.7%), copy/paste (-42.7%), and conventional voice recognition (-67.8%). Survey responses (n=233; 26.4% response rate) indicated improvements across domains, with most respondents reporting reduced burnout, increased job satisfaction, improved work-life balance, and a strong preference to continue using DAX. CONCLUSIONS: Deployment of ambient AI documentation technology at scale was associated with improvements in documentation efficiency, substantial reductions in manual input, and improved provider well-being, supporting its potential to meaningfully alleviate documentation burden.
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Large-Scale Implementation of Ambient AI Documentation and Its Effects on EHR Efficiency and Clinician Well-Being. — 科研速览 Science Skim