Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Formative Research

Date Submitted: Jul 9, 2025
Date Accepted: Dec 2, 2025

The final, peer-reviewed published version of this preprint can be found here:

AI-Powered Ambient Scribe Technology Experiences Among Emergency Physicians: Cross-Sectional, Mixed Methods Pilot Survey Study

Marquis T, Kopp M, Anderson JS, Napoli AM, Brown LL, Berlyand Y

AI-Powered Ambient Scribe Technology Experiences Among Emergency Physicians: Cross-Sectional, Mixed Methods Pilot Survey Study

JMIR Form Res 2026;10:e80401

DOI: 10.2196/80401

PMID: 41775342

PMCID: 12996897

Artificial Intelligence-Powered Ambient Scribe Technology Experiences Among Emergency Physicians: A Cross-Sectional, Mixed-Methods Pilot Survey Study

  • Taylor Marquis; 
  • Matthew Kopp; 
  • Jared S. Anderson; 
  • Anthony M. Napoli; 
  • Linda L. Brown; 
  • Yosef Berlyand

ABSTRACT

Background:

Early studies in the outpatient setting have shown that artificial intelligence (AI) scribe technology reduces time spent on notes with improved clinic visit experiences for physicians and patients. As the emergency department (ED) presents a significantly different environment from the outpatient setting, there remains a pressing need to research the potential value of ambient scribe technology in the ED.

Objective:

This pilot study aimed to evaluate emergency physicians’ experiences using Nuance® Dragon® Ambient eXperience (DAX™) Copilot, an artificial intelligence (AI) scribe technology, and to compare it with in-person scribes and independent documentation.

Methods:

A cross-sectional survey was conducted among 16 board-certified emergency and pediatric emergency physicians across four emergency departments within a single urban health system. Physicians were granted access to DAX Copilot and subsequently invited to complete an anonymous electronic survey administered via REDCap. The survey assessed baseline use of in-person scribes, experience with DAX Copilot, and comparative preferences among documentation methods.

Results:

Fourteen physicians (87.5%) completed the survey. Of these, 64.3% reported being satisfied or very satisfied with DAX Copilot, while 21.4% expressed dissatisfaction. When given the option, 50.0% preferred DAX Copilot, 28.5% preferred in-person scribes, and 0.0% preferred independent documentation. Among prior users of in-person scribes, 50% favored DAX Copilot. DAX Copilot was reported to improve documentation efficiency (71.4%) and reduce after-shift documentation time (64.3%). However, only 42.9% of respondents trusted the accuracy of DAX-generated notes, compared to 75% who trust in in-person scribes. Few respondents found DAX Copilot helpful for physical exams (21.4%) or medical decision-making documentation (21.4%).

Conclusions:

DAX Copilot shows promise in enhancing documentation efficiency and reducing administrative burden in the emergency department. While most physicians preferred AI-assisted documentation over independent charting, confidence in documentation accuracy and functionality remains limited compared to human scribes. Further research is needed to assess longitudinal outcomes and optimize AI integration into emergency workflows.


 Citation

Please cite as:

Marquis T, Kopp M, Anderson JS, Napoli AM, Brown LL, Berlyand Y

AI-Powered Ambient Scribe Technology Experiences Among Emergency Physicians: Cross-Sectional, Mixed Methods Pilot Survey Study

JMIR Form Res 2026;10:e80401

DOI: 10.2196/80401

PMID: 41775342

PMCID: 12996897

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.