Evidence map›Paper›PMID 41775342›Full record

ArticleJMIR formative research2026

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

Taylor Marquis, Matthew Kopp, Jared S Anderson, Anthony M Napoli, Linda L Brown, Yosef Berlyand

Abstract read
In one paragraph

Article in JMIR formative research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Taylor MarquisDepartment of Emergency Medicine, Alpert Medical School, Brown University, Providence, RI, United States.ORCID 0009-0003-8594-283X
Matthew KoppDepartment of Emergency Medicine, Alpert Medical School, Brown University, Providence, RI, United States.ORCID 0009-0005-8129-5510
Jared S AndersonDepartment of Emergency Medicine, Alpert Medical School, Brown University, Providence, RI, United States.ORCID 0000-0001-7682-9059
Anthony M NapoliDepartment of Emergency Medicine, Alpert Medical School, Brown University, Providence, RI, United States.ORCID 0000-0001-7622-7306
Linda L BrownDepartment of Emergency Medicine, Alpert Medical School, Brown University, Providence, RI, United States.ORCID 0000-0001-5130-8548
Yosef BerlyandDepartment of Emergency Medicine, Alpert Medical School, Brown University, Providence, RI, United States.ORCID 0000-0003-2313-8507

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth care organizations have started to implement artificial intelligence-powered ambient scribe technology in clinical documentation workflows. Early outpatient studies have shown mixed results. Few studies have evaluated ambient scribes in the emergency department (ED). Due to differences in setting and patient acuity between the ED and ambulatory clinics, there remains a pressing need to research this technology in the ED.

objectiveThis study aimed to evaluate emergency physicians' (EPs) satisfaction, perceived documentation efficiency, after-shift documentation time, and trust in ambient scribe-generated notes compared with in-person scribes or independent documentation, and to identify ED-specific challenges.

methodsA cross-sectional survey was conducted among 16 board-certified adult and pediatric EPs who were granted access to the ambient scribe technology across 4 EDs. EPs used the ambient scribe for several months before completing a survey with multiple-choice and free-text responses. We performed a mixed methods analysis by summarizing quantitative data through descriptive statistics and performing a practical thematic analysis on free-text responses.

resultsOf the 16 EPs, 14 (87.5%) completed the survey. Among respondents, 9 (64.3%; 95% CI 38.7%-83.7%) reported being satisfied or very satisfied with the ambient scribe, while 3 (21.4%; 95% CI 7.6%-47.6%) expressed dissatisfaction. When given the option, 7 (50%; 95% CI 26.8%-73.2%) respondents preferred the ambient scribe, 4 (28.5%; 95% CI 11.7%-54.6%) preferred in-person scribes, and none (95% CI 0%-20.6%) preferred independent documentation. Among previous users of in-person scribes, 50% (4/8; 95% CI 21.5%-78.5%) favored the ambient scribe. The ambient scribe was reported to improve documentation efficiency (10/14, 71.4%; 95% CI 45.4%-88.3%) and reduce after-shift documentation time (9/14, 64.3%; 95% CI 38.7%-83.7%). However, only 42.9% (6/14; 95% CI 22.3%-69.2%) of respondents trusted the accuracy of ambient scribe-generated notes, compared with 75% (6/8; 95% CI 40.9%-92.9%) who trusted in-person scribes. Few respondents found the ambient scribe helpful for physical examinations (3/13, 23.1%; 95% CI 8.2%-50.3%) or medical decision-making documentation (5/14, 35.7%; 95% CI 16.3%-61.2%). A thematic analysis identified 5 themes: challenges due to the workplace environment, challenges due to the patient population, workflow improvement, workflow harm, and narrow usefulness.

conclusionsThis mixed methods pilot study is among the first to evaluate ambient scribe technology in the ED. Our results add ED-specific insights to literature focused on the outpatient setting. Our findings reveal the potential for enhancing documentation efficiency and reducing administrative burden while highlighting setting-specific challenges. While most EPs preferred artificial intelligence-assisted documentation over independent charting, confidence in documentation accuracy and functionality remains limited compared with human scribes and varies by note component. As the demand for efficiency in emergency medicine continues to grow, scalable solutions such as ambient scribes could play a pivotal role if functionality, reliability, and physician trust can be further optimized.

Indexed as

Artificial IntelligenceDocumentationPhysiciansAdultCross-Sectional StudiesElectronic Health RecordsEmergency Service, HospitalFemaleHumansIntelligent SystemsMaleMiddle AgedPilot ProjectsSurveys and QuestionnairesAIartificial intelligenceclinical documentationelectronic health recordsemergency department operationshealth care technologymedical scribesnatural language processing

Identifiers

PMID41775342
PMCPMC12996897

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.