Evidence map›Paper›PMID 40672471›Full record

ArticlemedRxiv : the preprint server for health sciences2025

A Randomized-Clinical Trial of Two Ambient Artificial Intelligence Scribes: Measuring Documentation Efficiency and Physician Burnout.

Paul J Lukac, William Turner, Sitaram Vangala, Aaron T Chin, Joshua Khalili, Ya-Chen Tina Shih, Catherine Sarkisian, Eric M Cheng, John N Mafi

2 registry-linked trialsAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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.

NCT06792890 nacompletednot on this map

A Randomized Controlled Trial of Two Ambient Artificial Intelligence Scribe Technologies to Improve Documentation Efficiency and Reduce Physician Burnout

TypeinterventionalSponsorUniversity of California, Los AngelesRan2024 to 2025Enrolled238ConditionsPhysician Workflow, Artificial Intelligence (AI)ArmsUse Nabla AI Scribe tool provided, Use AI Scribe tool provided by Vendor B
NCT07742761 naactive not recruitingnot on this mapstarted 2026, after this paper: background citation

Emergency Medicine Practitioners Overall Well-being Enhancement With Ambient AI Scribes

TypeinterventionalSponsorWashington University School of MedicineRan2026 to 2027Enrolled55ConditionsWell-being at Work, BurnoutArmsAmbient AI Scribe
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
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

9 authors.

Paul J LukacDepartment of Pediatrics, David Geffen School of Medicine; UCLA Health Information Technology, UCLA Health, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-3315-6613
William TurnerDivision of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.
Sitaram VangalaDivision of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-8842-5702
Aaron T ChinDepartment of Pediatrics, Division of Immunology, Allergy and Rheumatology, David Geffen School of Medicine; UCLA Health Information Technology, UCLA Health, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0001-9490-6580
Joshua KhaliliDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0009-0009-3559-4332
Ya-Chen Tina ShihDepartment of Radiation Oncology and Department of Medicine, David Geffen School of Medicine; Department of Health Policy and Management, Fielding School of Public Health; Program in Cancer Health Economics Research, Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0001-7290-3864
Catherine SarkisianDivision of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, and Veterans Administration Greater Los Angeles Geriatrics Research Education and Clinical Center, Los Angeles, CA, United States.ORCID 0000-0003-2768-2323
Eric M ChengDepartment of Neurology, David Geffen School of Medicine; UCLA Health Information Technology, UCLA Health, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-2568-5603
John N MafiDivision of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States; RAND Corporation, Santa Monica, CA, United States.ORCID 0000-0002-0322-7636

Funding

UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
NRSA Training CoreTL1TR001883 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ALEX BUI, Nina Thawata Harawa · 2016 to 2026
$8.6M
Midcareer Award in Patient-Oriented Community-Academic Partnered Aging ResearchK24AG047899 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SARKISIAN, CATHERINE A · 2014 to 2025
$2.0M
Leveraging Electronic Health Records to Measure and Reduce Harmful, Low-Value Care Among Older AdultsK76AG064392 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MAFI, JOHN · 2020 to 2024
$1.2M
NCATS NIH HHS TL1 TR001883NCATS NIH HHS UL1 TR001881NIA NIH HHS K24 AG047899NIA NIH HHS K76 AG064392
6 · The paper itself

Abstract

Importance: Ambient artificial intelligence (AI) scribes record patient encounters and generate visit notes almost instantaneously, representing a promising solution to documentation burden and associated physician burnout. Despite swift and widespread adoption of AI scribes, their impacts have not been examined in randomized-clinical trials. Objective: To test the effectiveness of two AI scribes in reducing time spent writing notes and associated burnout in a randomized-clinical trial. Design: Parallel three-arm pragmatic randomized-clinical trial where physicians were assigned 1:1:1 via covariate-constrained randomization (balancing on time-in-note, baseline burnout score, and clinic days /week) to either one of two AI scribe applications-Microsoft DAX or Nabla-or a usual-care control group from 11/4/2024-1/3/2025. Setting: A large academic health system in California. Participants: 313 outpatient physicians were recruited based on leadership referrals and department-wide emails. 238 participants representing 14 specialties qualified. Intervention: Intervention-arm physicians gained access to an AI scribe for two months. Main Outcomes and Measures: The primary outcome was change from baseline log writing time-in-note. Secondary outcomes measured by surveys included Mini-Z 2.0, 4-item physician task load (TL), and Professional Fulfillment Index-Work Exhaustion (PFI-WE) scores to evaluate aspects of burnout, work environment, and stress, as well as targeted questions addressing safety and accuracy. Results: DAX was used in 33.5% of 24,696 visits; Nabla was used in 29.5% of 23,653 visits. Nabla users experienced a 9.5% [95% CI:-17.2%,-1.8%] (p=.02) decrease in time-in-note versus the control group and a 7.8% [-15.5%,-0.1%] (p=.05) decrease versus DAX users, while DAX users exhibited no significant change versus control (-1.7% [-9.4%,+5.9%]; p=.66). Total Mini-Z, scaled 10-50 with higher scores indicating improvement, increased with users of any scribe (+2.76 [+1.41,+4.10]; p<.001). Reductions in TL (scale 0-400, TL=-35.8 [-63.7, -7.9]; p=.01) and work exhaustion (scale 0-4, PFI-WE=-0.27 [-0.48, -0.07]; p=.01) were seen with users of any scribe. One Grade 1 (mild) adverse event was reported, while clinically-significant inaccuracies were noted "occasionally" on 5-point Likert questions (DAX 2.7 [2.4-3.0] vs. Nabla 2.8 [2.6-3.0]; p=.68). Conclusion and Relevance: Use of Nabla reduced time-in-note, while use of any scribe led to modest improvements in physician burnout, work exhaustion, and task load. Performance was remarkably similar across two distinct vendor platforms, and occasional inaccuracies observed in either scribe require ongoing physician vigilance. Trial Registration: ClinicalTrials.gov Identifier: NCT06792890.

Identifiers

PMID40672471
PMCPMC12265753

What OpenQuestion holds

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Registered trials

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.