ArticlemedRxiv : the preprint server for health sciences2025
A Randomized-Clinical Trial of Two Ambient Artificial Intelligence Scribes: Measuring Documentation Efficiency and Physician Burnout.
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.
What it found
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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.
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.
A Randomized Controlled Trial of Two Ambient Artificial Intelligence Scribe Technologies to Improve Documentation Efficiency and Reduce Physician Burnout
Emergency Medicine Practitioners Overall Well-being Enhancement With Ambient AI Scribes
Who cites it
1 citing paper in PubMed.
- Impact of an Ambient AI Scribe Among Clinicians and Patients: Real-World Prospective Observational Time-Motion Study.JMIR medical informatics · 2026Observational
Corrections and comments
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Authors and funding
9 authors.
Funding
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.
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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.