Evidence map›Paper›PMID 38787556›Full record

ArticleJAMA network open2024

Virtual Scribes and Physician Time Spent on Electronic Health Records.

Lisa Rotenstein, Edward R Melnick, Christine Iannaccone, Jianyi Zhang, Aqsa Mugal, Stuart R Lipsitz, Michael J Healey, Christopher Holland, Richard Snyder, Christine A Sinsky and 2 more

Registry-linked trialAbstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06792890 (A Randomized Controlled Trial of Two Ambient Artificial Intelligence Scribe Technologies to Improve Documentation Efficiency and Reduce Physician Burnout), which is not on this map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing 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.

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
3 · Its place in the literature

Who cites it

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

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Review
  8. Article
  9. The Ethics of AI Scribes as Epistemic Agents.JMIR medical informatics · 2026
    Article
  10. Article
  11. Review
  12. Article
  13. Clinician Perceptions of Virtual Scribe Use: A Survey Study.Journal of general internal medicine · 2026
    Article
  14. The Promise and Limits of Hybrid Ambient Documentation.Journal of general internal medicine · 2026
    Article
  15. Article
  16. Review
  17. Review
  18. Article
  19. Article
  20. 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

12 authors.

Lisa RotensteinHarvard Medical School, Boston, Massachusetts.
Edward R MelnickDepartment of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut.
Christine IannacconeBrigham and Women's Hospital, Boston, Massachusetts.
Jianyi ZhangBrigham and Women's Hospital, Boston, Massachusetts.
Aqsa MugalBrigham and Women's Hospital, Boston, Massachusetts.
Stuart R LipsitzHarvard Medical School, Boston, Massachusetts.
Michael J HealeyHarvard Medical School, Boston, Massachusetts.
Christopher HollandMass General Brigham, Boston, Massachusetts.
Richard SnyderMass General Brigham, Boston, Massachusetts.
Christine A SinskyAmerican Medical Association, Chicago, Illinois.
David TingHarvard Medical School, Boston, Massachusetts.
David W BatesHarvard Medical School, Boston, Massachusetts.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Importance: Time on the electronic health record (EHR) is associated with burnout among physicians. Newer virtual scribe models, which enable support from either a real-time or asynchronous scribe, have the potential to reduce the burden of the EHR and EHR-related documentation. Objective: To characterize the association of use of virtual scribes with changes in physicians' EHR time and note and order composition and to identify the physician, scribe, and scribe response factors associated with changes in EHR time upon virtual scribe use. Design, Setting, and Participants: Retrospective, pre-post quality improvement study of 144 physicians across specialties who had used a scribe for at least 3 months from January 2020 to September 2022, were affiliated with Brigham and Women's Hospital and Massachusetts General Hospital, and cared for patients in the outpatient setting. Data were analyzed from November 2022 to January 2024. Exposure: Use of either a real-time or asynchronous virtual scribe. Main Outcomes: Total EHR time, time on notes, and pajama time (5:30 pm to 7:00 am on weekdays and nonscheduled weekends and holidays), all per appointment; proportion of the note written by the physician and team contribution to orders. Results: The main study sample included 144 unique physicians who had used a virtual scribe for at least 3 months in 152 unique scribe participation episodes (134 [88.2%] had used an asynchronous scribe service). Nearly two-thirds of the physicians (91 physicians [63.2%]) were female and more than half (86 physicians [59.7%]) were in primary care specialties. Use of a virtual scribe was associated with significant decreases in total EHR time per appointment (mean [SD] of 5.6 [16.4] minutes; P < .001) in the 3 months after vs the 3 months prior to scribe use. Scribe use was also associated with significant decreases in note time per appointment and pajama time per appointment (mean [SD] of 1.3 [3.3] minutes; P < .001 and 1.1 [4.0] minutes; P = .004). In a multivariable linear regression model, the following factors were associated with significant decreases in total EHR time per appointment with a scribe use at 3 months: practicing in a medical specialty (-7.8; 95% CI, -13.4 to -2.2 minutes), greater baseline EHR time per appointment (-0.3; 95% CI, -0.4 to -0.2 minutes per additional minute of baseline EHR time), and decrease in the percentage of the note contributed by the physician (-9.1; 95% CI, -17.3 to -0.8 minutes for every percentage point decrease). Conclusions and Relevance: In 2 academic medical centers, use of virtual scribes was associated with significant decreases in total EHR time, time spent on notes, and pajama time, all per appointment. Virtual scribes may be particularly effective among medical specialists and those physicians with greater baseline EHR time.

Indexed as

DocumentationElectronic Health RecordsPhysiciansAdultFemaleHumansMaleMiddle AgedQuality ImprovementRetrospective StudiesTime Factors

Identifiers

PMID38787556
PMCPMC11127114

What OpenQuestion holds

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LicenceCC BY
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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.