Evidence map›Paper›PMID 40306686›Full record

SynthesisApplied clinical informatics2025

Clinical Implementation of Artificial Intelligence Scribes in Health Care: A Systematic Review.

Hadeel Hassan, Amy R Zipursky, Naveed Rabbani, Jacqueline G You, Gabriel Tse, Evan Orenstein, Mondira Ray, Chase Parsons, Stella Shin, Gregory Lawton and 3 more

Erratum issuedAbstract readSystematic Review
In one paragraph

Synthesis in Applied clinical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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.

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

26 citing papers in PubMed.

  1. Article
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  6. Article
  7. Strengths and Potential Pitfalls of the Use of Artificial Intelligence in Psychiatric Education and Practice.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026
    Article
  8. Article
  9. Article
  10. Review
  11. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Hadeel HassanDivision of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada.
Amy R ZipurskyProgram in Child Health Evaluative Sciences, Peter Gilgan Research Institute, The Hospital for Sick Children, Toronto, Canada.
Naveed RabbaniDepartment of Pediatrics, Harvard Medical School, Boston, Massachusetts, United States.
Jacqueline G YouDepartment of Pathology, Massachusetts General Hospital, Boston, Massachusetts, United States.
Gabriel TseDepartment of Pediatrics, Stanford University, Stanford, California, United States.
Evan OrensteinInformation Services and Technology, Children's Healthcare of Atlanta, Atlanta Georgia, United States.
Mondira RayDepartment of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, United States.
Chase ParsonsDepartment of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, United States.
Stella ShinInformation Services and Technology, Children's Healthcare of Atlanta, Atlanta Georgia, United States.
Gregory LawtonDepartment of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Karim JessaDepartment of Emergency Medicine, The Hospital for Sick Children, Toronto, Canada.
Lillian SungDivision of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada.
Adam P YanDivision of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada.

Funding

RESEARCH TRAINING-MEDICAL INFORMATICS 90T15LM007092 · NLM · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Nils Gehlenborg · 1992 to 2026
$32.8M
NLM NIH HHS T15 LM007092
6 · The paper itself

Abstract

Artificial intelligence (AI) scribes use advanced speech recognition and natural language processing to automate clinical documentation and ease administrative burden. However, little is known about the effect of AI scribes on clinicians, patients, and organizations.This study aimed to (1) propose an evaluation framework to guide future AI scribe implementations, (2) describe the effect of AI scribes along the domains proposed in the developed evaluation framework, and (3) identify gaps in the AI scribe implementation literature to be evaluated in future studies.Databases including Embase, Embase Classic, and Ovid Medline were searched, and a manual review was conducted of the New England Journal of Medicine AI. Studies published after 2021 that reported on the implementation of AI scribes in health care were included. Descriptive analysis was undertaken. Quality assessment was undertaken using the Newcastle-Ottawa Scale. The nominal group technique was used to develop an evaluation framework.Eleven studies met the inclusion criteria, with 10 published in 2024. The most frequently used AI scribe was Dragon Ambient eXperience (

Indexed as

Artificial IntelligenceDelivery of Health CareDiffusion of InnovationDocumentationImplementation ScienceHumansNatural Language Processing

Identifiers

PMID40306686
PMCPMC12449105

What OpenQuestion holds

Textmetadata
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.