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Appl Clin Inform 2025; 16(04): 1121-1135
DOI: 10.1055/a-2597-2017
Special Topic on Reducing-Technology Related Stress and Burnout

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

Hadeel Hassan
1   Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada
2   Program in Child Health Evaluative Sciences, Peter Gilgan Research Institute, The Hospital for Sick Children, Toronto, Canada
,
Amy R. Zipursky
2   Program in Child Health Evaluative Sciences, Peter Gilgan Research Institute, The Hospital for Sick Children, Toronto, Canada
3   Department of Emergency Medicine, The Hospital for Sick Children, Toronto, Canada
,
Naveed Rabbani
4   Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, United States
,
Jacqueline G. You
5   Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts, United States
6   Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
,
Gabe Tse
7   Department of Pediatrics, Stanford University, Stanford, California, United States
,
Evan Orenstein
8   Information Services and Technology, Children's Healthcare of Atlanta, Atlanta Georgia, United States
9   Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States
,
Mondira Ray
10   Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, United States
,
Chase Parsons
10   Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, United States
,
Stella Shin
8   Information Services and Technology, Children's Healthcare of Atlanta, Atlanta Georgia, United States
9   Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States
,
Gregory Lawton
11   Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
,
Karim Jessa
3   Department of Emergency Medicine, The Hospital for Sick Children, Toronto, Canada
,
Lillian Sung
1   Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada
2   Program in Child Health Evaluative Sciences, Peter Gilgan Research Institute, The Hospital for Sick Children, Toronto, Canada
,
Adam P. Yan
1   Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada
2   Program in Child Health Evaluative Sciences, Peter Gilgan Research Institute, The Hospital for Sick Children, Toronto, Canada
› Author Affiliations
Funding J.G.Y. and M.R. are supported by the National Library of Medicine/National Institutes of Health grant (grant no.: T15LM007092). L.S. is supported by the Canada Research Chair in Pediatric Oncology Supportive Care.
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Abstract

Background

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.

Objectives

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.

Methods

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.

Results

Eleven studies met the inclusion criteria, with 10 published in 2024. The most frequently used AI scribe was Dragon Ambient eXperience (n = 7, 64%). While clinicians often reported improved documentation quality, AI scribe accuracy varied, frequently requiring manual edits and raising occasional concerns about errors. Nine of 10 studies reported improvements in at least one efficiency metric, and seven of ten studies highlighted positive effects on clinician wellness and burnout. Patient experience was assessed in three studies, all reporting favorable outcomes.

Conclusion

AI scribes represent a promising tool for improving clinical efficiency and alleviating documentation burden. This systematic review highlights the potential benefits of AI scribes, including reduced documentation time and enhanced clinician satisfaction, while also identifying critical challenges such as variable adoption, performance limitations, and gaps in evaluation.

Keywords

artificial intelligence - electronic health records and systems - ambient scribe - natural language processing - data processing - clinical data management - ambient listening

Protection of Human and Animal Subjects

No human subjects were involved in the project.


Supplementary Material



Publication History

Received: 18 February 2025

Accepted: 29 April 2025

Accepted Manuscript online:
30 April 2025

Article published online:
19 September 2025

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