This paper is in the following e-collection/theme issue:

Editorial (4) Ambient AI Scribes and AI-Driven Documentation Technologies (22) Electronic Health Records (1364) Clinical Communication, Electronic Consultation and Telehealth (793) Generative Language Models Including ChatGPT (775) AI Language Models in Health Care (230) Artificial Intelligence (2295) Adoption and Change Management of eHealth Systems (938) eHealth Infrastructures (435) New Technologies (115)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80898, first published .
AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration

AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration

AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration

Authors of this article:

Tiffany I Leung1, 2 Author Orcid Image ;   Andrew J Coristine1, 3 Author Orcid Image ;   Arriel Benis4 Author Orcid Image
Article Authors Cited by (8) Tweetations Metrics

Journals

  1. Palm E, Manikantan A, Mahal H, Belwadi S, Pepin M. Assessing the quality of AI-generated clinical notes: validated evaluation of a large language model ambient scribe. Frontiers in Artificial Intelligence 2025;8 View
  2. Scott I, Cresswell K, Williams R, van der Vegt A. How can we promote greater adoption of AI in healthcare?. BMJ Quality & Safety 2025:bmjqs-2025-019405 View
  3. Leiserowitz G, Mansfield J, MacDonald S, Jost M. Patient Attitudes Toward Ambient Voice Technology: Preimplementation Patient Survey in an Academic Medical Center. JMIR Medical Informatics 2025;13:e77901 View
  4. Coiera E, Fraile-Navarro D. AI Scribes: Are We Measuring What Matters?. JMIR Medical Informatics 2026;14:e89337 View
  5. Atiku S, Olakotan O, Owolanke K. Usability‐Related Barriers and Facilitators Influencing the Adoption and Use of AI Scribes in Healthcare: A Scoping Review. Journal of Evaluation in Clinical Practice 2026;32(1) View
  6. Ferreira Santos J, Dores H. Large Language Models in Cardiovascular Prevention: A Narrative Review and Governance Framework. Diagnostics 2026;16(3):390 View
  7. Menz B, Scarfo N, Modi N, Cornelisse E, Li L, Tan J, Gandhi J, Maher D, Kousa D, Daniel K, Menon V, Bacchi S, McKinnon R, Wiese M, Rowland A, Sorich M, Hopkins A. Vision-Enabled AI scribes reduce omissions in clinical conversations: evidence from simulated medication histories. npj Digital Medicine 2026 View

Books/Policy Documents

  1. Hirosawa T. Artificial Intelligence in Medical Diagnostics. View