AI Scribe Safety: Measuring What Happens After Signing

Unlabelled: Coiera and Fraile-Navarro question whether AI scribes are being evaluated on metrics that truly impact care. While current evaluations focus on the quality of the initial draft, signed clinical notes are dynamic, as their content can be copied, summarized, coded, and re-ingested by downstream AI tools. We argue that safety must be measured downstream, focusing on how small errors in initial documentation can compound across the patient's electronic health record.

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Publication Details

Journal
JMIR Medical Informatics
Published
2026-08-10
DOI
https://doi.org/10.2196/103162
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Scribe Safety: Measuring What Happens After Signing

Vera Sorin, Eyal Klang
JMIR Medical Informatics
Artificial Intelligence in Healthcare and Education
article

AI Scribe Safety: Measuring What Happens After Signing

Vera Sorin, Eyal Klang
article en

Abstract

Unlabelled: Coiera and Fraile-Navarro question whether AI scribes are being evaluated on metrics that truly impact care. While current evaluations focus on the quality of the initial draft, signed clinical notes are dynamic, as their content can be copied, summarized, coded, and re-ingested by downstream AI tools. We argue that safety must be measured downstream, focusing on how small errors in initial documentation can compound across the patient's electronic health record.

JMIR Medical InformaticsVol. 14
Beth Israel Deaconess Medical Center (US), Mayo Clinic (US), Mayo Clinic in Arizona (US), Mayo Clinic in Florida (US)
Openalex Percentile: Top 13%
Artificial Intelligence in Healthcare and Education
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