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.
Authors
- Vera Sorin (ORCID: https://orcid.org/0000-0003-0509-4686)
- Eyal Klang (ORCID: https://orcid.org/0000-0002-4567-3108)
Institutions
- Beth Israel Deaconess Medical Center (US)
- Mayo Clinic (US)
- Mayo Clinic in Arizona (US)
- Mayo Clinic in Florida (US)
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