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Tracing the Pen: Electronic Health Records Amid the Rise of Generative AI

Year: 2026
Type: article
Abstract: Large language models (LLMs) are poised to transform physician interactions with electronic health records (EHRs) by assisting clinical documentation, drafting preliminary diagnostic reports, and supporting patient communication. While LLMs reduce administrative burden, their integration in clinical workflows introduces the risk of blending AI- and human-generated content within EHRs. This perspective reviews technological and policy solutions to ensure traceability of AI-generated content in EHRs to preserve clinical integrity.
DOI: 10.1038/s41746-026-02508-6
Authors: Arash A. Nargesi, Jacqueline G. You, Danielle S. Bitterman, Marc D. Succi, Rebecca G. Mishuris, Eric G. Poon, Adam B. Landman
Institutions: Broad Institute, Brigham and Women's Hospital, Mass General Brigham, Massachusetts General Hospital, Duke University, Duke Medical Center, Brown University
Language: English
Field: Medicine
Open Access status: gold
Estimated APC paid: $4,090
OpenAlex ID: W7155074516
FWCI: 3.67
Cites: 61
Cited by: 2
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