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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月21日

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  • Arash A. Nargesi,
  • Jacqueline G. You,
  • Danielle S. Bitterman,
  • Marc D. Succi,
  • Rebecca G. Mishuris,
  • Eric G. Poon,
  • Adam B. Landman

摘要

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.