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

Arash A Nargesi1,2,3, Jacqueline G You4,5, Danielle S Bitterman5,6,7

  • 1Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA, USA.

NPJ Digital Medicine
|April 21, 2026
PubMed
Summary

Large language models (LLMs) can help doctors with electronic health records (EHRs), but it is important to track AI-generated content to maintain medical accuracy and trust.

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Area of Science:

  • Health Informatics
  • Artificial Intelligence in Medicine
  • Clinical Workflow Optimization

Background:

  • Large language models (LLMs) offer significant potential to streamline physician tasks within electronic health records (EHRs).
  • These tasks include clinical documentation, preliminary report generation, and patient communication, aiming to reduce administrative workload.
  • However, the seamless integration of LLM-generated content into EHRs poses challenges regarding content traceability.

Purpose of the Study:

  • To explore the implications of integrating AI-generated content into EHR systems.
  • To review existing and proposed technological and policy solutions for ensuring the traceability of AI-generated content.
  • To maintain the integrity of clinical information within EHRs.

Main Methods:

  • This perspective paper reviews current literature and technological advancements.
  • It analyzes policy frameworks relevant to AI in healthcare.
  • The review focuses on solutions for distinguishing AI-generated from human-generated clinical data.

Main Results:

  • LLMs can reduce physician administrative burden in EHR tasks.
  • A critical challenge is the potential for undetectable blending of AI and human clinical documentation.
  • Traceability solutions are necessary to ensure accountability and data integrity.

Conclusions:

  • Ensuring the traceability of AI-generated content in EHRs is crucial for preserving clinical integrity.
  • A combination of technological safeguards and clear policy guidelines is required.
  • Proactive measures are needed to manage the risks associated with LLM integration in healthcare.