: Towards Autonomous Electronic Health Record Navigation.

Journal: Research square
Published Date:

Abstract

Clinicians spend large amounts of time on clinical documentation, and inefficiencies impact quality of care and increase clinician burnout. Despite the promise of electronic medical records (EMR), the transition from paper-based records has been negatively associated with clinician wellness, in part due to poor user experience, increased burden of documentation, and alert fatigue. In this study, we present Almanac Copilot, an autonomous agent capable of assisting clinicians with EMR-specific tasks such as information retrieval and order placement. On EHR-QA, a synthetic evaluation dataset of 300 common EHR queries based on real patient data, Almanac Copilot obtains a successful task completion rate of 74% (n = 221 tasks) with a mean score of 2.45/3 (95% CI:2.34-2.56). By automating routine tasks and streamlining the documentation process, our findings highlight the significant potential of autonomous agents to mitigate the cognitive load imposed on clinicians by current EMR systems.

Authors

  • Zakka Cyril
    Department of Cardiothoracic Surgery, Stanford Medicine.
  • Cho Joseph
    Department of Cardiothoracic Surgery, Stanford Medicine.
  • Fahed Gracia
    Department of Cardiovascular Medicine, Stanford Medicine.
  • Shad Rohan
    Division of Cardiovascular Surgery, Penn Medicine.
  • Moor Michael
    Department of Computer Science, Stanford University.
  • Fong Robyn
    Department of Cardiothoracic Surgery, Stanford Medicine.
  • Kaur Dhamanpreet
    Department of Cardiothoracic Surgery, Stanford Medicine.
  • Ravi Vishnu
    Byers Center for Biodesign, Stanford University.
  • Aalami Oliver
    Byers Center for Biodesign, Stanford University.
  • Daneshjou Roxana
    Department of Dermatology, Stanford Medicine.
  • Chaudhari Akshay
    Radiology & Integrative Biomedical Imaging Informatics, Stanford Medicine.
  • Hiesinger William
    Department of Cardiothoracic Surgery, Stanford Medicine.

Keywords

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