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ReflectOR: an LLM-based Agent for Post-Operative Surgical Debriefing.

Lorenzo Fumi1, Marco Bombieri1, Sara Allievi2

  • 1Department of Information Engineering and Computer Science, University of Trento, Italy.

... International Workshop on Spoken Dialogue Systems Technology. International Workshop on Spoken Dialogue Systems Technology
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Summary
This summary is machine-generated.

Surgical debriefings are crucial for patient safety but often rushed. ReflectOR, an AI system, processes operating room audio to support these sessions, enhancing team performance and identifying potential errors.

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Area of Science:

  • Medical Error Prevention
  • Artificial Intelligence in Healthcare
  • Surgical Safety

Background:

  • Ineffective teamwork and communication in surgery can lead to medical errors.
  • Post-operative debriefings are vital for improving surgical team performance and patient safety.
  • Clinicians' time constraints often result in rushed or incomplete debriefing sessions.

Purpose of the Study:

  • To introduce ReflectOR, an Agentic-AI architecture designed to assist surgical debriefings.
  • To leverage AI for processing operating room audio recordings to support debriefing processes.
  • To address the challenges of time limitations in conducting effective surgical debriefings.

Main Methods:

  • Development of an Agentic-AI architecture named ReflectOR.
  • Utilizing specialized sub-agents for distinct debriefing support tasks.
  • Processing audio recordings from the operating room environment.

Main Results:

  • ReflectOR employs sub-agents for summary generation, event timeline construction, error identification, and material tracking.
  • Qualitative evaluation demonstrated the system's effectiveness in contextualizing transcripts.
  • The AI architecture shows potential as a valuable tool for surgical debriefing.

Conclusions:

  • ReflectOR offers a novel AI-driven approach to enhance surgical debriefing quality and efficiency.
  • The system can help overcome time constraints faced by clinicians.
  • Key considerations for real-world clinical implementation of AI in surgical debriefing are discussed.