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Enhancing Patient Safety Event Analysis Using Artificial Intelligence: A Pilot Study of an Artificial

Zoe M Pruitt1, Garrett Zabala1, Katharine Adams2

  • 1MedStar Health National Center for Human Factors in Healthcare.

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|January 22, 2026
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Summary

An AI tool aids patient safety event (PSE) report analysis, helping identify trends and improve workflow efficiency. This technology supports analysts in uncovering novel insights within large safety databases.

Keywords:
AI in health carehealth care algorithmspatient safetypatient safety event reportspatient safety reporting software

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Area of Science:

  • Health Informatics
  • Artificial Intelligence in Healthcare
  • Patient Safety Research

Background:

  • Analyzing large volumes of patient safety event (PSE) reports presents a significant challenge.
  • Existing methods may not efficiently support analysts in uncovering novel trends.

Purpose of the Study:

  • To develop and evaluate an AI-powered software tool for analyzing patient safety event (PSE) reports.
  • To assess the tool's potential to support analysts and identify new trends in patient safety data.

Main Methods:

  • Pilot evaluation across seven organizations (4 healthcare facilities, 3 patient safety organizations).
  • Feedback collected via interviews with patient safety analysts.
  • Analysis of findings using a human cognition framework for information visualization.

Main Results:

  • 6 out of 7 institutions reported the tool aided in identifying valuable insights (e.g., procedural errors, categorization inconsistencies, medication/device issues).
  • Emerging themes algorithm effectively highlighted undetected patterns and novel keywords.
  • Design principles improved report review efficiency, though narrative data quality posed limitations.

Conclusions:

  • The AI tool shows potential for enhancing patient safety analysis by supporting trend and pattern detection.
  • Future work will address limitations and refine data organization for improved usability based on user mental models.