使用人工智能增强患者安全事件分析:对基于人工智能的报告分析工具进行试点研究
Zoe M Pruitt1, Garrett Zabala1, Katharine Adams2
1MedStar Health National Center for Human Factors in Healthcare.
Journal of patient safety
|January 22, 2026
概括
人工智能工具有助于分析患者安全事件 (PSE) 报告,帮助识别趋势并提高工作流程效率. 这项技术支持分析师在大型安全数据库中发现新的见解.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 患者安全研究 患者安全研究
背景情况:
- 分析大量的患者安全事件 (PSE) 报告是一个重大挑战.
- 现有的方法可能无法有效地支持分析师发现新趋势.
研究的目的:
- 开发和评估一款基于人工智能的软件工具,用于分析患者安全事件 (PSE) 报告.
- 评估该工具在支持分析师和识别患者安全数据新趋势方面的潜力.
主要方法:
- 在七个组织进行试点评估 (4个医疗机构,3个患者安全组织).
- 通过采访患者安全分析师收集的反.
- 使用人类认知框架进行信息可视化的发现分析.
主要成果:
- 7个机构中有6个报告说,该工具有助于识别有价值的见解 (例如程序错误,分类不一致,药物/设备问题).
- 新兴主题算法有效地突出了未被检测到的模式和新的关键词.
- 设计原则提高了报告审查效率,尽管叙事数据质量存在局限性.
结论:
- 人工智能工具显示了通过支持趋势和模式检测来增强患者安全分析的潜力.
- 未来的工作将解决局限性,并完善数据组织,以基于用户心理模型改进可用性.
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