数字标准化患者:人工智能教练在手术护理中培养文化敏捷性
Arya S Rao1,2,3, Richard S Lee1,2,3, Ethan Bott1,2,3
1Harvard Medical School, Boston, MA.
Journal of the American College of Surgeons
|July 24, 2025
概括
大型语言模型 (LLM) 显示出在培训外科住院医生文化灵巧方面具有前景. 基于LLM的标准化患者平台被认为是可行和有效的,用于实践文化敏感的沟通和解决患者的情绪.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 进行外科手术培训.
背景情况:
- 文化灵巧对于公平的外科护理至关重要.
- 标准化患者 (SP) 接触是有效的,但资源密集型.
- 大型语言模型 (LLM) 为培训提供了一个可扩展的替代方案.
研究的目的:
- 评估基于LLM的SP平台对文化技巧培训的可行性和感知有效性.
- 评估一般外科住院医生与模拟的文化敏感患者接触的经验.
主要方法:
- 一项为期两周的试点研究,涉及16名普通外科住院医生.
- 居民与一个新的SP-LLM平台互动,模拟文化敏感的场景.
- 互动后的调查评估了现实主义,情感深度,文化相关性和教育实用性.
主要成果:
- SP-LLM平台被认为是临床准确和现实的.
- 它支持文化敏感的沟通,并解决患者的情绪.
- 文本交互被青为反思;语音交互收到了混合的反.
结论:
- 基于LLM的SP平台显示了在外科手术中培养文化灵巧性的可扩展工具的潜力.
- 该平台具有临床相关性,并且有效地练习敏感沟通.
- 进一步发展可以增强现实主义和扩大对培训的准入.
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