患者饮食补充剂使用:临床笔记的自然语言处理结果是否与调查数据一致?
Douglas Redd1,2, Terri Elizabeth Workman2,3, Yijun Shao2,3
1Center for Data Science and Outcome Research, Washington DC VA Medical Center, Washington, DC 20422, USA.
Medical sciences (Basel, Switzerland)
|June 27, 2023
概括
许多患者在没有医疗指导的情况下使用食补充剂,导致未知的药物相互作用. 一个自然语言处理 (NLP) 工具在临床笔记中有效地检测到补充剂的使用,尽管患者报告各不相同.
科学领域:
- 药理学 药理学是指药理学的学科.
- 医疗信息学 医疗信息学
- 自然语言处理自然语言处理.
背景情况:
- 饮食补充剂的使用很普遍,通常没有医生监督.
- 补充剂和药物之间的潜在相互作用对患者构成风险.
- 目前的电子健康记录不足以记录补充剂的使用情况.
研究的目的:
- 开发和评估一种自然语言处理 (NLP) 工具,用于在临床笔记中检测食补充剂的使用.
- 评估NLP识别的补充剂使用与患者自我报告之间的相关性.
主要方法:
- 研究了一组来自三个医疗机构的377名患者.
- 创建了一个新的NLP工具,可以从非结构化的临床笔记中提取补充信息.
- 用患者调查收集自我报告的补充剂使用数据进行比较.
主要成果:
- NLP模型在整体补充剂检测方面获得了0.914的高F1得分.
- 对于个别补充剂的检测准确性各不相同,在0.83和叶酸在0.39的F1分数.
- 在笔记中记录的补充剂使用和患者自我报告之间观察到显著的差异.
结论:
- 自然语言处理在从临床文档中识别食补充剂使用方面表现强.
- 患者自我报告的补充剂摄入量可能与医疗记录中记录的信息不一致.
- 医疗保健机构对补充剂使用的记录方法的改进是有必要的,以确保患者的安全.
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