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主题建模临床社会工作笔记,用于探索健康因素的社会决定因素

Shenghuan Sun¹, Travis Zack^1,2, Christopher Y K Williams¹

¹Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94158, United States.

|January 15, 2024

概括

社会工作笔记揭示了健康的重要社会决定因素 (SDoH) 数据,补充了医生记录. 主题建模有效地确定了SDoH主题,帮助针对有风险的患者进行有针对性的干预.

科学领域:

医疗信息学医疗信息学
社会工作研究社会工作研究
公共卫生公共卫生

背景情况:

关于健康社会决定因素 (SDoH) 的现有研究主要使用医生笔记和结构化电子健康记录数据.
社会工作笔记代表了一个未充分利用的资源,用于获取全面的SDoH信息.
社会工作者在解决社会和经济因素方面的角色使他们的笔记成为SDoH数据的宝贵来源.

研究的目的:

调查临床社会工作笔记作为SDoH信息来源的有用性.
采用词汇频率分析和主题建模,在社会工作笔记中识别与SDoH相关的术语和主题.
将社会工作笔记中的SDoH内容与医生笔记进行比较.

主要方法:

分析了来自181,644名患者的0.95万份临床社会工作笔记.
进行了词汇频率分析,将术语与ICD-10章节相关联.
应用了隐性迪里克莱特分配 (LDA) 主题建模来识别流行的SDoH主题,按笔记类型和疾病组分层.

主要成果:

单词频率分析揭示了医疗术语,但也揭示了微妙的SDoH指标.
通过LDA主题建模,成功提取了11个与SDoH风险因素相关的不同主题 (例如,财务状况,虐待,社会支持,心理健康).
主题建模显示了SDoH主题在不同笔记类型和患者疾病组的变化.

结论:

隐性迪里克莱特分配 (LDA) 主题建模对于从社会工作笔记中提取SDoH主题是有效的.
社会工作笔记包含丰富,一致的SDoH信息,对患者护理有价值.
对社会工作笔记的分析可以为弱势群体提供有针对性的干预措施.

关键词:

电子健康记录是电子医疗记录.自然语言处理自然语言处理.健康的社会决定因素社会工作笔记社会工作笔记主题建模主题建模

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