在临床文档中识别污名化语言:对新兴文献的范围审查
Veronica Barcelona1, Danielle Scharp1, Betina R Idnay2
1Columbia University School of Nursing, New York, New York, United States of America.
PloS one
|June 28, 2024
概括
电子健康记录 (EHR) 中的污名化语言反映了隐含的偏见,并影响了患者的护理. 自然语言处理 (NLP) 提供了一种有希望的方法来识别和减轻临床文档中的这种偏见.
科学领域:
- 健康 公平 卫生 公平
- 医疗信息学 医疗信息学
- 卫生社会学 卫生社会学
背景情况:
- 种族主义和隐含的偏见导致医疗保健差距.
- 电子健康记录 (EHR) 中的污名化语言是一个新兴的关注领域.
- 这种语言可能会对患者的护理和结果产生负面影响.
研究的目的:
- 进行对电子人权书籍中对污名化语言的文献进行范围审查.
- 识别,描述和评估有关这个主题的现有研究.
- 了解临床医生笔记中污名化语言的影响.
主要方法:
- 搜索了主要的数据库 (PubMed,CINAHL,Embase) 并进行了手动搜索.
- 包括到2022年4月发表的研究.
- 使用EndNote和Covidence进行数据管理和选.
主要成果:
- 审查了9项采用不同方法的研究 (横截面,定性,混合方法,队列).
- 通过内容分析,采访和专家指南,识别了污名化的语言.
- 在四项研究中使用自然语言处理 (NLP) 来检测偏见的语言.
- 所有研究都得出结论,对语言的污名化会对患者的感知和结果产生负面影响.
结论:
- NLP是一种新兴的工具,用于检测EHR中的污名化语言.
- 基于NLP的系统可以选文档并提醒临床医生.
- 这项研究可以提高人们对沟通中隐含偏见的认识,并促进公平的医疗保健.
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