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医疗保健中的种族偏见:研究护理点工具和无意的从业者偏见对患者治疗和诊断的影响。

Racial biases in healthcare: Examining the contributions of Point of Care tools and unintended practitioner bias to patient treatment and diagnosis.

机构信息

Queen's University, Canada.

出版信息

Health (London). 2023 Sep;27(5):829-846. doi: 10.1177/13634593211061215. Epub 2021 Dec 7.

Abstract

Sophisticated algorithms are used daily to search through hundreds of medical journals in order to package updated medical insights into commercial databases. Healthcare practitioners can access these searchable databases-called Point of Care (PoC) tools-as downloadable apps on their smartphones or tablets to comprehensively and efficiently inform patient diagnosis and treatment. Because racist biases are unintentionally incorporated into the search reports that the companies generate and that practitioners regularly access, the aim of this article is to examine how healthcare practitioners' "pre-existing" racial stereotypes interact with pithy conclusions about race and ethnicity in PoC tools. I use qualitative research methods (content analysis, discourse analysis, open-ended semi-structured interviews, and role play) to frame the analysis within the Public Health Critical Race Praxis (PHCRP). This approach facilitates an understanding of how biological racism-the use of scientific evidence to support inherent differences between races-that is embedded in PoC algorithms informs a practitioner's assessment of a patient, and converges with persistent racial bias in medical training, medical research and healthcare. I contextualize the study with one semi-structured interview with an Editor of a leading PoC tool, MedScope (pseudonomized), and 10 semi-structured interviews with healthcare practitioners in S.E. Ontario, Canada. The article concludes that PoC tools and practitioners' personal biases contribute to racial prejudices in healthcare provision. This warrants further research on racial bias in medical literature and curriculum design in medical school.

摘要

复杂的算法每天都被用于搜索数百种医学期刊,以便将最新的医学见解打包到商业数据库中。医疗保健从业者可以通过智能手机或平板电脑访问这些可搜索的数据库——称为即时护理 (PoC) 工具——以全面、高效地为患者诊断和治疗提供信息。由于搜索报告中无意中纳入了公司生成的种族偏见,并且从业者经常访问这些报告,因此本文旨在探讨医疗保健从业者的“预先存在”种族刻板印象如何与 PoC 工具中关于种族和族裔的简洁结论相互作用。我使用定性研究方法(内容分析、话语分析、开放式半结构化访谈和角色扮演)将分析框架置于公共卫生批判种族实践 (PHCRP) 中。这种方法有助于理解即时护理算法中嵌入的生物种族主义——即利用科学证据来支持种族之间固有的差异——如何影响从业者对患者的评估,并与医学培训、医学研究和医疗保健中持续存在的种族偏见相融合。我通过对一位领先的 PoC 工具 MedScope(化名)的编辑的一次半结构化访谈和对加拿大安大略省东南部的 10 位医疗保健从业者的 10 次半结构化访谈来为研究提供背景。文章的结论是,PoC 工具和从业者的个人偏见导致了医疗保健服务中的种族偏见。这需要对医学文献和医学院课程设计中的种族偏见进行进一步研究。

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