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本文引用的文献

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Mitigating Racial And Ethnic Bias And Advancing Health Equity In Clinical Algorithms: A Scoping Review.减轻临床算法中的种族和民族偏见并促进健康公平:范围综述。
Health Aff (Millwood). 2023 Oct;42(10):1359-1368. doi: 10.1377/hlthaff.2023.00553.
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Developing and Evaluating a Diversity, Equity, and Inclusion Storytelling Model in Data Courses in an Academic Electronic Health Record.在学术电子健康记录中开发和评估数据课程中的多样性、公平性和包容性叙事模型。
AMIA Annu Symp Proc. 2023 Apr 29;2022:461-467. eCollection 2022.
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AMIA's Focus on Diversity, Equity, and Inclusion.美国医学信息学会对多元化、公平和包容的关注。
Appl Clin Inform. 2022 Oct;13(5):1161-1162. doi: 10.1055/a-1957-6669. Epub 2022 Oct 9.
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Addressing Health Equity and Social Determinants of Health Through Healthy People 2030.通过《健康人民 2030》解决健康公平和健康的社会决定因素问题。
J Public Health Manag Pract. 2021;27(Suppl 6):S249-S257. doi: 10.1097/PHH.0000000000001297.
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Dissecting racial bias in an algorithm used to manage the health of populations.剖析用于管理人群健康的算法中的种族偏见。
Science. 2019 Oct 25;366(6464):447-453. doi: 10.1126/science.aax2342.
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Principles of Inclusion, Diversity, Access, and Equity.包容、多元、可及与公平原则。
J Infect Dis. 2019 Aug 20;220(220 Suppl 2):S30-S32. doi: 10.1093/infdis/jiz198.
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An approach to studying social disparities in health and health care.一种研究健康与医疗保健方面社会差异的方法。
Am J Public Health. 2004 Dec;94(12):2139-48. doi: 10.2105/ajph.94.12.2139.

将多样性、公平性、包容性和可及性融入健康信息学教育的数据叙事模型。

Integrating Diversity, Equity, Inclusion, and Accessibility into a Data Storytelling Model for Health Informatics Education.

作者信息

Gao Grace, Martin Christie L, Jeffery Alvin D

机构信息

School of Nursing, St Catherine University, St Paul, Minnesota, United States.

School of Nursing, University of Minnesota, Minneapolis, Minnesota, United States.

出版信息

Appl Clin Inform. 2024 Oct;15(5):1066-1073. doi: 10.1055/a-2407-1329. Epub 2024 Aug 30.

DOI:10.1055/a-2407-1329
PMID:39214145
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11634530/
Abstract

BACKGROUND

Health informatics education is pivotal in integrating diversity, equity, inclusion, and accessibility (DEIA) principles into curricula and leveraging data with equity considerations. Integrating clinically driven data with other datasets is crucial to comprehensive understanding of patient care demographics, experiences, and outcomes to create equity-minded data storytelling. Publicly available Healthy People 2030 (HP2030) resources complement academic electronic health records, supporting tailored learning activities in informatics education to enhance educational utility through a DEIA lens.

OBJECTIVES

This case report describes the expansion of an existing diversity, equity, and inclusion (DEI) checklist to an updated DEIA checklist for preparing future informaticians to collect and critically evaluate DEIA features using this checklist in creating equity-minded data storytelling.

METHODS

The DEI-Oriented Data Storytelling Model and the HP2030 framework were utilized to develop the DEIA checklist. We employed an informal cognitive walkthrough to expand the DEIA checklist and evaluate the DEIA measures or characteristics within datasets from the HP2030 social determinants of health (SDOH) five topics using this checklist.

RESULTS

We reviewed 76 available SDOH-related datasets and added six measures to "demographics" and seven to "skills, abilities, and accessibility" of the DEIA checklist. Our evaluation of the DEIA checklist verified HP2030's inclusion of all measures, except "religions/beliefs." All DEIA measures were linked to equity and accessibility, one in inclusion, and the inclusion of three characteristics comprising the category "language" and six characteristics comprising the category "images."

CONCLUSION

Results highlighted the accessibility and comprehensiveness of HP2030 demographic data resources, considering SDOH factors and promoting inclusive data representation to address health disparities. The DEIA checklist provides a structured tool in facilitating unbiased data collection and visualization of SDOH-related data through an equity-informed lens. Integrating an equity-minded data storytelling with frameworks like HP2030 enriches health informatics education, broadens students' understanding of health disparities, and supports evidence-based interventions for improved health outcomes.

摘要

背景

健康信息学教育对于将多样性、公平性、包容性和可及性(DEIA)原则融入课程以及在公平考量下利用数据至关重要。将临床驱动的数据与其他数据集整合对于全面理解患者护理人口统计学、经历和结果以创建注重公平的数据叙事至关重要。公开可用的《健康人民2030》(HP2030)资源补充了学术电子健康记录,支持信息学教育中的定制学习活动,以通过DEIA视角提高教育效用。

目的

本病例报告描述了将现有的多样性、公平性和包容性(DEI)清单扩展为更新的DEIA清单,以使未来的信息学专业人员能够使用该清单收集并批判性地评估DEIA特征,从而创建注重公平的数据叙事。

方法

采用以DEI为导向的数据叙事模型和HP2030框架来制定DEIA清单。我们运用非正式认知演练来扩展DEIA清单,并使用该清单评估HP2030健康社会决定因素(SDOH)五个主题的数据集中的DEIA措施或特征。

结果

我们审查了76个可用的与SDOH相关的数据集,并在DEIA清单的“人口统计学”中增加了六项措施,在“技能、能力和可及性”中增加了七项措施。我们对DEIA清单的评估验证了HP2030包含了除“宗教/信仰”之外的所有措施。所有DEIA措施都与公平性和可及性相关联,一项与包容性相关联,还包括构成“语言”类别的三个特征和构成“图像”类别的六个特征。

结论

结果突出了HP2030人口数据资源的可及性和全面性,考虑了SDOH因素并促进包容性数据呈现以解决健康差异问题。DEIA清单提供了一个结构化工具,有助于通过公平知情的视角进行无偏见的数据收集和SDOH相关数据的可视化。将注重公平的数据叙事与HP2030等框架相结合丰富了健康信息学教育,拓宽了学生对健康差异的理解,并支持基于证据的干预措施以改善健康结果。