将多样性,公平,包容性和可访问性整合到健康数据讲故事模型中信息学教育教育信息学
Grace Gao1, Christie L Martin2, Alvin D Jeffery3
1School of Nursing, St Catherine University, St Paul, Minnesota, United States.
Applied clinical informatics
|August 30, 2024
概括
这项研究增强了健康信息学教育的检查清单,改善了收集和评估多样性,公平,包容性和可访问性 (DEIA) 数据的方法. 更新的DEIA检查清单,使用健康人2030资源,有助于创建公平的数据故事,以解决健康差异.
科学领域:
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
- 公共卫生 公共卫生
背景情况:
- 医疗信息教育必须整合多样性,公平,包容性和可访问性 (DEIA) 的原则.
- 在公平考虑下利用数据对于了解患者护理和结果至关重要.
- 公共可用的健康人2030 (HP2030) 资源可以通过DEIA镜头增强信息学教育.
研究的目的:
- 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.
- 准备未来的计算机专家批判性地评估数据中的DEIA特征.
- 支持创建以公平为导向的数据讲故事.
主要方法:
- 使用了DEI导向数据叙述模型和HP2030框架来开发DEIA检查清单.
- 采用非正式的认知步骤来扩大检查清单.
- 在HP2030健康的社会决定因素 (SDOH) 数据集中使用检查清单评估DEIA措施.
主要成果:
- 审查了76个与SDOH相关的数据集,为"人口统计"增加了6个措施,为"技能,能力和可访问性"增加了7个措施.
- 经过验证,HP2030包含了除"宗教/信仰"外的所有DEIA措施.
- 与公平性和可访问性相关的DEIA措施,并注意到包括"语言"和"图像"特征.
结论:
- HP2030人口统计数据资源是可访问和全面的,用于解决SDOH和促进包容性数据表示.
- 该DEIA检查清单有助于从股权信息的角度进行公正的数据收集和对SDOH数据的可视化.
- 将公平的数据讲故事与HP2030等框架相结合,丰富了健康信息学教育,并支持对健康差异的干预.
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