在医疗保健和健康研究中的数据质量和多样性
Solveig Bünz1, Sonja Harkener1, Jürgen Stausberg1
1Institute for Medical Informatics, Biometry and Epidemiology, Faculty of Medicine, University Duisburg-Essen, Essen, Germany.
Studies in health technology and informatics
|May 17, 2025
概括
卫生系统数据质量不佳可能会对多样性,公平性和包容性产生负面影响. 处理数据质量对于公平的健康研究和护理至关重要,特别是关于年龄,种族,性别,性别和社会地位.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健服务研究 医疗服务研究
- 数据科学数据科学数据科学
背景情况:
- 数据驱动的卫生系统越来越重要.
- 数据质量不足对多样性,公平性和包容性 (DEI) 构成风险.
- 了解数据质量和DEI之间的联系对于公平的健康结果至关重要.
研究的目的:
- 识别和分析数据质量与健康研究和护理中的多样性之间的关系的证据.
- 要突出来自数据质量差的DEI风险.
- 为健康领域的数据收集和管理提供最佳实践信息.
主要方法:
- 进行了文献审查,以找到有关数据质量和多样性的研究.
- 对13项选定的研究进行了描述性分析.
- 分析的重点是年龄,种族和种族,性别和性别以及社会地位等方面.
主要成果:
- 确定了DEI的风险,包括错误分类和缺失的数据.
- 广泛的分类和缺乏文化意识会对数据质量产生负面影响.
- 在年龄,种族,种族,性别,性别和社会地位方面注意到了具体的担忧.
结论:
- 确保数据质量对于保持多样性,公平性和健康中的包容性至关重要.
- 对DEI风险的考虑必须纳入健康数据的规划和管理.
- 医疗研究和医疗保健机构都需要改进数据质量实践.
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