在医疗保健数据生态系统中探索元数据目录:分类学发展研究
Simon Scheider1, Mostafa Kamal Mallick1
1Fraunhofer Institute for Software and Systems Engineering, Dortmund, Germany.
本研究介绍了20个维度和101个特征的分类法,用于设计有效的健康元数据目录 (HMDC),以加强在欧洲医疗保健中的数据共享. 这些发现为开发FAIR (可查找,可访问,可互操作,可重复使用) 的健康数据生态系统提供了实际指导.
科学领域:
- 医疗信息学 医疗信息学
- 信息系统工程 信息系统工程
- 数据治理数据治理
背景情况:
- 欧洲医疗保健正在投资数据生态系统,以利用不断增加的健康数据.
- 健康元数据目录 (HMDC) 对于数据的分配,共享和使用至关重要,旨在实现 FAIR 原则.
- 对HMDCs的可操作设计知识很少,阻碍了开发和创新.
研究的目的:
- 探索HMDCs的结构设计元素.
- 用实证维度和特征来对HMDC进行分类.
- 为HMDC开发和理论提供可操作的设计知识.
主要方法:
- 一种基于信息系统指南的分类构建方法.
- 结合感应和演研究方法.
- 系统性文献综述 (38篇文章) 和多个案例研究 (17个HMDC),经过专家重点小组的改进.
主要成果:
- 20个维度和101个特征的经验基础的分类学,用于结构和分类 FAIR HMDC.
- 关键的设计考虑包括元数据资产和数据安全/治理.
- 通过4个专家共同创建的用例来证明分类学的相关性.
结论:
- 该研究提供了基本的,可操作的设计知识,用于在欧洲医疗保健中构建HMDC.
- 为从业者,科学家和政策制定者提供健康数据生态系统的指导.
- 解决了可操作的HMDC设计知识的研究缺口.
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