健康数据生态系统的演变:一项国际调查
Jordan P Lerner-Ellis1, E Magda Price2, Shazia Subhani3
1Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada; Lunenfeld-Tanenbaum Research Institute, Toronto, ON M5G 1X5, Canada.
American journal of human genetics
|July 22, 2025
概括
国际卫生数据生态系统 (HDEs) 显示出高度兴趣,但面临数据共享障碍. 项目多样性,而不是共同的假设,是HDE的特征,这表明独特的特征可能会阻碍集体数据共享努力.
科学领域:
- 医疗信息学 医疗信息学
- 健康 数据科学 数据科学
- 国际卫生系统 国际卫生系统
背景情况:
- 健康数据生态系统 (HDEs) 正因其在推进健康研究和护理方面的潜力而引起全球关注.
- 尽管人们越来越感兴趣,但仍有大量的金融,司法和技术障碍阻碍了HDE内部广泛的数据共享.
- 了解各种高质量企业的运营特征和成功因素对于优化数据共享和集体行动至关重要.
研究的目的:
- 对健康数据生态系统 (HDEs) 进行国际调查,以了解其运营概况和数据共享实践.
- 确定影响高水平教育机构发展和有效性的因素.
- 探索挑战和潜在的解决方案,以加强全球HDE的数据共享.
主要方法:
- 采用结构化采访方法,与来自13个国际HDE的高级项目团队成员进行了采访,其中包括H3非洲项目.
- 收集的数据包括医疗保健系统的集中化,项目开始日期,融资模式,IT基础设施和数据共享任务的实施.
- 对面试数据进行了定性分析,以确定共同的主题和操作特征.
主要成果:
- 观察到全球对HDE的兴趣很高,与数据共享的持续障碍并存.
- 没有证据支持常见的假设,即早期启动日期或自上而下的政府任务在HDE开发中具有优势.
- 没有确定HDE有效性,价值或成功的最终参考模型;项目多样性显著.
结论:
- 个体HDE的独特多样性可能无意中阻碍了集体行动,如数据共享.
- 需要进一步的研究来了解HDE开发中遇到的陷,并确定克服这些陷的有效策略.
- 先进的评估工具,如欧盟的成熟度水平模型 (MLM),可以帮助国家评估其HDE发展阶段并规划未来战略.
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