对临床数据跨境联合分析的隐私保护工作流程
Miroslav Puskaric1, Balasubramanian Chandramouli2, Thomas Osmo3
1HLRS, University of Stuttgart, Germany.
Studies in health technology and informatics
|August 23, 2024
概括
这项研究开发了一种安全的联合数据分析工作流程,用于跨境的敏感患者信息. 保护隐私的方法确保了数据安全,而不会影响分析结果,证明了其适用于跨境研究的可行性.
科学领域:
- 医疗信息学 医疗信息学
- 数据安全 数据安全
- 流行病学 流行病学
背景情况:
- 在不同司法管辖区分析敏感的患者数据带来了重大隐私挑战.
- 由于法律和道德限制,共享个人级别的数据往往是不可能的.
研究的目的:
- 开发和验证一个保护隐私的联合数据分析工作流程.
- 允许对敏感的临床数据进行安全的跨境分析,而不暴露患者层面的信息.
- 展示数据协调在联合分析框架中的整合.
主要方法:
- 使用开源软件和DataSHIELD库设计了一个联合的数据分析工作流.
- 工作流使用R语言进行统计计算,并确保数据保持在远程站点.
- 在安全工作流中实施和展示数据协调技术.
主要成果:
- 联合工作流成功地对来自泛欧洲SARS-Cov-2队列 (ORCHESTRA项目) 的敏感临床数据集进行了数据分析.
- 结果与集中分析进行了验证,证实了同等的结果,而不影响患者的隐私.
- 该研究表明了跨境联合分析框架的可行性.
结论:
- 联合数据分析是安全的,涉及敏感健康数据的跨境研究的可行方法.
- 维护数据安全,可用性和可用性需要对数据协调,匿名化和IT基础设施给予密切关注.
- 这种保护隐私的方法取得了与传统集中式方法相美的分析结果.
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