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DataSHIELD:在一个多站点联合分析平台中减轻披露风险.

Demetris Avraam1,2, Rebecca C Wilson2, Noemi Aguirre Chan3

  • 1Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, DK-1353, Denmark.

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数据盾 (DataSHIELD) 能够对大规模的健康数据进行联合分析,提高发现的有效性. 这种开源平台通过多层次的披露预防机制确保数据安全和隐私.

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科学领域:

  • 生物医学信息学 生物医学信息学
  • 流行病学 流行病学
  • 数据治理数据治理

背景情况:

  • 流行病学发现的有效性依赖于数据三角化和大型数据集.
  • 获取健康和生物医学数据往往受到实际,道德和法律以及治理约束的限制.
  • 跨司法管辖区的数据访问请求由于治理要求而耗时.

研究的目的:

  • 描述DataSHIELD的披露保护系统.
  • 将DataSHIELD作为一种解决方案,用于对健康和生物医学数据进行大规模统计分析.
  • 突出DataSHIELD在处理数据分析中的技术和监管挑战方面的能力.

主要方法:

  • DataSHIELD采用联合分析,使得远程数据分析无需数据传输.
  • 该平台与安全访问数据研究的"五个安全"框架保持一致.
  • 防止披露机制的多层系统可以在实时分析过程中减轻披露风险.

主要成果:

  • 数据盾提供实时远程统计分析.
  • 防止披露的机制在系统,分析和治理层面整合在一起.
  • 该软件在遵守数据治理的同时,方便对健康和生物医学数据进行大规模统计分析.

结论:

  • DataSHIELD提供了一个强大的解决方案,用于对敏感健康数据进行安全,联合分析.
  • 该平台解决了大规模研究数据访问和治理方面的挑战.
  • 通过安全的数据分析,DataSHIELD提高了流行病学发现的有效性.