共同治理模式:一种避免在现有可信的研究环境之间进行数据分离的方法
Fatemeh Torabi1,2, Chris Orton1,3,4, Emma Squires1,2,4
1Population Data Science, Swansea University, Swansea, SA2 8PP.
International journal of population data science
|February 29, 2024
概括
值得信赖的研究环境 (TREs) 允许使用"五个安全"框架安全访问数据. 标准化TRE治理对于多TRE协作和联合分析至关重要,提高研究精度和罕见疾病研究.
科学领域:
- 医疗信息学 医疗信息学
- 数据治理数据治理
- 生物信息学是一种生物信息学.
背景情况:
- 值得信赖的研究环境 (TREs) 通过数据库来促进安全的数据访问.
- 有五个保险柜.
- 框架,但缺乏标准化的方法阻碍了跨TRE数据分析.
- 在英国TREs的不同治理模式限制了相互理解和合作的潜力.
研究的目的:
- 记录英国主要TRE的治理特征,为国家分析做出贡献.
- 确定促进多TRE协作和联合分析的要素.
主要方法:
- 总结了15个英国TRE的治理特征 (数据访问,请求程序,模型).
- 进行了多个TRE协作分析的案例研究.
- 在治理和架构考虑中确定了联合分析的共同点.
主要成果:
- 所有15个英国TRE都允许对汇总输出进行聚合分析.
- 数据访问请求和披露控制程序在TRE之间有很大的差异.
- 在2023年,40%的TREs拥有ISO 20071认证;56.2%参与了四国分析.
结论:
- 安全的多TRE个人级数据分析在技术上是可行的,但需要强大的治理框架.
- 一个标准化的治理模式对于将TRE演变成一个有凝聚力的多TRE生态系统至关重要.
- 解决利益相关者和公众的关切对于成功的多TRE数据共享至关重要.
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