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  • 标题:Secure data analysis environments: can we agree on criteria for “Appropriate secure access” to linked health data?
  • 本地全文:下载
  • 作者:Louisa R Jorm ; Kim McGrail ; J. Charles Victor
  • 期刊名称:International Journal of Population Data Science
  • 电子版ISSN:2399-4908
  • 出版年度:2018
  • 卷号:3
  • 期号:4
  • 页码:1-2
  • DOI:10.23889/ijpds.v3i4.836
  • 出版社:Swansea University
  • 摘要:Many health data linkage ecosystems across the world have designed and implemented secure data analysis environments as one of their controls to protect patient privacy and confidentiality. These have been shaped by local legislation and data governance policies, available IT infrastructure and resources, and the skills and imagination of their architects. However, at present their various features and functionalities have not been reviewed, synthesised or contrasted. Burton et al [1] have proposed 12 criteria for Data Safe Havens in health and healthcare, which they conceptualise broadly as encompassing data governance and ethics, quality and curation of data repositories, and data security. Under this definition, secure analysis environments, which may or may not be integrated with data repositories, are a component of a Data Safe Haven, addressing the criterion “Appropriate secure access to individually identifying data”. To guide those building and operating these environments, and data custodians and stewards who need to assess their fitness-for-purpose, it would be of great value to discuss and agree an aggregate term (e.g. “Secure Data Lab”) that describes them, and to develop a more detailed set of criteria for what entails “Appropriate secure access” to linked health data.
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