Trusted Data Spaces as a Viable and Sustainable Solution for Networks of Population-Based Patient Registries

Nicholas Nicholson,Sandra Caldeira, Artur Furtado, Ciaran Nicholl

JMIR public health and surveillance(2023)

引用 0|浏览5
暂无评分
摘要
Harmonization and integration of health data remain as the focus of many ongoing efforts toward the goal of optimizing health and health care policies. Population-based patient registries constitute a critical element of these endeavors. Although their main function is monitoring and surveillance of a particular disease within a given population, they are also an important data source for epidemiology. Comparing indicators across national boundaries brings an extra dimension to the use of registry data, especially in regions where supranational initiatives are or could be coordinated to leverage good practices; this is particularly relevant for the European Union. However, strict data protection laws can unintentionally hamper the efforts of data harmonization to ensure the removal of statistical bias in the individual data sets, thereby compromising the integrated value of registries' data. Consequently, there is the motivation for creating a new paradigm to ensure that registries can operate in an environment that is not unnecessarily restrictive and to allow accurate comparison of data to better ascertain the measures and practices that are most conducive to the public health of societies. The pan-European organizational model of cancer registries, owing to its long and successful establishment, was considered as a sound basis from which to proceed toward such a paradigm. However, it has certain drawbacks, particularly regarding governance, scalability, and resourcing, which are essential elements to consider for a generic patient registry model. These issues are addressed in a proposal of an adapted model that promises a valuable pan-European data resource for epidemiological research, while providing a closely regulated environment for the processing of pseudonymized patient summary data on a broader scale than has hitherto been possible.
更多
查看译文
关键词
population-based patient registries,trusted research environments,registry network model,data federation,cancer registries,noncommunicable diseases
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要