Gkoulalas-Divanis Aris, Loukides Grigorios, Sun Jimeng
IBM Research-Ireland, Damastown Industrial Estate, Mulhuddart, Dublin 15, Ireland.
School of Computer Science & Informatics, Cardiff University, 5 The Parade, Roath, Cardiff CF24 3AA, UK.
J Biomed Inform. 2014 Aug;50:4-19. doi: 10.1016/j.jbi.2014.06.002. Epub 2014 Jun 14.
The dissemination of Electronic Health Records (EHRs) can be highly beneficial for a range of medical studies, spanning from clinical trials to epidemic control studies, but it must be performed in a way that preserves patients' privacy. This is not straightforward, because the disseminated data need to be protected against several privacy threats, while remaining useful for subsequent analysis tasks. In this work, we present a survey of algorithms that have been proposed for publishing structured patient data, in a privacy-preserving way. We review more than 45 algorithms, derive insights on their operation, and highlight their advantages and disadvantages. We also provide a discussion of some promising directions for future research in this area.
电子健康记录(EHRs)的传播对于一系列医学研究非常有益,从临床试验到疫情控制研究,但必须以保护患者隐私的方式进行。这并非易事,因为传播的数据需要防范多种隐私威胁,同时还要对后续分析任务有用。在这项工作中,我们对为以隐私保护方式发布结构化患者数据而提出的算法进行了综述。我们审查了45多种算法,深入了解它们的运行情况,并突出它们的优缺点。我们还对该领域未来研究的一些有前景的方向进行了讨论。