Anonymization for outputs of population health and health services research conducted via an online data center. (19th December 2016)

• Record Type: Journal Article
• Authors: O'Keefe, Christine M; Westcott, Mark; O'Sullivan, Maree; Ickowicz, Adrien; Churches, Tim
• Is Part Of: Journal of the American Medical Informatics Association. Volume 24:Number 3(2017:May)
• Page Start: 544
• Page End: 549
• Publication Date: 2016-12-19
• Subjects: data anonymization -- confidentiality -- privacy -- biomedical research -- health services research; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocw152
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract : Objective: Online data centers (ODCs) are becoming increasingly popular for making health-related data available for research. Such centers provide good privacy protection during analysis by trusted researchers, but privacy concerns may still remain if the system outputs are not sufficiently anonymized. In this article, we propose a method for anonymizing analysis outputs from ODCs for publication in academic literature. Methods: We use as a model system the Secure Unified Research Environment, an online computing system that allows researchers to access and analyze linked health-related data for approved studies in Australia. This model system suggests realistic assumptions for an ODC that, together with literature and practice reviews, inform our solution design. Results: We propose a two-step approach to anonymizing analysis outputs from an ODC. A data preparation stage requires data custodians to apply some basic treatments to the dataset before making it available. A subsequent output anonymization stage requires researchers to use a checklist at the point of downloading analysis output. The checklist assists researchers with highlighting potential privacy concerns, then applying appropriate anonymization treatments. Conclusion: The checklist can be used more broadly in health care research, not just in ODCs. Ease of online publication as well as encouragement from journals to submit supplementary material are likely to increase both the volume and detail of analysis results publicly available, which in turn will increase the need for approaches such as the one suggested in this paper.