 Avoiding Disclosure of Individually Identifiable Health InformationSergio Prada, Claudia González-MartÃnez, Joshua Borton, Johannes Fernandes-Huessy, Craig Holden, Elizabeth Hair and and Tim Mulcahy SAGE Open, 2011, vol. 1, issue 3, 2158244011431279 Abstract: Achieving data and information dissemination without harming anyone is a central task of any entity in charge of collecting data. In this article, the authors examine the literature on data and statistical confidentiality. Rather than comparing the theoretical properties of specific methods, they emphasize the main themes that emerge from the ongoing discussion among scientists regarding how best to achieve the appropriate balance between data protection, data utility, and data dissemination. They cover the literature on de-identification and reidentification methods with emphasis on health care data. The authors also discuss the benefits and limitations for the most common access methods. Although there is abundant theoretical and empirical research, their review reveals lack of consensus on fundamental questions for empirical practice: How to assess disclosure risk, how to choose among disclosure methods, how to assess reidentification risk, and how to measure utility loss. Keywords: public use files; disclosure avoidance; reidentification; de-identification; data utility (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:1:y:2011:i:3:p:2158244011431279 Access Statistics for this article More articles in SAGE Open |
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