Re-Identification Risk of De-Identified Data Sets in the Era of Big Data

Sunday, 16 February 2014: 1:30 PM-4:30 PM
Regency C (Hyatt Regency Chicago)
Federal statistical agencies and their contractors often collect data from individuals or other entities under a pledge of confidentiality.  Dissemination of these results in the form of public microdata files can facilitate advances in research, inform public policy, and further citizens’ knowledge. As the demand for access to publicly available microdata files increases, there are growing concerns regarding the confidentiality of the collected information. Federal agencies are ethically and legally obligated to protect the confidentiality of subjects’ identities and failure to do so can break promises and violate laws. Ideally, publicly available microdata should be released in a way that balances the usefulness of the data and the privacy of the subjects. Numerous statistical methods to assess re-identification risk have been proposed in the literature, and it is important that U.S. federal government agencies such as the National Institutes of Health and Veterans Affairs invest in gaining a comprehensive understanding of these methods for the purpose of creating a guidance or checklist of recommended procedures. This session will provide guidance regarding methods that have been used or could be applied to protect health data that is already de-identified according to the Safe Harbor method. Speakers will provide descriptions and information on techniques that have been applied in practice and are interpretable by the general community.
Leslie Taylor, VA Puget Sound Health Care System
Xiao Hua Andrew Zhou, University of Washington
LaTanya Sweeney, Harvard University
De-Identifying Health Data
Bradley Malin, Vanderbilt University
De-Identified Medical Data and HIPAA
Eran Halperin, Tel Aviv University and University of California, Berkeley
Protecting Privacy in Clinical Genomics Databases
Daniel Barth-Jones, Columbia University
Re-Identification Risk: Perception Versus Reality
Xiao Hua Andrew Zhou, University of Washington
Statistical Methods for Re-Identification
Paul Ohm, University of Colorado
Issues in Privacy Regulation, Law and Society