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December 21, 2018

Preserving Patient Confidentiality as Data Grow: Implications of the Ability to Reidentify Physical Activity Data

Author Affiliations
  • 1Center for Quantitative Health, Massachusetts General Hospital, Boston
  • 2Department of Computer Science, Tufts University, Medford, Massachusetts
JAMA Netw Open. 2018;1(8):e186029. doi:10.1001/jamanetworkopen.2018.6029

Individual information has the potential to be individually identifying information. In their article, Na et al1 demonstrate the potential for activity data collected by commercially available smart watches, smartphones, and fitness trackers to contribute to probabilistic reidentification of research participants. Activity tracker data join a long list of previously reported data types that can be reidentified (eg, those described by Erlich and Narayanan2 and Sweeney3). Given this history, the results of Na et al are not surprising; however, these findings are important because they speak to a core value of medicine—confidentiality—in a context of growing relevance: waveform data of the sort used by Na and colleagues are becoming more common with the widespread availability of sensors to generate these data and the potential for remote monitoring reimbursement to speed their clinical adoption.4

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