Authors: Howe, Holly L.; Lake, Andrew J.; Shen, Tiefu

Source: American Journal of Epidemiology, Volume 165, Number 5, 1 March 2007 , pp. 597-601(5)

Publisher: Oxford University Press

Abstract:

The authors developed the Record Uniqueness (RU) software program to assess electronic data files for risk of confidentiality breach based on unique combinations of key variables. The underlying methodology utilized by the RU program generates a frequency distribution for every variable selected for analysis and for all combinations of the variables selected. In addition, the program provides the regression coefficient that designates the relative contribution of each variable to the unique records on the data file. The authors used RU to evaluate a North American Association of Central Cancer Registries research data set with 4.67 million cases from 34 population-based cancer registries for 1995-2001. To illustrate the process and utility of RU, they describe the evaluation process of the confidentiality risk of adding a county-based socioeconomic measure to the research file. The RU method enables one to be assured of record confidentiality, provides flexibility to adjust record uniqueness thresholds for different users or purposes of data release, and facilitates good stewardship of confidential data balanced with maximum use and release of information for research. RU is a useful data tool that can quantify the risk of confidentiality breach of electronic health databases, including reidentifiability of cases through triangulation of information or linkage with other electronic databases.

Document Type: Research article

DOI: http://dx.doi.org/10.1093/aje/kwk049

Publication date: 2007-03-01

More about this publication?

• The American Journal of Epidemiology is the premier epidemiological journal devoted to the publication of empirical research findings, methodological developments in the field of epidemiological research and opinion pieces. It is aimed at both fellow epidemiologists and those who use epidemiological data, including public health workers and clinicians.

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