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American Journal of Epidemiology Advance Access originally published online on December 20, 2006
American Journal of Epidemiology 2007 165(5):597-601; doi:10.1093/aje/kwk049
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American Journal of Epidemiology Copyright © 2006 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

PRACTICE OF EPIDEMIOLOGY

Method to Assess Identifiability in Electronic Data Files

Holly L. Howe1, Andrew J. Lake2 and Tiefu Shen3

1 North American Association of Central Cancer Registries, Inc., Springfield, IL
2 Information Management Services, Inc., Silver Spring, MD
3 Illinois State Cancer Registry, Springfield, IL

Reprint requests to Dr. Holly L. Howe, 2121 West White Oaks Drive, Springfield, IL 62704-6495 (e-mail: hhowe{at}naaccr.org).

Received for publication December 19, 2005. Accepted for publication July 28, 2006.

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.

confidentiality; medical informatics; neoplasms; privacy; regression analysis; social class

Abbreviations: NAACCR, North American Association of Central Cancer Registries; RU, Record Uniqueness; SEER, Surveillance, Epidemiology, and End Results


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