Leveraging Administrative Data for Program Evaluations: A Method for Linking Data Sets Without Unique Identifiers

Andrea L. Lorden, Tiffany A. Radcliff, Luohua Jiang, Scott A. Horel, Matthew L. Smith, Kate Lorig, Benjamin L. Howell, Nancy Whitelaw, Marcia G. Ory

Research output: Contribution to journalArticlepeer-review


In community-based wellness programs, Social Security Numbers (SSNs) are rarely collected to encourage participation and protect participant privacy. One measure of program effectiveness includes changes in health care utilization. For the 65 and over population, health care utilization is captured in Medicare administrative claims data. Therefore, methods as described in this article for linking participant information to administrative data are useful for program evaluations where unique identifiers such as SSN are not available. Following fuzzy matching methodologies, participant information from the National Study of the Chronic Disease Self-Management Program was linked to Medicare administrative data. Linking variables included participant name, date of birth, gender, address, and ZIP code. Seventy-eight percent of participants were linked to their Medicare claims data. Linking program participant information to Medicare administrative data where unique identifiers are not available provides researchers with the ability to leverage claims data to better understand program effects.

Original languageEnglish (US)
Pages (from-to)245-259
Number of pages15
JournalEvaluation and the Health Professions
Issue number2
StatePublished - Jun 2016


  • administrative data
  • fuzzy matching
  • linkage
  • Medicare
  • program evaluation

ASJC Scopus subject areas

  • Health Policy


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