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

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...

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Bibliographic Details
Published in:Evaluation & the health professions 2016-06, Vol.39 (2), p.245-259
Main Authors: Lorden, Andrea L., Radcliff, Tiffany A., Jiang, Luohua, Horel, Scott A., Smith, Matthew L., Lorig, Kate, Howell, Benjamin L., Whitelaw, Nancy, Ory, Marcia
Format: Article
Language:English
Subjects:
Age Factors
Aged
Aged, 80 and over
Childbirth & labor
Chronic Disease - therapy
Chronic illnesses
Data analysis
Data collection
Data Collection - methods
Demographics
Evaluation research
Female
Fuzzy
Fuzzy Logic
Health administration
Health promotion
Health Services - utilization
Health technology assessment
Help seeking behavior
Humans
Insurance Claim Review
Leverage
Longitudinal Studies
Male
Medicare
Medicare - statistics & numerical data
Patient Compliance
Patient Education as Topic - methods
Privacy
Program Evaluation - methods
Research Design
Self-Management - methods
Selfmanagement
Sex Factors
Social security
United States
Wellness programs
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Summary: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.
ISSN:0163-2787
1552-3918
DOI:10.1177/0163278714547568