Address correspondence to Siran M. Koroukian, Ph.D., Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, WG-49, Cleveland, OH 44106-4945; e-mail: email@example.com. Bassam Dahman, Ph.D., and Cathy J. Bradley, Ph.D., are with the Department of Public Health Management and Policy, School of Medicine, Virginia Commonwealth University, Richmond, VA. Glenn Copeland, M.B.A., is with the Michigan Cancer Surveillance Program, Vital Records and Health Data Development Section, Lansing, MI. Cathy J. Bradley, Ph.D., is also with the Cancer Prevention and Control, Massey Cancer Center, Richmond, VA.
The Utility of the State Buy-In Variable in the Medicare Denominator File to Identify Dually Eligible Medicare-Medicaid Beneficiaries: A Validation Study
Article first published online: 15 OCT 2009
© Health Research and Educational Trust
Health Services Research
Volume 45, Issue 1, pages 265–282, February 2010
How to Cite
Koroukian, S. M., Dahman, B., Copeland, G. and Bradley, C. J. (2010), The Utility of the State Buy-In Variable in the Medicare Denominator File to Identify Dually Eligible Medicare-Medicaid Beneficiaries: A Validation Study. Health Services Research, 45: 265–282. doi: 10.1111/j.1475-6773.2009.01051.x
- Issue published online: 8 JAN 2010
- Article first published online: 15 OCT 2009
- Dual Medicare-Medicaid beneficiaries;
- state buy-in;
- positive predictive value
Objective. To compare the adequacy of the state buy-in variable (SBI) in the Medicare denominator file to identify dually eligible patients.
Data Source/Study Settings. We used linked Medicare and Medicaid data from Michigan and Ohio for elders diagnosed with incident breast, prostate, or colorectal cancer between 1996 and 2001.
Study Design. Using the Medicaid enrollment file as the “gold standard,” we assessed the number of duals from Medicare files in cross-sectional and longitudinal analyses.
Data Collection/Extraction Methods. Data for the study population were linked with Medicare and Medicaid files using patient identifiers.
Principal Findings. Sensitivity was low (74.2 percent, 95 percent confidence interval [CI]: 72.7, 75.6 and 80.8 percent, 79.7, 81.9, in Michigan and Ohio, respectively). PPV was above 95 percent in Michigan and 88.8 percent in Ohio. Both sensitivity and PPV varied between and within the states. Both in Michigan and in Ohio, we observed limited agreement on the length of enrollment in Medicaid between the two data sources.
Conclusions. Except to examine disparities by dual status at a very broad level, the SBI variable alone may be inadequate to identify duals. The findings call for improvements in Medicare and Medicaid information management systems and for uniformity in database linking strategies.