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Medicaid, Medicare, and the Michigan Tumor Registry: A Linkage StrategyVirginia Commonwealth University, Department of Health Administration and Massey Cancer Center, Grant House, Richmond, VA, cjbradley{at}vcu.edu
Department of Family Practice and Michigan State Univ. East Lansing
Department of Epidemiology Michigan State University, East Lansing
Roberts Research Associates, East Lansing, MI
Michigan Cancer Surveillance Program, Michigan Department of Community Health, Lansing
Department of Health Services Research and Policy, School of Public Health, University of Minnesota, Minneapolis The study of health outcomes and the reduction in health disparities is at the forefront of the nation's health care agenda. A theme in the disparities literature is the call for a data infrastructure that can track progress toward goals aimed at reducing differences in health outcomes. This article describes a strategy for linking Medicaid, Medicare, and Michigan Tumor Registry data for the purposes of studying disparities in cancer diagnosis, quality of care, and survival. The authors review their procedures for ensuring that a correct match between files occurred and offer guidance for merging and assessing the quality of these complex linked data sets. A cohort of 113,604 subjects (90%) from a population of 125,900 subjects was correctly linked from the Michigan Tumor Registry to Medicare and Medicaid files. Using probabilistic and deterministic methods, the prediction rate of the Medicaid match to the Michigan Tumor Registry was 93%. Approximately 13% of the subjects were dually eligible for Medicare and Medicaid. An expansive data set reflecting the Medicare and Medicaid medical service utilization and outcomes for a cohort of individuals age 65 years and older when diagnosed with cancer was created. This data set serves as a cornerstone of a health outcomes data infrastructure. The methodology described may serve as a model for other researchers seeking to create a similar data set in their state.
Key Words: Key words: cancer • Medicare • Medicaid • administrative data. (Med Decis Making 2007;27:352—363)
This version was published on August
1, 2007 Medical Decision Making, Vol. 27, No. 4,
352-363 (2007) This article has been cited by other articles:
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