© 2002 by the American Diabetes Association, Inc.
Attributing Inpatient Medicare Costs to Diabetes Among the Texas ElderlyFrom the School of Public Health, the University of Texas-Houston Health Science Center, Houston, Texas OBJECTIVEThis study compares alternative methods for attributing hospital utilization and costs to diabetes. Findings from five "numerator" methods, found in the literature and based on presence of certain diagnoses or combinations of diagnoses in the billing records, were compared to benchmark findings derived from attributable risk calculations. RESEARCH DESIGN AND METHODSEstimates of non-HMO, short-term, nonspecialized hospital stays, hospital days, and costs attributable to diabetes in Texas were derived from the 1995 Medicare inpatient database (MEDPAR) for persons aged at least 65 years at the end of 1994. Attributable risk calculations applied age-, sex-, and ethnicity-specific estimates of diabetes prevalence, based on the combined 19871994 National Health Interview Surveys, to 1995 Medicare non-HMO, Part A (hospital insurance) enrollment among the Texas elderly. Alternative prevalence estimates were based on the 19941996 Texas Behavioral Risk Factor Surveillance System. RESULTSThe five numerator methods yielded cost estimates that were 10, 10, 75, 144, and 172% of the benchmark estimate. CONCLUSIONSThis study documents great variation in diabetes cost estimates that might result from alternative methods for selecting diagnoses or combinations of diagnoses as criteria for attributing costs to diabetes. Whereas no method that ignores population prevalence yielded an accurate cost estimate, I suggest that further empirical study may be helpful in selecting those combinations of diagnoses that might, on average, reasonably estimate diabetes costs in situations where population denominators are unavailable or prevalence is unknown.
Abbreviations: BRFSS, Behavioral Risk Factor Surveillance System DRG, diagnostic-related group ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification MEDPAR, Medicares inpatient billing database NHIS, National Health Interview Survey.
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