Attributing Inpatient Medicare Costs to Diabetes Among the Texas Elderly
- Roy R. McCandless, DRPH
- From the School of Public Health, the University of Texas-Houston Health Science Center, Houston, Texas
Abstract
OBJECTIVE—This 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 METHODS—Estimates 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 1987–1994 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 1994–1996 Texas Behavioral Risk Factor Surveillance System.
RESULTS—The five numerator methods yielded cost estimates that were 10, 10, 75, 144, and 172% of the benchmark estimate.
CONCLUSIONS—This 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.
- BRFSS, Behavioral Risk Factor Surveillance System
- DRG, diagnostic-related group
- ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification
- MEDPAR, Medicare’s inpatient billing database
- NHIS, National Health Interview Survey.
Footnotes
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Address correspondence and reprint requests to Roy R. McCandless, DrPH, Department of Family and Community Medicine, University of California, San Francisco, 3333 California St., Suite 365, San Francisco, CA 94118. E-mail: roymcc{at}itsa.ucsf.edu.
Received for publication 27 February 2002 and accepted in revised form 29 July 2002.
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