Published online before print March 20, 2006, doi: 10.1161/CIRCULATIONAHA.105.611194
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(Circulation. 2006;113:1693-1701.)
© 2006 American Heart Association, Inc.
Health Services and Outcomes Research |
An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With Heart Failure
From the Section of Cardiovascular Medicine, Department of Medicine (H.M.K., Yongfei Wang), Section of Health Policy and Administration, Department of Epidemiology and Public Health (H.M.K.), and Robert Wood Johnson Clinical Scholars Program (H.M.K.), Yale University School of Medicine, New Haven, Conn; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Conn (H.M.K., Yun Wang, J.A.M.); Centers for Medicare & Medicaid Services, Baltimore, Md (L.F.H., M.J.I., S.R.); Department of Health Care Policy, Harvard Medical School, Boston, Mass (S.T.N.); and Department of Biostatistics, Harvard School of Public Health, Boston, Mass (S.T.N.).
Correspondence to Dr Harlan M. Krumholz, Yale University School of Medicine, Room I-456 SHM, 333 Cedar St, PO Box 208088, New Haven, CT 06520-8088. E-mail harlan.krumholz{at}yale.edu
Received December 28, 2005; revision received February 13, 2006; accepted February 16, 2006.
Background— A model using administrative claims data that is suitable for profiling hospital performance for heart failure would be useful in quality assessment and improvement efforts.
Methods and Results— We developed a hierarchical regression model using Medicare claims data from 1998 that produces hospital risk-standardized 30-day mortality rates. We validated the model by comparing state-level standardized estimates with state-level standardized estimates calculated from a medical record model. To determine the stability of the model over time, we used annual Medicare cohorts discharged in 1999–2001. The final model included 24 variables and had an area under the receiver operating characteristic curve of 0.70. In the derivation set from 1998, the 25th and 75th percentiles of the risk-standardized mortality rates across hospitals were 11.6% and 12.8%, respectively. The 95th percentile was 14.2%, and the 5th percentile was 10.5%. In the validation samples, the 5th and 95th percentiles of risk-standardized mortality rates across states were 9.9% and 13.9%, respectively. Correlation between risk-standardized state mortality rates from claims data and rates derived from medical record data was 0.95 (SE=0.015). The slope of the weighted regression line from the 2 data sources was 0.76 (SE=0.04) with intercept of 0.03 (SE=0.004). The median difference between the claims-based state risk-standardized estimates and the chart-based rates was <0.001 (25th percentile=–0.003; 75th percentile=0.002). The performance of the model was stable over time.
Conclusions— This administrative claims-based model produces estimates of risk-standardized state mortality that are very good surrogates for estimates derived from a medical record model.
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