Application of the Risk Stratification Index to Multilevel Models of All-condition 30-Day Mortality in Hospitalized Populations Over the Age of 65

BACKGROUND: The Risk Stratification Index (RSI) is superior to Hierarchical Conditions Categories (HCC) in patient-level regressions but has not been applied to assess hospital effects. OBJECTIVE: The objective of this study was to measure the accuracy of RSI in modeling 30-day hospital mortality across all conditions using multilevel logistic regression. SUBJECTS AND DATA SOURCES: A 100% sample of Medicare inpatient stays from 2009 to 2014, restricted to patients greater than 65 years of age in general hospitals, resulting in 64 million stays at 3504 hospitals. RESEARCH DESIGN: We calculated RSI and HCC scores for patient stays using multilevel logistic regression in 3 populations: all inpatients, surgical, and nonsurgical. Correlations of risk-standardized mortality rates with rates of specific case types assessed case-mix balance. Patient stay volume was included to assess smaller hospitals. RESULTS: We found a negligible correlation of all-conditions risk-standardized mortality rates with hospitals’ proportions of orthopedic, cardiac, or pneumonia cases. RSI outperformed HCC in multilevel regressions containing both patient and hospital-level effects. C-statistics using RSI were 0.87 for the all-inpatients group, 0.87 for surgical, and 0.86 for nonsurgical stays. With HCC they were 0.82, 0.82, and 0.81. Akaike Information Criteria and Bayesian Information Criteria values were higher with HCC. RSI shifted 41% of hospitals’ rankings by >1 decile. Hospitals with smaller volumes had higher 30-day observed and standardized mortality: 11.2% in the lowest volume quintile versus 8.5% in the highest volume quintile. CONCLUSION: RSI has superior accuracy and results in a significant shift in rankings compared with HCC in multilevel models of 30-day hospital mortality across all conditions.