Abstract 3276: Assessment of Predictive Accuracy of Centers for Medicare and Medicaid Services’ Method to Risk Adjust Patients for Interhospital Comparison of 30-day Mortality Rates
Introduction: The Centers for Medicare and Medicaid Services (CMS) will initiate public reporting of 30 day death rates for hospitals caring for patients with heart failure (HF). While hospital specific rates will be adjusted for medical comorbidities, it is not known if this method is adequate to allow direct hospital comparisons.
Hypothesis: More accurate risk adjustment of patients can be accomplished by including variables that have previously been described to be predictors of mortality in HF.
Methods: We assessed the CMS HF risk adjustment model in a population of 3639 patients studied in the Guidelines Applied in Practice (GAP) - HF study. Probabilties for 30 day mortality were calculated for the CMS model. Multivariable logistic regression analysis was then performed with other models including variables (no mVO2) from the Heart Failure Survival Score (HFSS), ADHERE Registry model (ARM), body mass index categories (BMI), pre-admission origin of patient (PAO), and admission in the previous 6 months (AP6). Probabilities of mortality were tabulated. Backward selection was then used to derive the best model from all candidate variables from a derivation data subset, followed by testing of the model on a validation data subset. Area under the curve (AUC) was then compared for each model.
Results: The AUCs and 95% CI are shown in the table⇓ below. Calculated AUCs for the CMS model and separate models were similar. The best model was defined by the following variables: admission in the previous 6 months, BUN > 43, systolic blood pressure > 115, 35 ≤ BMI < 40, BMI ≥ 40, mean arterial pressure, serum sodium, and PAO as well as the CMS model variables. The AUCs for the derivation and validation sets were both significantly greater than that provided by the CMS model alone.
Conclusions: Risk adjustment for the purpose of interhospital comparison of 30-day mortality rates is best performed with models that include clinical admission variables in addition to the medical comorbidites.