Do Hierarchical Condition Category Model Scores Predict Hospitalization Risk in Newly Enrolled Medicare Advantage Participants as Well as Probability of Repeated Admission Scores

OBJECTIVES: To compare how well hierarchical condition categories (HCC) and probability of repeated admission (PRA) scores predict hospitalization. DESIGN: Longitudinal cohort study with 12-month follow-up. SETTING: A Medicare Advantage (MA) plan. PARTICIPANTS: Four thousand five hundred six newly enrolled beneficiaries. MEASUREMENT: HCC scores were identified from enrollment files. The PRA tool was administered by mail and telephone. Inpatient admissions were based on notifications. The Mann-Whitney test was used to compare HCC scores of PRA responders and nonresponders. The receiver operating characteristic curve provided the area under the curve (AUC) for each score. Admission risk in the top 5% of scores was evaluated using logistic regression. RESULTS: Within 60 days of enrollment, 45.1% of the 3,954 beneficiaries with HCC scores completed the PRA tool. HCC scores were lower for the 1,783 PRA respondents than the 2,171 nonrespondents (0.71 vs 0.81, P<.001). AUCs predicting hospitalization with regard to HCC and PRA were similar (0.638, 95% confidence interval (CI)=0.603–0.674; 0.654, 95% CI=0.618–0.690). Individuals identified in the top 5% of scores using both tools, using HCC alone, or using PRA alone had higher risk for hospitalization than those below the 95th percentile (odds ratio (OR)=8.5, 95% CI=3.7–19.4, OR=3.8, 95% CI=2.3–6.3, and OR=3.9, 95% CI=2.3–6.4, respectively). CONCLUSION: HCC scores provided to MA plans for risk adjustment of revenue can also be used to identify hospitalization risk. Additional studies are required to evaluate whether a hybrid approach incorporating administrative and self-reported models would further optimize risk stratification efforts.