Application of a Medicare claims-based model predicting left ventricular ejection fraction subtype to investigate the epidemiology of heart failure in the US Medicare program

Abstract Introduction Administrative claims do not contain ejection fraction (EF) information for heart failure (HF) patients. To address this limitation, we recently developed a claims-based model to classify HF patients into reduced EF (rEF) or preserved EF (pEF) using 35 predictors. Purpose To report distribution of key patient characteristics and rates of HF decompensation and mortality in model-identified rEF and pEF patients from nationwide Medicare claims (2012–2016) and compare with estimates from the literature. Methods We identified HF patients ≥65 years from US Medicare claims using recorded diagnosis after ≥6 months of continuous enrollment. The date of HF diagnosis was the cohort entry date. The 6-month baseline period prior to the cohort entry date was used to identify predictors and apply the claims-based model to distinguish rEF and pEF. Patients were followed for the composite outcome of time to first HF decompensation (HF hospitalization or outpatient IV diuretic treatment) or all-cause mortality. Descriptive statistics were used to summarize baseline patient characteristics. Cumulative incidence estimates along with 95% confidence intervals (CI) were calculated for the composite endpoint as well as all-cause and cause-specific mortality (derived from National Death Index linkage) using the Kaplan-Meier method. Results A total of 3,134,414 HF patients with an average age of 79 years were identified, of which 200,950 (6.4%) were classified as rEF. Among those classified as rEF, men comprised a larger proportion (68% vs 41%), the average age was lower (76 vs 79 years), and history of myocardial infarction was more frequent (32% vs 13%) compared to pEF. One-year cumulative incidence (95% CI) of the composite endpoint was 42.6% (42.4–42.8%) for rEF and 36.9% (36.7–37.0%) for pEF. One-year all-cause mortality incidence was similar between the groups (27.4% [27.2–27.6%] for rEF and 26.4% [26.3–26.4%] for pEF), however, cardiovascular mortality was higher for rEF (16.7% [16.5–16.8%] vs 12.3% [12.2–12.3%]), whereas non-cardiovascular mortality was higher for pEF (12.9% [12.7–13.1%] vs 16.0% (16.0–16.1%) (Figure 1). These results were in line with estimates from other well-established cardiovascular cohorts including the Get With The Guidelines-HF cohort and the Olmstead County HF epidemiology cohort. Conclusion We replicated well-documented differences in key patient characteristics and endpoints between rEF and pEF in these populations identified based on application of a claims-based model. Our results support use of this model for identifying cohorts of rEF and pEF to conduct subtype specific investigations of treatment outcomes. However, a notably lower proportion of patients were identified as having rEF compared to previous reports indicating low sensitivity of this approach for rEF and suggesting that model-based classification may not be useful in tracking subtype specific incidence or prevalence of HF using Medicare claims. Cumulative incidence of outcomes in HF Funding Acknowledgement Type of funding source: Private grant(s) and/or Sponsorship. Main funding source(s): Novartis Inc.