Patient stratification for risk of readmission due to heart failure by using nationwide administrative data.

ABSTRACT

BACKGROUND: Identifying patients with heart failure (HF) who are most at risk of readmission permits targeting adapted interventions. The use of administrative data enables regulators to support the implementation of such interventions. METHODS AND RESULTS: In a French nationwide cohort of patients aged 65 years or older, surviving an index hospitalization for HF in 2015 (N = 70,657), we studied HF readmission predictors available in administrative data, distinguishing HF severity from overall morbidity and taking into account the competing mortality risk, over a 1-year follow-up period. We also computed cumulative incidences and daily rates of HF readmission for patient groups defined according to HF severity and overall morbidity. Of the patients, 31.8% (n = 22,475) were readmitted at least once for HF, and 17.6% (n = 12,416) died without any readmission for HF. HF severity and overall morbidity were the strongest readmission predictors were the strongest readmission predictors (subdistribution hazard ratios 2.66 [95% CI 2.52-2.81] and 1.37 [1.30-1.45], respectively, when comparing extreme categories). Overall morbidity and age were more strongly associated with the rate of death without HF readmission (cause-specific hazard ratios). The difference in observed HF readmission between patient risk groups was approximately 40% (21.9%, n = 2144/9,786 vs 60.4%, n = 618/1023). CONCLUSIONS: Segmentation of HF patients into readmission risk groups is possible by using administrative data, and it enables the targeting of preventive interventions.