Predictors of 30-Day Readmission in Patients Hospitalized With Heart Failure as a Primary Versus Secondary Diagnosis

Abstract

Short-term rehospitalizations are common, costly, and detrimental to patients with heart failure (HF). Current research and policy have focused primarily on 30-day readmissions for patients with HF as a primary diagnosis at index hospitalization, whereas a much larger population of patients are admitted with HF as a secondary diagnosis. This study aims to compare patients initially hospitalized for HF as either a primary or a secondary diagnosis, and to identify the most important factors in predicting 30-day readmission. Patients admitted with HF between 2014 and 2016 in the Nationwide Readmissions Database were included and divided into 2 cohorts: those admitted with a primary and secondary diagnosis of HF. Multivariable logistic regression was performed to predict 30-day readmission. Statistically significant predictors in multivariable logistic regression were used for dominance analysis to rank these factors by relative importance. Co-morbidities were the major driver of increased risk of 30-day readmission in both groups. Individual Elixhauser co-morbidities and the Elixhauser co-morbidity indexes were significantly associated with an increase in 30-day readmission. The 5 most important predictors of 30-day readmission according to dominance analysis were age, Elixhauser co-morbidity indexes of co-morbidity complications and readmission, number of diagnoses, and renal failure. These 5 factors accounted for 68% of the 30-day readmission risk. Measures of patient co-morbidities were among the strongest predictors of readmission risk. This study highlights the importance of expanding predictive models to include a broader set of clinical measures to create better-performing models of readmission risk for HF patients.

Keywords: 30-day readmission; co-morbidity; heart failure; readmission predictor.