Readmission Risk Trajectories for Patients With Heart Failure Using a Dynamic Prediction Approach: Retrospective Study.

ABSTRACT: BACKGROUND:Patients hospitalized with heart failure suffer the highest rates of 30-day readmission among other clinically defined patient populations in the United States. Investigation into the predictability of 30-day readmissions can lead to clinical decision support tools and targeted interventions that can help care providers to improve individual patient care and reduce readmission risk. OBJECTIVE:This study aimed to develop a dynamic readmission risk prediction model that yields daily predictions for patients hospitalized with heart failure toward identifying risk trajectories over time and identifying clinical predictors associated with different patterns in readmission risk trajectories. METHODS:A two-stage predictive modeling approach combining logistic and beta regression was ap

SUBMITTER: Jiang W 

PROVIDER: S-EPMC6781727 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature