Predictive Modeling Of 30-Day Readmission Of Heart Failure Patients Using Admit Labs, Early Clinical Tests, And History And Physical Exam For In-Hospital Modification Of Readmission Risk

Background: All 30-day readmission risk models created to date use hospital discharge data gathered at the end of a hospital’s direct patient impact. Since 30-day readmission penalties are charged to hospitals, predictive models should use data from the time of index admission. This study created risk scores for 30-day readmission from factors available at admission among heart failure (HF) patients. Methods: HF patients aged 65 years or older who were admitted as inpatients to Intermountain Healthcare hospitals from 2005-2012 and not discharged to hospice were studied. Data included 205 predictor variables gathered within 24 hours of index admission and the 30-day readmission outcome. Patients were randomly divided into derivation (70%) and validation (30%) groups. Logistic regression was used to build sex-specific predictive models for 30-day readmission, including all variables (full model), only clinical and H&P factors (clinical model), and only laboratory tests (lab model). Results: C-statistics for...