Machine-Learning Modeling to Predict Hospital Readmission Following Discharge to Post-Acute Care

Primary purpose was to generate a model to identify key factors relevant to acute care hospital readmission within 90 days from 3 types of post-acute care (PAC) sites: home with home care services (HC), skilled nursing facility (SNF), and inpatient rehabilitation facility (IRF). Specific aims were to (1) examine demographic characteristics of adults discharged to 3 types of PAC sites and (2) compare 90-day acute hospital readmission rate across PAC sites and risk levels.