DEVELOPING AND VALIDATING EHR-INTEGRATED READMISSION RISK PREDICTION MODELS FOR HOSPITALIZED PATIENTS WITH DIABETES (eDERRI)
Purpose/Goal(s): Hospital readmission is an undesirable, costly outcome for both patients and hospitals that is often preventable. Patients with diabetes are at higher risk of readmission within 30 days of hospital discharge than patients without diabetes.
This project aims to develop new versions of the DERRI model enhanced by EHR (Electronic Health Records) data (eDERRI) that predict unplanned 30-day all-cause hospital readmission risk among patients with diabetes.
Using data from all PaTH sites the aims are:
and will build an automated, EHR-integrated eDERRI tool that automatically captures EHR data to predict readmission risk
Study Design: Data on the study population will be drawn from PaTH. Through the PaTH infrastructure, data will be collected from more than 40 academic, community, and specialty hospitals. Subjects will be identified using data in the PaTH Common Data Model and will not be contacted directly.
Sponsor: National Institute of Health