Ontology highlight
ABSTRACT: Importance
Accurate identification of hospital readmission risk during a current hospitalization may enhance decision-making, facilitate targeted systems-level interventions, and avoid preventable readmissions.Objective
To temporally and externally validate a suite of readmission risk prediction models across 48 children's hospitals to assess their generalizability and feasibility for future clinical implementation.Design, setting, and participants
This prognostic study analyzed data from the Pediatric Health Information System (PHIS) database, which contains billing and resource use data from 48 US children's hospitals, including the derivation hospital (DH) and 47 hospitals participating in the PHIS database (hereafter other PHIS hospitals). Children aged 18 years
SUBMITTER: Carroll AR
PROVIDER: S-EPMC11826366 | biostudies-literature | 2025 Feb
REPOSITORIES: biostudies-literature