aceAdaptation of a fair individualized polysocial risk score for hospitalization risk prediction
Objectives We adapted the individualized polysocial risk score (iPsRS), a machine learning model originally developed for patients with type 2 diabetes, to evaluate its generalizability in predicting 1-year hospitalization risk in a disease-agnostic adult cohort, with attention to fairness and explainability. Materials and methods The study utilized de-identified electronic health record data from a retrospective cohort of 17 857 adult patients at the University of Florida Health. The original iPsRS framework wa…
Adapted iPsRS model using 13 individual-level SDoH predictors predicted 1-year all-cause hospitalization in a general adult cohort with AUROC up to 0.671, enabling equity-aware risk stratification for clinical care.
Model achieved only moderate predictive performance with AUROC up to 0.671, limiting clinical discrimination, and was evaluated in a single health system retrospective cohort.
Evidence
- Peer-reviewedJAMIA Open2026-08-24
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Truvace Impact Record TRV-2026-0897, v1: “Adaptation of a fair individualized polysocial risk score for hospitalization risk prediction.” Truvace, 2026-08-26. /record/TRV-2026-0897 (accessed at citation time). sha256 0070a3772adb05d8…
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