aceDynamic Pressure Ulcer Risk Predictions for Hospitalized Patients: Development and Validation of a Machine Learning Model With Nurses
Aim To develop and validate a dynamic prediction model for daily pressure ulcer risk predictions together with an expert group of nurses. Design Diagnostic study. Methods All admissions to general wards in a single-center tertiary university hospital in the Netherlands were included. A retrospective dataset with candidate predictors was collected from the electronic health records and split into a training set (December 2021-November 2022, N = 19,931) and a validation set (January 2023-June 2023, N = 11,387). Th…
A nurse-co-designed machine learning model for daily pressure ulcer risk discriminated better than the Waterlow score on a held-out validation set of general ward admissions at one Dutch hospital.
The model was developed and validated using retrospective data from general wards at one center, so performance elsewhere and its effect on patient outcomes are not established in this study.
Evidence
- Peer-reviewedJournal of Clinical Nursing2026-10-07
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Truvace Impact Record TRV-2026-1776, v1: “Dynamic Pressure Ulcer Risk Predictions for Hospitalized Patients: Development and Validation of a Machine Learning Model With Nurses.” Truvace, 2026-10-18. /record/TRV-2026-1776 (accessed at citation time). sha256 9b540fc5ec9196b2…
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