Posted: Aug 02, 2021
This comprehensive study investigates the efficacy of evidence-based nursing interventions in preventing pressure ulcers within hospital settings, employing a novel computational framework that integrates machine learning with clinical decision support systems. Unlike traditional approaches that rely on retrospective analysis, our methodology introduces a predictive modeling system that anticipates pressure ulcer development risk in real-time, enabling proactive intervention. We developed and implemented a multi-faceted intervention protocol incorporating advanced sensor technology, automated risk assessment algorithms, and personalized care planning. The research was conducted across three major hospital systems over a 24-month period, involving 2,347 patients and 487 nursing staff members. Our results demonstrate a statistically significant 68
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