A Study on the Effectiveness of Nursing Interventions in Reducing Hospital-Acquired Infections
Posted: May 09, 2023
Abstract
This comprehensive study investigates the efficacy of targeted nursing interventions in mitigating hospital-acquired infections (HAIs) through a novel computational framework that integrates machine learning with clinical workflow optimization. Unlike traditional approaches that focus primarily on medical protocols, our research introduces a data-driven methodology that analyzes nursing behavioral patterns, intervention timing, and resource allocation efficiency. WedevelopedaproprietaryalgorithmcalledtheNursingIntervention Optimization System (NIOS) that processes multi-dimensional clinical data including patient vital signs, nurse-patient interaction logs, environmental factors, and infection incidence records. The study was conducted across three major healthcare facilities over an 18-month period, encompassing 2,347 patients and 184 nursing staff members. Our findings reveal that optimized nursing intervention scheduling, when combined with real-time risk assessment, can reduce HAIs by 42.7
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