International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Impact of AI-Powered Early Warning Scoring Systems on Nursing Interventions in Critical Care Units

Author(s) Ms. Nisha Singh, Ms. Nazima Thomas, Ms. Kangujam Sonalika Devi
Country India
Abstract Background: Critical care nursing requires rapid and accurate patient status assessment. This study investigates the efficacy of an AI-powered early warning scoring system in enhancing nursing interventions and patient outcomes.
Objective: To quantitatively evaluate the impact of AI-driven predictive analytics on patient deterioration detection, nursing response times, and clinical outcomes in critical care units.
Methods: A quasi-experimental comparative study was conducted with 300 adult patients (150 in control and 150 in AI-enhanced groups). The study measured intervention times, mortality rates, and length of stay using advanced statistical analyses.
Results: The AI-enhanced group demonstrated statistically significant improvements in early patient status detection (p < 0.001), reduced intervention times (mean difference 22.5 minutes, 95% CI 18.3-26.7), and lower mortality rates (8.6% vs. 14.2% in control group).
Conclusion: AI-powered early warning scoring systems show substantial promise in improving critical care nursing practices, offering more precise and timelier patient monitoring and intervention strategies.
Keywords Keywords: Artificial Intelligence, Critical Care Nursing, Early Warning Scoring, Patient Monitoring, Healthcare Technology
Field Medical / Pharmacy
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-05-16
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.44877
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E-ISSN 2582-2160
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