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By: Sanjeev Kumar Vishwakarma and Peter Jasper Youtham.
1. PhD Scholar, Department of Nursing, Index Nursing College, Indore, Madhya Pradesh, India.
2. Professor & Research Guide, Department of Nursing, Index Nursing College, Indore, Madhya Pradesh, India.
Background: Intensive Care Units (ICUs) face challenges in effectively monitoring critically ill patients. Traditional monitoring methods may not detect subtle signs of deterioration in time, leading to worsened outcomes. Artificial Intelligence (AI)-driven monitoring systems have emerged as a potential solution, promising improved predictive capabilities and patient outcomes. Objective: This study aimed to evaluate the impact of AI-based monitoring systems on ICU patient outcomes, focusing on mortality rates, length of ICU stay (LOS), and predictive accuracy for conditions such as sepsis and respiratory failure. Methods: A prospective cohort study was conducted in an ICU, comparing AI-based monitoring with traditional ICU monitoring systems. The study included 300 ICU patients, with 150 in each group. Data on mortality, length of stay, and complications were collected. AI system performance was assessed using sensitivity, specificity, and Area Under the Curve (AUC) for predictive accuracy. Regression analysis was performed to evaluate the impact of AI on patient outcomes. Results: AI-based monitoring led to a significant reduction in mortality rates (18%) compared to traditional systems (26%) (p = 0.045). AI was also associated with a shorter ICU stay (12.5 days vs. 14.8 days, p = 0.021). The AI system demonstrated high predictive accuracy, with an AUC of 0.912 for mortality prediction. Conclusion: AI-based monitoring systems significantly improve ICU outcomes by reducing mortality and LOS. However, challenges regarding alert fatigue, ethical concerns, and system integration must be addressed to optimize AI’s use in critical care.
Keywords: Artificial Intelligence, ICU, Predictive Analytics, Mortality, Length of Stay, Early Warning Systems, Clinical Decision Support.
Citation:
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