Modern Decision-Making Models for Enhancing Risk Management and Occupational Safety in Hospitals: A Critical Analytical Review.

Abstract

The study aims to critically analyze contemporary decision-making models and their role in strengthening risk management and occupational safety within hospitals. Employing a descriptive–analytical methodology, it synthesizes empirical and theoretical insights from recent studies addressing the integration of artificial intelligence, predictive analytics, and structured risk assessment frameworks in healthcare settings. The findings reveal that advanced decision-support systems significantly enhance incident prevention, staff awareness, and compliance with safety regulations. Moreover, the results underscore that hybrid models-combining AI-driven analytics with traditional managerial judgment-offer superior adaptability to complex hospital environments. The study recommends that healthcare administrators adopt integrative, technology-enabled decision-making frameworks to promote proactive safety culture and institutional resilience.