Optimizing Smart Hospital Management with Cooperative Robots and Game-Theoretic Approaches

This study presents a framework to optimize smart hospital management by integrating cooperative robots and game-theoretic approaches, particularly the Kalai-Smorodinsky Bargaining Solution (KSBS). The objective is to streamline healthcare delivery, enhance patient outcomes, and improve resource utilization by automating repetitive tasks and supporting inter-departmental workflows. Six critical hospital departments such as emergency room (ER), Intensive Care Unit (ICU), surgery, radiology, finance, and administration are modeled as players in a cooperative game, where the cooperative robots are used to align their tasks and objectives efficiently. The KSBS is applied to ensure equitable and efficient decision-making, with five key performance metrics such as efficiency, resource utilization, cost reduction, innovation, and conflict resolution which are used to evaluate system performance. Compared to existing methods, the proposed framework achieves a 30.9% reduction in waiting time, a 16% decrease in average processing time, a 42.9% improvement in communication latency, and a 20% increase in throughput, highlighting its superiority in improving hospital workflows and task coordination. The solution aims to balance the negotiated outcomes, prioritizing fairness among departments while maximizing overall hospital performance. This approach fosters collaboration, mitigates conflicts, and enables sustainable, patient-centric outcomes in hospital management.