Design and Application of a New Four-party Collaborative Management Model in the Intelligent Scheduling System for Operating Room

Abstract

This study targets issues in traditional manual operating room scheduling, including unbalanced resource use, low efficiency, poor inter-departmental communication, and ignored nursing staff personal needs. It developed an integrated surgical scheduling platform to achieve refined, intelligent operating room management while balancing medical quality and humanistic care. Built on the existing Hospital Information System (HIS) with Caché database and Vue + .Net B/S three-tier architecture, the platform integrates five core functions: standardized surgical application, intelligent scheduling, staff rostering, dynamic dispatching, and information collaboration. It combines multi-objective optimization algorithms and Answer Set Programming (ASP) for precise matching of personnel, procedures, time and demands. Comparative analysis was conducted between 66,300 manually scheduled surgeries in 2024 (observation group) and 79,000 surgeries under intelligent scheduling in 2025 (control group). Results showed significant improvements: elective surgery scheduling time reduced by 78.1%, operating room golden time utilization increased by 31.18%, nursing workload balance rose by 27%, nursing emotional exhaustion positive rate decreased by 23%, and nursing turnover reached 0, with enhanced patient experience and staff satisfaction (p < 0.05). The platform forms a four-party collaborative management system, realizing efficient resource allocation and providing replicable experience for intelligent operating room management in tertiary hospitals.