The Indian military healthcare system is tasked with ensuring the physical and mental well-being of service members, veterans, and their dependents. Despite its extensive network of specialized facilities, the system faces persistent challenges in managing patient flow, particularly in the Outpatient Departments (OPD). Current queuing methods, predominantly first-come, first-served and token-based systems, fail to address the complexities of patient prioritization, real-time doctor efficiency, and dynamic workload balancing, resulting in prolonged waiting times and inefficiencies.This research introduces a novel dynamic queuing algorithm designed to optimize patient flow in military OPDs. The algorithm combines Weighted Round Robin (WRR) for priority-based assignment, a Tribonacci-based aging mechanism to dynamically elevate patient priority with waiting time, and real-time load balancing to ensure equitable resource utilization. The study evaluates the algorithm’s performance through a simulation with heterogeneous doctor efficiency and diverse patient priorities. Results demonstrate significant reductions in patient waiting times and improved workload distribution among medical personnel, showcasing the algorithm’s potential to enhance operational efficiency and patient satisfaction in military healthcare facilities.By addressing limitations in traditional systems and leveraging a multi-dimensional optimization approach, this study contributes a scalable, adaptive framework for efficient queuing in high-demand healthcare environments. This innovation not only supports the operational objectives of military hospitals but also sets a precedent for broader applications in complex healthcare systems.

The Indian military healthcare system plays a crucial role in safeguarding the health and well-being of those who serve in the military, including active personnel, retired veterans, and their dependents. This extensive network of hospitals and medical facilities spans across all branches of the armed forces—Army, Navy, and Air Force—providing specialized medical care. Despite its broad reach, the system faces challenges, particularly within Outpatient Departments (OPDs), which handle a substantial volume of daily visits. This workload tends to spike during health crises, such as pandemics. Managing patient flow effectively remains a persistent challenge for military hospitals. Traditional queuing strategies, such as the first-come, first-served and token-based systems, fall short of handling the complexity of patient prioritization, doctor efficiency, and real-time workload adjustments. These methods often lead to inefficiencies like extended waiting periods, uneven workload distribution among medical personnel, and suboptimal resource use. The manual system’s inability to adapt to changing patient demands and the urgency of medical needs further exacerbates these issues. There is an urgent need for improved queue management solutions in military hospital OPDs. A dynamic queuing algorithm that can adapt to real-time data—such as patient arrivals, doctor availability, and consultation times—could significantly enhance patient flow, reduce waiting times, and improve overall system efficiency. By implementing a flexible queuing approach, military hospitals can better address the needs of their beneficiaries, thereby enhancing both operational outcomes and patient satisfaction.