Optimization of Markov Queuing Model in Hospital Bed Resource Allocation

Abstract

Bed resources are the platform in which most medical and health resources in the hospital play a role and carry the core functions of the health service system. How to improve the efficiency of the use of bed resources through scientific management measures and methods and ultimately achieve the optimization of overall health resources is the focus of hospital management teams. This paper analyzes the previous research models of knowledge related to queuing theory in medical services. From the perspective of the hospital and the patient, several indicators such as the average total number of people, the utilization rate of bed resources, the patient stop rate, and the patient average waiting time are defined to measure the performance of the triage queue calling model, which makes the patient queue more reasonable. According to the actual task requirements of a hospital, a Markov queuing strategy based on Markov service is proposed. A mathematical queuing model is constructed, and the process of solving steady-state probability based on Markov theory is analyzed. Through the comparative analysis of simulation experiments, the advantages and disadvantages of the service Markov queuing model and the applicable scope are obtained. Based on the theory of the queuing method, a queuing network model of bed resource allocation is established in principle. Experimental results show that the queuing strategy of bed resource allocation based on Markov optimization effectively improves resource utilization and patient satisfaction and can well meet the individual needs of different patients. It does not only provide specific optimization measures for the object of empirical research but also provides a reference for the development of hospital bed resource allocation in theory.