A Markov decision optimization of medical service resources for two-class patient queues in emergency departments via particle swarm optimization algorithm.

ABSTRACT: In the modern healthcare system, the rational allocation of emergency department (ED) resources is crucial for enhancing emergency response efficiency, ensuring patient safety, and improving the quality of medical services. This paper focuses on the issue of ED resource allocation and designs a priority sorting system for ED patients. The system classifies patients into two queues: urgent and routine. Considering different service rates, a multi-server preemptive priority queueing model [Formula: see text] and a multi-server non-preemptive priority queueing model [Formula: see text] are constructed. Additionally, the number of beds, K, is introduced as the capacity of the urgent queue. By comprehensively considering the costs associated with patient waiting time, the cost of rejecting the

SUBMITTER: Wang CH 

PROVIDER: S-EPMC11758071 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature