Research On Operation Optimization Of Urban Emergency Medical System Under Uncertain Environment

Emergency medical services play an important role in protecting the health of residents in large and medium-sized cities in China.The demand for emergency medical services is often unknown and full of high uncertainty,which makes the urban emergency medical service system face huge challenges in operation and management.Throughout the whole process of patients receiving emergency medical services,there is a contradiction between patients’ need and medical service supply in the procedures that the ambulances response to the patients and take them to the hospital,as well as the procedure that allocating the emergency beds to the coming patients.Therefore,the operation optimization of the urban emergency medical system is studied in this dissertation to help more rational and efficient use of emergency medical resources and improve the emergency medical system benefits.The optimization of the part of emergency medical system outside the hospital is studied at first.In the link of response and transporting the patients to the hospital,there are problems such as ambulance offload delay,patients’ over-waiting in emergency departments and the unreasonable number of emergency beds.Thus,the continuous time Markov chain method was used to model the system and the system average ambulance queue length is analytically represented.Besides,mathematical programming models are established and heuristic algorithms such as tabu search are designed to solve the problem.Then,the emergency bed management and scheduling optimization of the emergency department in the hospital is studied.The shortage of beds in the hospitalization procedure usually occurs when critically ill patients arrive at the hospital and finish their emergency treatment.In this regard,a continuous-time Markov decision model is established to describe the process of patient admission control.With some specific admission rule constraints,the linear programming algorithm is used to solve the decision process to obtain the optimal admission policy.Meanwhile,some kinds of threshold policies are put forward and the optimal thresholds are solved out based on policy evaluation method.In addition,according to the reality in the emergency department such as increasing bed temporarily and accepting patients transferred from other hospital,we modified the patient admission control model and shows that this model could be generalized to various complex emergency admission situations.Finally,numerical experiments show the comparison of actual control group and the optimized results obtained by the proposed models and methods,and verifies the effectiveness of the optimization to emergency medical system.