LEE- Endüstri Mühendisliği-Doktora
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Yazar "Öksüz, Mehmet Kürşat" ile LEE- Endüstri Mühendisliği-Doktora'a göz atma
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ÖgeEmergency medical system design for disaster response(Graduate School, 2020-08-28) Öksüz, Mehmet Kürşat ; Satoğlu, Şule Itır ; 507142120 ; Industrial Engineering ; Endüstri MühendisliğiDisasters are large-scale events that affect human life, both materially and spiritually. There are many precautions to be taken to mitigate the devastating effect of disasters. One of them is effectively planning of post-disaster emergency medical response system. Since the most important factor is saving human life, proper planning of medical centers, and transportation of casualties to these centers is crucial during the disaster response phase. Therefore, it is necessary to design the Emergency Medical System (EMS) before disasters. EMS consists of many components such as disaster areas, hospitals, Temporary Medical Centers (TMC), casualties, medical staff, ambulances, etc. The proper planning and design of EMS are crucial to respond casualties and serve them effectively. Therefore, location planning of TMCs or field hospitals, classification of injuries (triage), assignment and transportation of casualties, determining the needs of medical staff in the medical centers play a significant role in mitigating the devastating effect of mass casualty events like disasters or incidents. Humanitarian Logistics or Disaster Management activities consist of preparation, supply, transportation, location, allocation, network design, tracking, and storage. Humanitarian Logistics is a challenging process, and this process contains many uncertainties. The main uncertainties in are the time, location, severity of a disaster, and size of demand. The uncertainties and variability in the complex nature of disaster management require formulating problems as a stochastic programming model in general. Humanitarian Logistics (HL) can be divided into three main topics, which are facility location, inventory management, and network flows/design problems. In the HL literature, facility location studies are commonly divided into three categories. These are emergency medical center, relief supplies warehouse, and shelter site or collection point location problems. In large-scale emergency events such as earthquake, hurricane, flood, and tsunami, the capacity of hospitals is not enough for the treatment of the casualties. Therefore, TMCs are located at the suitable sites by considering existing hospitals to serve casualties for medical response. In the first part of this study, it is aimed to determine the location and number of TMCs in case of an earthquake by considering different factors. In the objective function, we considered the setup cost of TMCs and the transportation cost of casualties. In addition, locations and bed capacities of the existing hospitals, possibilities of damage to the hospitals and roads are taken into account. At the same time, a widely used triage system is applied to classify casualties according to their injured level. The distances between disaster areas and EMCs also considered to minimize response time. For this problem, a two-stage stochastic programming model was developed. The proposed model finds an optimal TMC location solution while minimizing the total setup cost of the TMCs and the total expected transportation cost of casualties. Besides, the model was reformulated by considering a single-type of casualty to show the effect of triage on the solution of the problem. Based on the different earthquake scenarios in JICA Report (2002), a real case study was conducted for the Kartal district of Istanbul. The results were presented, and a sensitivity analysis was performed for critical parameters. The medical staff planning of medical centers is vital as wells as the location planning of medical centers to provide services to all casualties assigned to these centers. Therefore, the medical staff capacity should be considered in addition to the patient's capacity when assigning casualties to the medical centers. Besides, assuming that all of the expected casualties occur immediately after the disaster causes ineffective and unrealistic usage of resources. There is also another fact that a casualty might not stay in the same health condition as time passes. For these reasons, a multi-objective dynamic stochastic model was proposed for the medical staff assignment, casualty allocation, and TMC location planning simultaneously. In the proposed model, it is aimed to minimize the expected values of the total number of unserved casualties, the distance between disaster areas and emergency medical centers, and the number of medical staff needed. The first 72 hours after the disaster was considered and divided into four periods to reflect the dynamic behaviour of such events. Thus, with the dynamic model, it is aimed to use the capacities of emergency medical centers more efficiently and realistically. The stochastic nature of casualties' health condition was also included the model as a Discrete-time Markov Chain. For the case study, Kartal district data used in the model-1 has been updated according to the recently published report of the Istanbul Metropolitan Municipality (IBB-KRDAE, 2020). AUGMECON2 method was applied to solve the multi-objective model, and the results were analysed. According to the results for the case study in the first model, the total patient capacity of existing hospitals and all recommended TMCs are not enough for the most probable earhtquake scenarios defined in JICA Report (2002). However, for the most optimistic scenario, setting up 53 out of 74 candidate TMCs after the disaster is suffcient to assign all casualties to the medical centers. Besides, the percentage of unassigned casualties is 14.9% for the most probable scenario and the average percentage of unassigned casualties over all scenarios is about 10%. In the second case study, where the injured estimates are taken from the most recent study (IBB-KRDAE, 2020), there is enough capacity to assign all casualties to the EMCs over all scenarios. The number of TMC that must be set up is 50 for the worst-case scenario and 21 for the base-scenario. The results and analysis for both models offers some managerial insights associated with the number of temporary medical centers needed, their locations, additional capacity requirements, required number of medical staff, and allocation of casualties. We hope that this study will give a new perspective about the pre- and post-disaster emergency medical system design and contribute to the Humanitarian Logistics literature.