A review on simulation models applied to emergency medical service operations

Aboueljinane, Lina; Şahin, Evren; Jemaı̈, Zied

doi:10.1016/j.cie.2013.09.017

Cited by 155 publications

(94 citation statements)

References 76 publications

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“…Consequently, most of what is known about the factors affecting response time performance in EMS systems has been obtained through simulation modelling. [13] Our simulation, based on part of a large urban SA EMS system, was designed to investigate the theory that response time performance in high-acuity incidents can be improved merely by increasing a single resource -emergency vehicles -while leaving the rest of the system in its original state.…”

Section: Discussionmentioning

confidence: 99%

Meeting national response time targets for priority 1 incidents in an urban emergency medical services system in South Africa: More ambulances won’t help

2015

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Background. Response time is viewed as a key performance indicator in most emergency medical services (EMS) systems. Objective. To determine the effect of increased emergency vehicle numbers on response time performance for priority 1 incidents in an urban EMS system in Cape Town, South Africa, using discrete-event computer simulation. Method. A simulation model was created, based on input data from part of the EMS operations. Two different versions of the model were used, one with primary response vehicles and ambulances and one with only ambulances. In both cases the models were run in seven different scenarios. The first scenario used the actual number of emergency vehicles in the real system, and in each subsequent scenario vehicle numbers were increased by adding the baseline number to the cumulative total. Results. The model using only ambulances had shorter response times and a greater number of responses meeting national response time targets than models using primary response vehicles and ambulances. In both cases an improvement in response times and the number of responses meeting national response time targets was observed with the first incremental addition of vehicles. After this the improvements rapidly diminished and eventually became negligible with each successive increase in vehicle numbers. The national response time target for urban areas was never met, even with a seven-fold increase in vehicle numbers. Conclusion. The addition of emergency vehicles to an urban EMS system improves response times in priority 1 incidents, but alone is not capable of the magnitude of response time improvement needed to meet the national response time targets.

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Section: Discussionmentioning

confidence: 99%

Meeting national response time targets for priority 1 incidents in an urban emergency medical services system in South Africa: More ambulances won’t help

2015

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“…They conclude that OR has enormous potential for the better management of emergency responses. In another review, Aboueljinane et al (2013) figure out that computer simulation models are utilized to improve the efficiency of emergency medical services, a prevalent server-to-customer system. They classify studies in accordance with the main steps of a model such as inputs, formulation, model architecture and outputs.…”

Section: Related Workmentioning

confidence: 99%

An ILP and simulation model to optimize search and rescue helicopter operations

Karataş

Razi

Günal

2017

Journal of the Operational Research Society

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Maritime search and rescue (SAR) operations, conducted for rendering aid to the victims in need of help at sea, play a crucial role in dropping the number of causalities. Therefore, it is of high importance to organize SAR operations properly. In this paper, we compose a hybrid methodology which combines optimization and simulation to allocate SAR helicopters. First, we build an integer linear programming (ILP) model to provide an effective deployment plan and use it as an input to a simulation model which includes constraints that the ILP model cannot tackle. Next, using a rule-based algorithm, we generate alternative solutions and seek better plans that exist in the vicinity of the ILP model solution. We perform our methodology on the historical incident data in the Aegean Sea region. Results show that the hybrid methodology we adopted leads to a more effective utilization of resources than the optimization model alone.

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“…For the hospital selection problem, a widely used rule consists of selecting the closest hospital to the demand points (Su and Shih [17]; Aboueljinane et al [18]). However, Ingolfsson et al [19] mentioned that the proximity could not be the only influencing factor as in Edmonton EMS, as 50% of patients are not transported to the closest hospitals.…”

Section: Hospital Selectionmentioning

confidence: 99%

“…Constraints (18) ensures that the travel time or distance between demand site and the hospital ℎ should not exceed 3 minutes.…”

Section: The Formulation Of the Problemmentioning

confidence: 99%

Optimization for the Locations of Ambulances under Two‐Stage Life Rescue in the Emergency Medical Service: A Case Study in Shanghai, China

Liu

Yang

Hao

2017

Mathematical Problems in Engineering

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With the development of society, public resources for healthcare are increasingly inadequate to meet the demands for the services. Therefore, it is extremely important for policymakers to provide citizens with the most effective healthcare services within the limited available resources. In order to achieve positive effect rescue operations in the Emergency Medical Services (EMS) system, the problems including where to locate the ambulance facilities and how many ambulance vehicles should be allocated to the stations have become the focus of attention. In this paper, we study the problem based on the demand for EMS in Songjiang District, Shanghai, China, followed by the joint planning of Emergency Medical Services management, which typically consists of ambulance facility locations planning and patient's assignment to hospitals. We proposed a modified Double Standard Model (DSM) to maximize the demand points covered at least two times within the minimum coverage criteria. The problem is solved by integer linear programming technique with the CPLEX software and we make a comparison between the solutions and the locations which exist in the emergency system used by the Songjiang emergency center. Our results show that the demand coverage rate and response time can be efficiently improved through relocating the current facilities without additional vehicle resources.

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A review on simulation models applied to emergency medical service operations

Cited by 155 publications

References 76 publications

Meeting national response time targets for priority 1 incidents in an urban emergency medical services system in South Africa: More ambulances won’t help

Meeting national response time targets for priority 1 incidents in an urban emergency medical services system in South Africa: More ambulances won’t help

An ILP and simulation model to optimize search and rescue helicopter operations

Optimization for the Locations of Ambulances under Two‐Stage Life Rescue in the Emergency Medical Service: A Case Study in Shanghai, China

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