Simulating rural Emergency Medical Services during mass casualty disasters - Sullivan, Kendra (Kansas State University, 2008)
Emergency Medical Systems (EMS) are designed to handle emergencies. Fortunately, most emergencies faced have only one patient. The every day system is not designed to respond to emergencies in which there are many casualties. Due to natural disasters and terrorist attacks that have occurred over the past decade, mass-casualty disaster response plans have become a priority for many organizations, including EMS. The resources available for constructing such plans are limited. Physical simulations or practices of the plan are often performed; however, it is not until a disaster strikes that the capabilities of the plan are truly realized. In this paper, it is proposed that discrete-event simulations are used as part of the planning process. A computer simulation can test the capability of the plan under different settings and help planners in their decision making. This paper looks at the creation of a discrete-event simulation using ARENA software. The simulation was found to accurately simulate the response to the Greensburg tornado that occurred May of 2008. A sensitivity analysis found that the simulation results are dependent upon the values assumed for Volunteer Injury Rate, Injury Level, Information Dissemination Rate and Transportation Decision variables. When a disaster occurs, the local resources are overwhelmed and outside aide must be called in. Decision rules for when to request more outside ambulances and when to release them to send them home are evaluated. The more resources that are made available, the quicker patients receive medical care. However, when outside ambulances are called in, they are putting their home area at risk because it no longer has complete (or any) ambulance coverage. As the percent of coverage decreases, the amount of time that victims spend waiting for ambulances also decreases. Many decision rules were evaluated, resulting in various combinations of ambulance wait times and average percent coverage. It is up to Disaster Planners to determine how much of an additional wait can be assumed by the disaster victims to prevent outside districts from taking on unwarranted risk of low coverage.
Keywords: Simulation; Disaster; Ambulance; EMS; Engineering, Industrial (0546); Health Sciences, Health Care Management (0769); Transportation (0709)