Emergency Medical Service Allocation in Response to Large Scale Events

In the event of a catastrophic or large scale event, demand for Emergency Medical Service (EMS) vehicles will almost certainly overwhelm the available supply. In such cases, it is necessary for cities to request aid (in the form of added capacity) from neighboring municipalities in order to bring the affected region back to its day-to-day levels of operation. In particular, we consider a region consisting of several cities, where each city is in charge of managing its own EMS vehicles. We propose that a centralized or statewide decision-maker coordinate the temporary transfer of resources (EMS vehicles) from cities in the unaffected region into the cities in the affected region. The control of each city’s EMS vehicles is modeled as a multi-server queueing system and classical results are used to estimate the number of vehicles available at each city. We then develop a deterministic resource allocation model to guide the allocation of available vehicles from the donor area into the affected one and a clearing system model to dynamically control the added resources. As the dimension of the problem is large, a heuristic we call the buddy system is proposed where cities are paired to form city groups. Within the city groups the clearing system model is solved by Markov decision processes. The performance of our heuristic is compared to several other reasonable heuristics via a detailed numerical study. Results show that the buddy system exhibits significant cost and time savings, and is generally robust to varying parameters.