Laura McLay
Optimal Emergency Medical Service Dispatching Policies

The goal of emergency medical service (EMS) systems is to save lives. Dispatching ambulances to emergency medical 911 calls has the potential to save lives through dynamic resource allocation. This paper provides an optimal dispatching methodology for server-to-customer systems using Markov decision processes. It is assumed that customers arrive sequentially, with the priority of each customer becoming known upon arrival, with classification errors in these customer priorities. The proposed model determines how to optimally dispatch servers to customers to maximize the average utility in an undiscounted, infinite horizon Markov decision process. The utilities and transition probabilities are location-dependent, with respect to both the server and customer locations. The analysis considers two cases for approaching the classification errors that correspond to over- and under-responding to perceived customer priority. A computational example is applied to an EMS system in order to determine the optimal policy for dispatching ambulances to patients in order to maximize patient survival.

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