Laura McLay
Optimal Emergency Medical Service Dispatching Policies
Abstract
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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