The Vehicle Mix Decision in Emergency Medical Service Systems

Kenneth C. Chong (), Shane G. Henderson () and Mark E. Lewis ()
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Kenneth C. Chong: School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
Shane G. Henderson: School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
Mark E. Lewis: School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853

Manufacturing & Service Operations Management, 2016, vol. 18, issue 3, 347-360

Abstract: We consider the problem of selecting the number of advanced life support (ALS) and basic life support (BLS) ambulances—the vehicle mix —to deploy in an emergency medical service (EMS) system, given a budget constraint. ALS ambulances can treat a wider range of emergencies, whereas BLS ambulances are less expensive to operate. To this end, we develop a framework under which the performance of a system operating under a given vehicle mix can be evaluated. Because the choice of vehicle mix affects how ambulances are dispatched to incoming calls, as well as how they are deployed to base locations, we adopt an optimization-based approach. We construct two models—one a Markov decision process, the other an integer program—to study the problems of dispatching and deployment in a tiered system, respectively. In each case, the objective function value attained by an optimal decision serves as our performance measure. Numerical experiments performed with both models suggest that, under reasonable choices of inputs, a wide range of tiered systems perform comparably to all-ALS fleets.

Keywords: ambulance dispatching; ambulance deployment; Markov decision processes; queues; integer programming; advanced life support; basic life support (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (6)

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