Abstract

Ambulance diversion (AD) is used by emergency departments (EDs) to relieve congestion by requesting ambulances to bypass the ED and transport patients to another facility. We study optimal AD control policies using a Markov Decision Process (MDP) formulation that minimizes the average time that patients wait beyond their recommended safety time threshold. The model assumes that patients can be treated in one of two treatment areas and that the distribution of the time to start treatment at the neighboring facility is known. Assuming Poisson arrivals and exponential times for the length of stay in the ED, we show that the optimal AD policy follows a threshold structure, and explore the behavior of optimal policies under different scenarios. We analyze the value of information on the time to start treatment in the neighboring hospital, and show that optimal policies depend strongly on the congestion experienced by the other facility. Simulation is used to compare the performance of the proposed MDP model to that of simple heuristics under more realistic assumptions. Results indicate that the MDP model performs significantly better than the tested heuristics under most cases. Finally, we discuss practical issues related to the implementation of the policies prescribed by the MDP.

Original languageEnglish (US)
Pages (from-to)298-312
Number of pages15
JournalEuropean Journal of Operational Research
Volume236
Issue number1
DOIs
StatePublished - Jul 1 2014

Keywords

  • Ambulance diversion
  • Emergency departments
  • Markov decision processes

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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