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Distributed coordination of emergency medical service for angioplasty patients

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Abstract

In this paper we study the coordination of Emergency Medical Service (EMS) for patients with acute myocardial infarction with ST-segment elevation (STEMI). This is a health problem with high associated mortality. A “golden standard” treatment for STEMI is angioplasty, which requires a catheterization lab and a highly qualified cardiology team. It should be performed as soon as possible since the delay to treatment worsens the patient’s prognosis. The decrease of the delay is achieved by coordination of EMS, which is especially important in the case of multiple simultaneous patients. Nowadays, this process is based on the First-Come-First-Served (FCFS) principle and it heavily depends on human control and phone communication with high proneness to human error and delays. The objective is, therefore, to automate the EMS coordination while minimizing the time from symptom onset to reperfusion and thus to lower the mortality and morbidity resulting from this disease. In this paper, we present a multi-agent decision-support system for the distributed coordination of EMS focusing on urgent out-of-hospital STEMI patients awaiting angioplasty. The system is also applicable to emergency patients of any pathology needing pre-hospital acute medical care and urgent hospital treatment. The assignment of patients to ambulances and angioplasty-enabled hospitals with cardiology teams is performed via a three-level optimization model. At each level, we find a globally efficient solution by a modification of the distributed relaxation method for the assignment problem called the auction algorithm. The efficiency of the proposed model is demonstrated by simulation experiments.

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Authors and Affiliations

  1. University Rey Juan Carlos, Madrid, Spain

    Marin Lujak, Holger Billhardt & Sascha Ossowski

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  1. Marin Lujak
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Correspondence to Marin Lujak.

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Lujak, M., Billhardt, H. & Ossowski, S. Distributed coordination of emergency medical service for angioplasty patients. Ann Math Artif Intell 78, 73–100 (2016). https://doi.org/10.1007/s10472-016-9507-9

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