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Supporting decision making to improve the performance of an Italian Emergency Medical Service

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Abstract

An Emergency Medical Service (EMS) plays a fundamental role in providing good quality health care services to citizens, as it provides the first answer in distressing situations. Early response, one of the key factors in a successful treatment of an injury, is strongly influenced by the performance of ambulances, which are sent to rescue the patient. Here we report the research carried on by the authors on the ambulance location and management in the Milano area (Italy), as a part of a wider research project in collaboration with the EMS of Milano and funded by Regione Lombardia. The question posed by the EMS managers was clear and, at the same time, tricky: could decision making tools be applied, based on the currently available data, to provide suggestions for decision makers? To answer such a question, three different studies have been carried on: first the evaluation of the current EMS system performance through statistical analysis; then the study of operational policies which can improve the system performance through a simulation model; and finally the definition of an alternative set of posts through an optimization model. This paper describes the methodologies underlying such studies and reports on how their main findings were crucial to help the EMS in changing its organization model.

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Notes

  1. Regione Lombardia is the regional administrative district to which Milano belongs, and it is in charge of organizing emergency services.

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Acknowledgements

The authors wish to thank the Milano 118 Emergency Service Management for the fruitful collaboration and for providing us the data set and allowing their use in this paper. Besides, the author wish to thank the students S. Delfa, S. Perego and C. Romantini for their help for the numerical results. Finally, the authors wish to thank the anonymous referees for their comments which helped in improving the paper.

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Authors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Torino, Turin, Italy

    Roberto Aringhieri

  2. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy

    Giuliana Carello

  3. Dipartimento di Matematica, Università degli Studi di Milano, Milan, Italy

    Daniela Morale

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  1. Roberto Aringhieri
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  2. Giuliana Carello
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  3. Daniela Morale
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Correspondence to Roberto Aringhieri.

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Aringhieri, R., Carello, G. & Morale, D. Supporting decision making to improve the performance of an Italian Emergency Medical Service. Ann Oper Res 236, 131–148 (2016). https://doi.org/10.1007/s10479-013-1487-0

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