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A geographic information system simulation model of EMS: reducing ambulance response time

  • Kobi Peleg
    Correspondence
    Address reprint requests to Kobi Peleg, PhD, Gertner Institute, Sheba Medical Center, Tel-Hashomer 52621, Israel
    Affiliations
    Trauma and Emergency Medicine Research Unit, The Gertner Institute for Health Policy Research, Sheba Medical Center, Tel-Hashomer, Israel

    Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts, USA
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  • Joseph S. Pliskin
    Affiliations
    Department of Industrial Engineering and Management and Department of Health Systems Management, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts, USA
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      Abstract

      Response time is a very important factor in determining the quality of prehospital EMS. Our objective was to model the response by Israeli ambulances and to offer model-derived strategies for improved deployment of ambulances to reduce response time. Using a geographic information system (GIS), a retrospective review of computerized ambulance call and dispatch logs was performed in two different regional districts, one large and urban and the other rural. All calls that were pinpointed geographically by the GIS were included, and their data were stratified by weekday and by daily shifts. Geographic areas (polygons) of, at most, 8 minutes response time were simulated for each of these subgroups to maximize the timely response of calls. Before using the GIS model, mean response times in the Carmel and Lachish districts were 12.3 and 9.2 minutes, respectively, with 34% and 62% of calls responded within 8 minutes. When ambulances were positioned within the modeled polygons, more than 94% of calls met the 8-minute criterion. The GIS simulation model presented in this study suggests that EMS could be more effective if a dynamic load-responsive ambulance deployment is adopted, potentially resulting in increased survival and cost-effectiveness.

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