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Time-dependent ambulance allocation considering data-driven empirically required coverage

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Abstract

Empirical studies considering the location and relocation of emergency medical service (EMS) vehicles in an urban region provide important insight into dynamic changes during the day. Within a 24-hour cycle, the demand, travel time, speed of ambulances and areas of coverage change. Nevertheless, most existing approaches in literature ignore these variations and require a (temporally and spatially) fixed (double) coverage of the planning area. Neglecting these variations and fixation of the coverage could lead to an inaccurate estimation of the time-dependent fleet size and individual positioning of ambulances. Through extensive data collection, now it is possible to precisely determine the required coverage of demand areas. Based on data-driven optimization, a new approach is presented, maximizing the flexible, empirically determined required coverage, which has been adjusted for variations due to day-time and site. This coverage prevents the EMS system from unavailability of ambulances due to parallel operations to ensure an improved coverage of the planning area closer to realistic demand. An integer linear programming model is formulated in order to locate and relocate ambulances. The use of such a programming model is supported by a comprehensive case study, which strongly suggests that through such a model, these objectives can be achieved and lead to greater cost-effectiveness and quality of emergency care.

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Acknowledgments

This research is financially supported by Stiftung Zukunft NRW. The authors are grateful to staff members of the Feuerwehr und Rettungsdienst Bochum for detailed insights.

The authors would like to thank the associate editor and two anonymous reviewers for their valuable comments. These suggestions have helped to improve the quality of this work.

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Authors and Affiliations

  1. Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany

    Dirk Degel, Lara Wiesche, Sebastian Rachuba & Brigitte Werners

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  1. Dirk Degel
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  2. Lara Wiesche
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  3. Sebastian Rachuba
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  4. Brigitte Werners
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Correspondence to Dirk Degel.

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Degel, D., Wiesche, L., Rachuba, S. et al. Time-dependent ambulance allocation considering data-driven empirically required coverage. Health Care Manag Sci 18, 444–458 (2015). https://doi.org/10.1007/s10729-014-9271-5

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  • DOI: https://doi.org/10.1007/s10729-014-9271-5

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