Time-dependent ambulance allocation considering data-driven empirically required coverage.
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, mos...
| Publicado en: | Health Care Management Science Vol. 18; no. 4; pp. 444 - 459 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Dec2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=111003671&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 111003671 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13869620 BSE jtl: Health Care Management Science issn: 13869620 maglogo: N pubinfo: dt: Dec2015 vid: 18 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 111003671 111003671 NLM24609684 111003671 10.1007/s10729-014-9271-5 NLM24609684 111003671 ppf: 444 ppct: 15 formats: tig: atl: Time-dependent ambulance allocation considering data-driven empirically required coverage. aug: au: Degel, Dirk Wiesche, Lara Rachuba, Sebastian Werners, Brigitte affil: Ruhr University Bochum, Universitätsstraße 150 44801 Bochum Germany sug: subj: Resource Allocation Methods Ambulances Germany Models, Theoretical Human Urban Health Services Urban Health Services Administration Urban Population Linear Regression Quality of Health Care Ambulances Economics Time Factors Geographic Information Systems Resource Allocation Economics Validation Studies Comparative Studies Evaluation Research Multicenter Studies ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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