Ambulance location for maximum survival
Ambulance location for maximum survival
This article proposes new location models for emergency medical service stations. The models are generated by incorporating a survival function into existing covering models. A survival function is a monotonically decreasing function of the response time of an emergency medical service (EMS) vehicle to a patient that returns the probability of survival for the patient. The survival function allows for the calculation of tangible outcome measures—the expected number of survivors in case of cardiac arrests. The survival-maximizing location models are better suited for EMS location than the covering models which do not adequately differentiate between consequences of different response times. We demonstrate empirically the superiority of the survival-maximizing models using data from the Edmonton EMS system.
42-58
Erkut, Erhan
756888bd-dd7a-485e-a68c-384760276af4
Ingolfsson, Armann
238232b8-75d6-49da-b39c-70c8d0c7238a
Erdogan, Gunes
468310a1-5c36-4c3d-8b39-079bd621b34b
2008
Erkut, Erhan
756888bd-dd7a-485e-a68c-384760276af4
Ingolfsson, Armann
238232b8-75d6-49da-b39c-70c8d0c7238a
Erdogan, Gunes
468310a1-5c36-4c3d-8b39-079bd621b34b
Erkut, Erhan, Ingolfsson, Armann and Erdogan, Gunes
(2008)
Ambulance location for maximum survival.
Naval Research Logistics (NRL), 55 (1), .
(doi:10.1002/nav.20267).
Abstract
This article proposes new location models for emergency medical service stations. The models are generated by incorporating a survival function into existing covering models. A survival function is a monotonically decreasing function of the response time of an emergency medical service (EMS) vehicle to a patient that returns the probability of survival for the patient. The survival function allows for the calculation of tangible outcome measures—the expected number of survivors in case of cardiac arrests. The survival-maximizing location models are better suited for EMS location than the covering models which do not adequately differentiate between consequences of different response times. We demonstrate empirically the superiority of the survival-maximizing models using data from the Edmonton EMS system.
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Published date: 2008
Organisations:
Centre of Excellence for International Banking, Finance & Accounting
Identifiers
Local EPrints ID: 204811
URI: http://eprints.soton.ac.uk/id/eprint/204811
ISSN: 0894-069X
PURE UUID: 2ca926df-77f4-4547-8967-47ff0efd9621
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Date deposited: 01 Dec 2011 16:38
Last modified: 14 Mar 2024 04:33
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Author:
Erhan Erkut
Author:
Armann Ingolfsson
Author:
Gunes Erdogan
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