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Improving ambulance coverage in a mixed urban-rural region in Norway using mathematical modeling

BACKGROUND: Ambulance services play a crucial role in providing pre-hospital emergency care. In order to ensure quick responses, the location of the bases, and the distribution of available ambulances among these bases, should be optimized. In mixed urban-rural areas, this optimization typically inv...

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Autores principales: van den Berg, Pieter L., Fiskerstrand, Peter, Aardal, Karen, Einerkjær, Jørgen, Thoresen, Trond, Røislien, Jo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461285/
https://www.ncbi.nlm.nih.gov/pubmed/30978264
http://dx.doi.org/10.1371/journal.pone.0215385
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author van den Berg, Pieter L.
Fiskerstrand, Peter
Aardal, Karen
Einerkjær, Jørgen
Thoresen, Trond
Røislien, Jo
author_facet van den Berg, Pieter L.
Fiskerstrand, Peter
Aardal, Karen
Einerkjær, Jørgen
Thoresen, Trond
Røislien, Jo
author_sort van den Berg, Pieter L.
collection PubMed
description BACKGROUND: Ambulance services play a crucial role in providing pre-hospital emergency care. In order to ensure quick responses, the location of the bases, and the distribution of available ambulances among these bases, should be optimized. In mixed urban-rural areas, this optimization typically involves a trade-off between backup coverage in high-demand urban areas and single coverage in rural low-demand areas. The aim of this study was to find the optimal distribution of bases and ambulances in the Vestfold region of Norway in order to optimize ambulance coverage. METHOD: The optimal location of bases and distribution of ambulances was estimated using the Maximum Expected Covering Location Model. A wide range of parameter settings were fitted, with the number of ambulances ranging from 1 to 15, and an average ambulance utilization of 0, 15, 35 and 50%, corresponding to the empirical numbers for night, afternoon and day, respectively. We performed the analysis both conditioned on the current base structure, and in a fully greenfield scenario. RESULTS: Four of the five current bases are located close to the mathematical optimum, with the exception of the northernmost base, in the rural part of the region. Moving this base, along with minor changes to the location of the four other bases, coverage can be increased from 93.46% to 97.51%. While the location of the bases is insensitive to the workload of the system, the distribution of the ambulances is not. The northernmost base should only be used if enough ambulances are available, and this required minimum number increases significantly with increasing system workload. CONCLUSION: As the load of the system increases, focus of the model shifts from providing single coverage in low-demand areas to backup coverage in high-demand areas. The classification rule for urban and rural areas significantly affects results and must be evaluated accordingly.
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spelling pubmed-64612852019-05-03 Improving ambulance coverage in a mixed urban-rural region in Norway using mathematical modeling van den Berg, Pieter L. Fiskerstrand, Peter Aardal, Karen Einerkjær, Jørgen Thoresen, Trond Røislien, Jo PLoS One Research Article BACKGROUND: Ambulance services play a crucial role in providing pre-hospital emergency care. In order to ensure quick responses, the location of the bases, and the distribution of available ambulances among these bases, should be optimized. In mixed urban-rural areas, this optimization typically involves a trade-off between backup coverage in high-demand urban areas and single coverage in rural low-demand areas. The aim of this study was to find the optimal distribution of bases and ambulances in the Vestfold region of Norway in order to optimize ambulance coverage. METHOD: The optimal location of bases and distribution of ambulances was estimated using the Maximum Expected Covering Location Model. A wide range of parameter settings were fitted, with the number of ambulances ranging from 1 to 15, and an average ambulance utilization of 0, 15, 35 and 50%, corresponding to the empirical numbers for night, afternoon and day, respectively. We performed the analysis both conditioned on the current base structure, and in a fully greenfield scenario. RESULTS: Four of the five current bases are located close to the mathematical optimum, with the exception of the northernmost base, in the rural part of the region. Moving this base, along with minor changes to the location of the four other bases, coverage can be increased from 93.46% to 97.51%. While the location of the bases is insensitive to the workload of the system, the distribution of the ambulances is not. The northernmost base should only be used if enough ambulances are available, and this required minimum number increases significantly with increasing system workload. CONCLUSION: As the load of the system increases, focus of the model shifts from providing single coverage in low-demand areas to backup coverage in high-demand areas. The classification rule for urban and rural areas significantly affects results and must be evaluated accordingly. Public Library of Science 2019-04-12 /pmc/articles/PMC6461285/ /pubmed/30978264 http://dx.doi.org/10.1371/journal.pone.0215385 Text en © 2019 van den Berg et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
van den Berg, Pieter L.
Fiskerstrand, Peter
Aardal, Karen
Einerkjær, Jørgen
Thoresen, Trond
Røislien, Jo
Improving ambulance coverage in a mixed urban-rural region in Norway using mathematical modeling
title Improving ambulance coverage in a mixed urban-rural region in Norway using mathematical modeling
title_full Improving ambulance coverage in a mixed urban-rural region in Norway using mathematical modeling
title_fullStr Improving ambulance coverage in a mixed urban-rural region in Norway using mathematical modeling
title_full_unstemmed Improving ambulance coverage in a mixed urban-rural region in Norway using mathematical modeling
title_short Improving ambulance coverage in a mixed urban-rural region in Norway using mathematical modeling
title_sort improving ambulance coverage in a mixed urban-rural region in norway using mathematical modeling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461285/
https://www.ncbi.nlm.nih.gov/pubmed/30978264
http://dx.doi.org/10.1371/journal.pone.0215385
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