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Exploring optimal air ambulance base locations in Norway using advanced mathematical modelling
BACKGROUND: Helicopter emergency medical services are an important part of many healthcare systems. Norway has a nationwide physician staffed air ambulance service with 12 bases servicing a country with large geographical variations in population density. The aim of the study was to estimate optimal...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5293838/ https://www.ncbi.nlm.nih.gov/pubmed/27325670 http://dx.doi.org/10.1136/injuryprev-2016-041973 |
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author | Røislien, Jo van den Berg, Pieter L Lindner, Thomas Zakariassen, Erik Aardal, Karen van Essen, J Theresia |
author_facet | Røislien, Jo van den Berg, Pieter L Lindner, Thomas Zakariassen, Erik Aardal, Karen van Essen, J Theresia |
author_sort | Røislien, Jo |
collection | PubMed |
description | BACKGROUND: Helicopter emergency medical services are an important part of many healthcare systems. Norway has a nationwide physician staffed air ambulance service with 12 bases servicing a country with large geographical variations in population density. The aim of the study was to estimate optimal air ambulance base locations. METHODS: We used high resolution population data for Norway from 2015, dividing Norway into >300 000 1 km×1 km cells. Inhabited cells had a median (5–95 percentile) of 13 (1–391) inhabitants. Optimal helicopter base locations were estimated using the maximal covering location problem facility location optimisation model, exploring the number of bases needed to cover various fractions of the population for time thresholds 30 and 45 min, both in green field scenarios and conditioning on the current base structure. We reanalysed on municipality level data to explore the potential information loss using coarser population data. RESULTS: For a 45 min threshold, 90% of the population could be covered using four bases, and 100% using nine bases. Given the existing bases, the calculations imply the need for two more bases to achieve full coverage. Decreasing the threshold to 30 min approximately doubles the number of bases needed. Results using municipality level data were remarkably similar to those using fine grid information. CONCLUSIONS: The whole population could be reached in 45 min or less using nine optimally placed bases. The current base structure could be improved by moving or adding one or two select bases. Municipality level data appears sufficient for proper analysis. |
format | Online Article Text |
id | pubmed-5293838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-52938382017-02-27 Exploring optimal air ambulance base locations in Norway using advanced mathematical modelling Røislien, Jo van den Berg, Pieter L Lindner, Thomas Zakariassen, Erik Aardal, Karen van Essen, J Theresia Inj Prev Original Article BACKGROUND: Helicopter emergency medical services are an important part of many healthcare systems. Norway has a nationwide physician staffed air ambulance service with 12 bases servicing a country with large geographical variations in population density. The aim of the study was to estimate optimal air ambulance base locations. METHODS: We used high resolution population data for Norway from 2015, dividing Norway into >300 000 1 km×1 km cells. Inhabited cells had a median (5–95 percentile) of 13 (1–391) inhabitants. Optimal helicopter base locations were estimated using the maximal covering location problem facility location optimisation model, exploring the number of bases needed to cover various fractions of the population for time thresholds 30 and 45 min, both in green field scenarios and conditioning on the current base structure. We reanalysed on municipality level data to explore the potential information loss using coarser population data. RESULTS: For a 45 min threshold, 90% of the population could be covered using four bases, and 100% using nine bases. Given the existing bases, the calculations imply the need for two more bases to achieve full coverage. Decreasing the threshold to 30 min approximately doubles the number of bases needed. Results using municipality level data were remarkably similar to those using fine grid information. CONCLUSIONS: The whole population could be reached in 45 min or less using nine optimally placed bases. The current base structure could be improved by moving or adding one or two select bases. Municipality level data appears sufficient for proper analysis. BMJ Publishing Group 2017-02 2016-06-20 /pmc/articles/PMC5293838/ /pubmed/27325670 http://dx.doi.org/10.1136/injuryprev-2016-041973 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Original Article Røislien, Jo van den Berg, Pieter L Lindner, Thomas Zakariassen, Erik Aardal, Karen van Essen, J Theresia Exploring optimal air ambulance base locations in Norway using advanced mathematical modelling |
title | Exploring optimal air ambulance base locations in Norway using advanced mathematical modelling |
title_full | Exploring optimal air ambulance base locations in Norway using advanced mathematical modelling |
title_fullStr | Exploring optimal air ambulance base locations in Norway using advanced mathematical modelling |
title_full_unstemmed | Exploring optimal air ambulance base locations in Norway using advanced mathematical modelling |
title_short | Exploring optimal air ambulance base locations in Norway using advanced mathematical modelling |
title_sort | exploring optimal air ambulance base locations in norway using advanced mathematical modelling |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5293838/ https://www.ncbi.nlm.nih.gov/pubmed/27325670 http://dx.doi.org/10.1136/injuryprev-2016-041973 |
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