Comparing population and incident data for optimal air ambulance base locations in Norway
Abstract Background Helicopter emergency medical services are important in many health care systems. Norway has a nationwide physician manned air ambulance service servicing a country with large geographical variations in population density and incident frequencies. The aim of the study was to compa...
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2018-05-01
|
Series: | Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s13049-018-0511-4 |
id |
doaj-893c4de7f3c24865a58db964a43cbe68 |
---|---|
record_format |
Article |
spelling |
doaj-893c4de7f3c24865a58db964a43cbe682020-11-25T00:45:15ZengBMCScandinavian Journal of Trauma, Resuscitation and Emergency Medicine1757-72412018-05-0126111110.1186/s13049-018-0511-4Comparing population and incident data for optimal air ambulance base locations in NorwayJo Røislien0Pieter L. van den Berg1Thomas Lindner2Erik Zakariassen3Oddvar Uleberg4Karen Aardal5J. Theresia van Essen6Faculty of Health Sciences, University of StavangerRotterdam School of Management, Erasmus UniversityNorwegian Air Ambulance Foundation, Department of ResearchDepartment of Global Public Health and Primary Care, University of BergenDepartment of Emergency Medicine and Pre-Hospital Services, St.Olav’s University HospitalDelft Institute of Applied Mathematics, Delft University of TechnologyDelft Institute of Applied Mathematics, Delft University of TechnologyAbstract Background Helicopter emergency medical services are important in many health care systems. Norway has a nationwide physician manned air ambulance service servicing a country with large geographical variations in population density and incident frequencies. The aim of the study was to compare optimal air ambulance base locations using both population and incident data. Methods We used municipality population and incident data for Norway from 2015. The 428 municipalities had a median (5–95 percentile) of 4675 (940–36,264) inhabitants and 10 (2–38) incidents. Optimal helicopter base locations were estimated using the Maximal Covering Location Problem (MCLP) optimization model, exploring the number and location of bases needed to cover various fractions of the population for time thresholds 30 and 45 min, in green field scenarios and conditioned on the existing base structure. Results The existing bases covered 96.90% of the population and 91.86% of the incidents for time threshold 45 min. Correlation between municipality population and incident frequencies was −0.0027, and optimal base locations varied markedly between the two data types, particularly when lowering the target time. The optimal solution using population density data put focus on the greater Oslo area, where one third of Norwegians live, while using incident data put focus on low population high incident areas, such as northern Norway and winter sport resorts. Conclusion Using population density data as a proxy for incident frequency is not recommended, as the two data types lead to different optimal base locations. Lowering the target time increases the sensitivity to choice of data.http://link.springer.com/article/10.1186/s13049-018-0511-4HEMSAir ambulanceFacility location problemMCLPPopulation densityIncidents |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jo Røislien Pieter L. van den Berg Thomas Lindner Erik Zakariassen Oddvar Uleberg Karen Aardal J. Theresia van Essen |
spellingShingle |
Jo Røislien Pieter L. van den Berg Thomas Lindner Erik Zakariassen Oddvar Uleberg Karen Aardal J. Theresia van Essen Comparing population and incident data for optimal air ambulance base locations in Norway Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine HEMS Air ambulance Facility location problem MCLP Population density Incidents |
author_facet |
Jo Røislien Pieter L. van den Berg Thomas Lindner Erik Zakariassen Oddvar Uleberg Karen Aardal J. Theresia van Essen |
author_sort |
Jo Røislien |
title |
Comparing population and incident data for optimal air ambulance base locations in Norway |
title_short |
Comparing population and incident data for optimal air ambulance base locations in Norway |
title_full |
Comparing population and incident data for optimal air ambulance base locations in Norway |
title_fullStr |
Comparing population and incident data for optimal air ambulance base locations in Norway |
title_full_unstemmed |
Comparing population and incident data for optimal air ambulance base locations in Norway |
title_sort |
comparing population and incident data for optimal air ambulance base locations in norway |
publisher |
BMC |
series |
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine |
issn |
1757-7241 |
publishDate |
2018-05-01 |
description |
Abstract Background Helicopter emergency medical services are important in many health care systems. Norway has a nationwide physician manned air ambulance service servicing a country with large geographical variations in population density and incident frequencies. The aim of the study was to compare optimal air ambulance base locations using both population and incident data. Methods We used municipality population and incident data for Norway from 2015. The 428 municipalities had a median (5–95 percentile) of 4675 (940–36,264) inhabitants and 10 (2–38) incidents. Optimal helicopter base locations were estimated using the Maximal Covering Location Problem (MCLP) optimization model, exploring the number and location of bases needed to cover various fractions of the population for time thresholds 30 and 45 min, in green field scenarios and conditioned on the existing base structure. Results The existing bases covered 96.90% of the population and 91.86% of the incidents for time threshold 45 min. Correlation between municipality population and incident frequencies was −0.0027, and optimal base locations varied markedly between the two data types, particularly when lowering the target time. The optimal solution using population density data put focus on the greater Oslo area, where one third of Norwegians live, while using incident data put focus on low population high incident areas, such as northern Norway and winter sport resorts. Conclusion Using population density data as a proxy for incident frequency is not recommended, as the two data types lead to different optimal base locations. Lowering the target time increases the sensitivity to choice of data. |
topic |
HEMS Air ambulance Facility location problem MCLP Population density Incidents |
url |
http://link.springer.com/article/10.1186/s13049-018-0511-4 |
work_keys_str_mv |
AT jorøislien comparingpopulationandincidentdataforoptimalairambulancebaselocationsinnorway AT pieterlvandenberg comparingpopulationandincidentdataforoptimalairambulancebaselocationsinnorway AT thomaslindner comparingpopulationandincidentdataforoptimalairambulancebaselocationsinnorway AT erikzakariassen comparingpopulationandincidentdataforoptimalairambulancebaselocationsinnorway AT oddvaruleberg comparingpopulationandincidentdataforoptimalairambulancebaselocationsinnorway AT karenaardal comparingpopulationandincidentdataforoptimalairambulancebaselocationsinnorway AT jtheresiavanessen comparingpopulationandincidentdataforoptimalairambulancebaselocationsinnorway |
_version_ |
1725271231843794944 |