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. 2018 May 24;26(1):42.
doi: 10.1186/s13049-018-0511-4.

Comparing population and incident data for optimal air ambulance base locations in Norway

Jo Røislien  1   2 , Pieter L van den Berg  3 , Thomas Lindner  4   5 , Erik Zakariassen  6 , Oddvar Uleberg  7 , Karen Aardal  8   9 , J Theresia van Essen  8
Affiliations

Comparing population and incident data for optimal air ambulance base locations in Norway

Jo Røislien et al. Scand J Trauma Resusc Emerg Med. .

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.

Keywords: Air ambulance; Coverage; Facility location problem; HEMS; Incidents; MCLP; Population density.

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Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Figures

Fig. 1
Fig. 1
Population density heat map of Norway (left) and incident frequencies (right). Colour dots represent centroid location of the 428 municipalities. The 12 existing air ambulance bases superimposed
Fig. 2
Fig. 2
Municipality population vs total number of municipality incidents in Norway 2015
Fig. 3
Fig. 3
Optimal location to achieve 90, 95 and 100% coverage within 45 min based on municipality population data (left column) and aggregated yearly number of municipality incidents (right column) in Norway in 2015
Fig. 4
Fig. 4
Optimal location to achieve 90, 95 and 99% coverage within 30 min based on municipality population data (left column) and aggregated yearly number of municipality incidents (right column)
Fig. 5
Fig. 5
Optimal HEMS base locations when relocating or adding one base to the existing base structure, based on population data (left column) and incidence data (right column) for a 45 min threshold
Fig. 6
Fig. 6
Optimal HEMS base locations when relocating or adding one base to the existing base structure, based on population data (left column) and incidence data (right column) for a 30 min threshold
See this image and copyright information in PMC

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