Locating helicopter ambulance bases in Iceland : Efficient and fair solutions

• Published in: Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine
• Main Authors: Gunnarsson, Björn, Björnsdóttir, Kristrún María, Dúason, Sveinbjörn, Ingólfsson, Ármann
• Other Authors: University of Akureyri
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2023
• Subjects: Sjúkraflutningar; Air ambulance; Facility location problem; Fairness; Emergency Medicine; Critical Care and Intensive Care Medicine; Reykjavík; Iceland
• Online Access: https://hdl.handle.net/20.500.11815/4794; https://doi.org/10.1186/s13049-023-01114-9

Publisher Copyright: © 2023, The Author(s). Background Fixed-wing air ambulances play an important role in healthcare in rural Iceland. More frequent use of helicopter ambulances has been suggested to shorten response times and increase equity in access to advanced emergency care. In finding optimal base locations, the objective is often efficiency—maximizing the number of individuals who can be reached within a given time. This approach benefits people in densely populated areas more than people living in remote areas and the solution is not necessarily fair. This study aimed to find efficient and fair helicopter ambulance base locations in Iceland. Methods We used high-resolution population and incident location data to estimate the service demand for helicopter ambulances, with possible base locations limited to twenty-one airports and landing strips around the country. Base locations were estimated using both the maximal covering location problem (MCLP) optimization model, which aimed for maximal coverage of demand, and the fringe sensitive location problem (FSLP) model, which also considered uncovered demand (i.e., beyond the response time threshold). We explored the percentage of the population and incidents covered by one to three helicopter bases within 45-, 60-, and 75-min response time thresholds, conditioned or not, on the single existing base located at Reykjavík Airport. This resulted in a total of eighteen combinations of conditions for each model. The models were implemented in R and solved using Gurobi. Results Model solutions for base locations differed between the demand datasets for two out of eighteen combinations, both with the lowest service standard. Base locations differed between the MCLP and FSLP models for one combination involving a single base, and for two combinations involving two bases. Three bases covered all or almost all demand with longer response time thresholds, and the models differed in four of six combinations. The two helicopter ambulance bases can possibly obtain 97% ...