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. 2022 Sep 28;19(19):12369.
doi: 10.3390/ijerph191912369.

Reorganization of an Emergency Medical System in a Mixed Urban-Rural Area

L'udmila Jánošíková  1 , Peter Jankovič  1 , Marek Kvet  1 , Gaston Ivanov  2 , Jakub Holod  2 , Imrich Berta  2
Affiliations

Reorganization of an Emergency Medical System in a Mixed Urban-Rural Area

L'udmila Jánošíková et al. Int J Environ Res Public Health. .

Abstract

The reorganization of an emergency medical system means that we look for new locations of ambulance stations with the aim of improving the accessibility of the service. We applied two tools that are well known in the operations research community, namely mathematical programming, and computer simulation. Using the hierarchical pq-median model, we proposed optimal locations of the stations throughout the country and within large towns. Several solutions have been calculated that differ in the number of stations that are supposed to be relocated to new positions. The locations proposed by the mathematical programming model were evaluated via computer simulation. The approach was demonstrated under the conditions of the Slovak Republic using real historical data on ambulance dispatches. We have concluded that (i) the distribution of the stations proposed by the hierarchical pq-median model overcomes the current distribution; the performance of the system has significantly improved even if only 10% of the stations are relocated to new municipalities; (ii) the variant that relocates 40% of the stations is a reasonable compromise between the benefits and induced costs; (iii) optimizing station locations in big towns can significantly improve the local as well as the nationwide performance indicators; the response times in two regional capitals has reduced by more than 4 min.

Keywords: ambulance location; computer simulation; coverage; emergency medical service; response time.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(a) The ratio of the number of trips on individual days to the daily average in 2019; (b) The ratio of the number of trips in individual months to the monthly average in 2019.
Figure 2
Figure 2
Trip rate by time of day, 2019.
Figure 3
Figure 3
The average response time decreases with increasing level of system optimization.
Figure 4
Figure 4
Difference in the average response time to the patients of priority K and N. A comparison of the 40% scenario with the current deployment of stations.
Figure 5
Figure 5
City of Banská Bystrica. (a) Distribution of demand; (b) Current and optimal locations of the stations; currently 4 stations are at the same address.
See this image and copyright information in PMC

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