Literature DB >> 35313480

A Multi-Objective Optimization Approach for Emergency Medical Service Facilities Location-Allocation in Rural Areas.

Yulong Chen1,2, Zhizhu Lai3.   

Abstract

Purpose: The location of emergency medical service (EMS) facilities is a basic facility location problem. Many scholars have examined this kind of problem, but research on the location of EMS facilities in rural areas is still lacking. Different from urban areas, the location optimization of EMS facilities in rural areas must consider the accessibility of roads. The objective of this study conducted the optimal locations of new EMS stations and construction/upgrading of transfer links aiming to improve the medical emergency efficiency of mountain rural areas.
Methods: Three multi-objective models were constructed to examine the effects of varying assumptions (suppose existing roads cannot be upgraded, existing roads can be upgraded, and existing roads can be upgraded and new roads can be constructed) about minimizing the population considered uncovered (response time from the residential to the EMS station less than or equal to 0.5 h), time spent traveling from the residential area to the EMS station, construction costs for building new emergency facilities, and costs for improving or building new roads. Furthermore, we developed an improved multi-objective simulated annealing algorithm to examine the problem of optimizing the design of rural EMS facilities.
Results: We tested the models and algorithm on the Miao Autonomous County of Songtao, Guizhou Province, China. According to the actual situation of the case area, the models and algorithm were tested with the assumption that only three new EMS stations would be constructed. The number of people not covered by EMS stations decreased from 30.7% in Model 1 to 22% in Model 2, and then to 18.9% in Model 3.
Conclusion: Our study showed that the traffic network had a significant impact on the location optimization of EMS stations in mountainous rural areas. Improving the traffic network conditions could effectively improve the medical emergency efficiency of mountain rural areas.
© 2022 Chen and Lai.

Entities:  

Keywords:  emergency medical service station; multi-objective simulated annealing algorithm; the problem of facility location design; traffic network

Year:  2022        PMID: 35313480      PMCID: PMC8934169          DOI: 10.2147/RMHP.S332215

Source DB:  PubMed          Journal:  Risk Manag Healthc Policy        ISSN: 1179-1594


  5 in total

1.  Optimization by simulated annealing.

Authors:  S Kirkpatrick; C D Gelatt; M P Vecchi
Journal:  Science       Date:  1983-05-13       Impact factor: 47.728

2.  Paramedic response time: does it affect patient survival?

Authors:  Peter T Pons; Jason S Haukoos; Whitney Bludworth; Thomas Cribley; Kathryn A Pons; Vincent J Markovchick
Journal:  Acad Emerg Med       Date:  2005-07       Impact factor: 3.451

3.  Reducing Emergency Medical Service response time via the reallocation of ambulance bases.

Authors:  L C Nogueira; L R Pinto; P M S Silva
Journal:  Health Care Manag Sci       Date:  2014-04-18

4.  Combining spatial information and optimization for locating emergency medical service stations: A case study for Lower Austria.

Authors:  Robert Fritze; Anita Graser; Markus Sinnl
Journal:  Int J Med Inform       Date:  2017-12-14       Impact factor: 4.046

5.  Optimizing locations of waste transfer stations in rural areas.

Authors:  Yulong Chen; Zhizhu Lai; Zheng Wang; Dongyang Yang; Leying Wu
Journal:  PLoS One       Date:  2021-05-21       Impact factor: 3.240

  5 in total

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