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

Yulong Chen; Zhizhu Lai

doi:10.2147/RMHP.S332215

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

Risk Manag Healthc Policy. 2022 Mar 15:15:473-490. doi: 10.2147/RMHP.S332215. eCollection 2022.

Authors

Yulong Chen^{1

2}, Zhizhu Lai³

Affiliations

¹ Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, Henan, People's Republic of China.
² The College of Environment and Planning, Henan University, Kaifeng, Henan, People's Republic of China.
³ School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, Jiangxi, People's Republic of China.

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.

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

Grants and funding

This work was supported by the Key Scientigic Research Projects of Colledges and University in Henan Province (Grant no. 21A170006), Scientific Research Fundation for PhD of GNNU (Grand no. BSJJ202116), Humanities and Social Sciences Research Project of the Ministry of Eduction (Grant no. 20YJ790017).