Chen Yulong, Lai Zhizhu
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.
The College of Environment and Planning, Henan University, Kaifeng, Henan, People's Republic of China.
Risk Manag Healthc Policy. 2022 Mar 15;15:473-490. doi: 10.2147/RMHP.S332215. eCollection 2022.
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.
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.
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.
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.
紧急医疗服务（EMS）设施的选址是一个基本的设施选址问题。许多学者已经研究过这类问题，但农村地区EMS设施选址的研究仍然不足。与城市地区不同，农村地区EMS设施的选址优化必须考虑道路的可达性。本研究的目的是确定新EMS站点的最佳位置以及建设/升级转运链路，以提高山区农村的医疗应急效率。
构建了三个多目标模型，以检验不同假设（假设现有道路无法升级、现有道路可以升级、现有道路可以升级且可以新建道路）对最小化未覆盖人口（从住宅到EMS站点的响应时间小于或等于0.5小时）、从住宅区到EMS站点的出行时间、建设新应急设施的成本以及改善或新建道路的成本的影响。此外，我们开发了一种改进的多目标模拟退火算法来研究农村EMS设施设计优化问题。
我们在中国贵州省松桃苗族自治县对模型和算法进行了测试。根据案例地区的实际情况，在仅建设三个新EMS站点的假设下对模型和算法进行了测试。EMS站点未覆盖的人数从模型1中的30.7%降至模型2中的22%，然后降至模型3中的18.9%。
我们的研究表明，交通网络对山区农村地区EMS站点的选址优化有重大影响。改善交通网络条件可以有效提高山区农村的医疗应急效率。
