Urban–sub-urban–rural variation in the supply and demand of emergency medical services

供求关系 业务 农村地区 紧急医疗服务 基尼系数 人口 衡平法 资源分配 斯皮尔曼秩相关系数 环境卫生 医学 医疗急救 资源配置 计算机科学 不平等 经济 病理 数学分析 微观经济学 法学 机器学习 经济不平等 数学 计算机网络 政治学
作者
Yue Li,Ji Li,Jiayu Geng,Tao Liu,Xin Liu,Haojun Fan,Chunxia Cao
出处
期刊:Frontiers in Public Health [Frontiers Media]
卷期号:10 被引量:3
标识
DOI:10.3389/fpubh.2022.1064385
摘要

Emergency medical services (EMSs) are a critical component of health systems, often serving as the first point of contact for patients. Understanding EMS supply and demand is necessary to meet growing demand and improve service quality. Nevertheless, it remains unclear whether the EMS supply matches the demand after the 2016 healthcare reform in China. Our objective was to comprehensively investigate EMS supply-demand matching, particularly among urban vs. sub-urban vs. rural areas.Data were extracted from the Tianjin Medical Priority Dispatch System (2017-2021). From supply and demand perspectives, EMS resources and patient characteristics were analyzed. First, we performed a descriptive analysis of characteristics, used Moran's I to explore the spatial layout, and used the Gini coefficient to evaluate the equity of EMS supply and demand. Second, we analyzed urban-sub-urban-rural variation in the characteristics of EMS supply and demand by using the chi-square test. Finally, we examined the association between the EMS health resource density index and the number of patients by using the Spearman correlation and divided supply-demand matching types into four types.In 2021, the numbers of medical emergency stations and ambulances were 1.602 and 3.270 per 100,000 population in Tianjin, respectively. There were gradients in the health resource density index of the number of emergency stations (0.260 vs. 0.059 vs. 0.036; P = 0.000) in urban, sub-urban, and rural areas. There was no spatial autocorrelation among medical emergency stations, of which the G values by population, geographical distribution, and the health resource density index were 0.132, 0.649, and 0.473, respectively. EMS demand was the highest in urban areas, followed by sub-urban and rural areas (24.671 vs. 15.081 vs. 3.210 per 1,000 population and per year; P = 0.000). The EMS supply met the demand in most districts (r = 0.701, P = 0.003). The high supply-high demand types with stationary demand trends were distributed in urban areas; the low supply-high demand types with significant demand growth trends were distributed in sub-urban areas; and the low supply-low demand types with the highest speed of demand growth were distributed in rural areas.EMS supply quantity and quality were promoted, and the supply met the demand after the 2016 healthcare reform in Tianjin. There was urban-sub-urban-rural variation in EMS supply and demand patterns.
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