ArticleFrontiers in public health2022
Urban-sub-urban-rural variation in the supply and demand of emergency medical services.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Urban-rural dichotomy of emergency medical service demand: spatiotemporal patterns and heterogeneous driving mechanisms.BMC public health · 2026Article
- Examining the association between spatial accessibility to emergency cardiac care centers and cardiovascular mortality in Georgia, United States.BMC cardiovascular disorders · 2026Article
- Spatial equity in the allocation of lifesaving resources: a cross-sectional spatial evaluation of automated external defibrillators in four first-tier Chinese cities.International journal of health geographics · 2026Article
- Carbon emission governance and public health efficiency in transitional China: Regional differences and spatial aggregation.PloS one · 2026Article
- Epidemiological and clinical analysis ofFrontiers in toxicology · 2026Article
- The five-link theory for improving the integrated and balanced development of emergency medical care in urban and rural areas.Journal of global health · 2025Article
- Spatial analysis of prehospital emergency medical services accessibility: a comparative evaluation of the GAUSS-probability two-step floating catchment area model in Handan City.Frontiers in public health · 2025Article
- Revealing spatiotemporal inequalities, hotspots, and determinants in healthcare resource distribution: insights from hospital beds panel data in 2308 Chinese counties.BMC public health · 2024Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: 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. Methods: 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. Results: 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; Conclusion: 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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