Spatial-temporal differentiation and driving forces of medical service resilience of prefecture-level cities in China
The resilience of medical services reflects a region's medical response ability in the face of risks.The study of the spatial-temporal differentiation and driving forces of the resilience level of urban medical services can provide a theoretical reference for the construction of healthy China.Taking 287 cities of the prefecture level and above in China as research samples and integrating the concept of resilience,this study constructed an evaluation indicator system of the resilience of urban medical services,and analyzed the spatial and temporal distribution characteristics and driving forces of the resilience of urban medical services in China from 2011 to 2021.The study found that:1)The resilience level of urban medical services in China continued to increase year by year and overall,the spatial distribution showed a pattern of high in the coastal regions and low inland.There has been a trend towards a weakening of the regional differences,and some cities showed a certain degree of local polarization.2)The COVID-19 pandemic has profoundly affected the resilience of urban medical services in China,which showed strong resistance and adaptability.3)Based on the differences of dynamic factor combination,four medical service resilience driving models are identified:medical resource-oriented,fund-oriented,environment-dependent,and scientific research-dependent.4)The resilience of medical services is influenced by many external factors.Population ageing is negatively associated with healthcare service resilience,while municipal sanitation capacity and the penetration rate of the Internet have a positive impact on the resilience of medical services.The paper analyzed the driving force model of the urban medical services resilience in China,which can provide practical reference for the construction and resilience improvement of medical services in different types of regions.
medical servicesresiliencespatial-temporal differentiationdriving forces
万方数据
维普
