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The Spatial Pattern Dynamics Of Medical Network And Influential Factors Analysis In Mountainous Regions Since The Last Ten Years And Medical Spatial Accessibility Research

Posted on:2017-04-19Degree:MasterType:Thesis
Country:ChinaCandidate:L DengFull Text:PDF
GTID:2180330485477015Subject:Physical geography
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There have been many severe problems faced since our country made allocations of the medical resources of urban and rural areas for a long time: the lack of medical resources, the insufficiency of medical services, the absence of health care and so on.Under the context of Chinese medical reform, which is rapidly promoted, medical resources, as an important part of public services, to achieve fairness and efficiency of the supply of rural medical facilities, make most residents easily and equally enjoy high-quality medical services is the focus of rural reform during this new period. In our study, we take Shizhu county as research object and on the basis of field research data of various types of medical institutions in in 2004-2014, use spatial autocorrelation trend surface analysis, kernel density estimation methods, study the spatial pattern dynamics of medical network and influential factors in mountainous regions since the last ten years; And use the modified two- step floating catchment area method to evaluate the characteristics of spatial accessibility for realizing the medical resources equally layout from the phase of "uniform" to "equilibrium", finally to "homogeneous".Based on a case study of Shizhu County, the main contents in this paper are as follows:(1) Medical network nodes, point data layer of resident area distribution and space network data set were built via data collection and spot investigation.(2) Spatial evolution law was explored using methods of spatial autocorrelation, trend surface analysis and kernel density estimation ground on a large quantity of literature.(3) In view of the difference of radiation area of hospitals at all levels, we chose time costs as the travel impedance and a modified two-step mobile search method was employed to calculate the spatial accessibility of medical resources in the survey region.(4)Regression equations related to influence factor under different time impedance were obtained using multiple linear regression analysis method to quantitatively illustrate the influence of each factor.(5) Based on GIS, we fulfilled the visualization of all results and deeply analyzed them from different scales and perspectives.Study found that:(1)In the last ten years the size of the medical network are generally on the rise on the whole; The space positions of each type of medical institutions changed obviously; Medical and health services of each town have great changes in development. The layout of the medical network increasingly dispersed,following the rules of "cluster-disperse"; medical network pattern evolution presents the characteristics of the west intensive and the eastern sparse, following the rules of fragmentation, decentralization, equalization; The spatial differentiation of medical network in the north and south direction is very clear, each type of medical institutions evolved from "disharmony to coordination";(2) The spatial accessibility of medical services in Shizhu County is poor and below the average level in Chongqing Municipality on the whole; medical resources distribution is uneven and the spatial differentiation is very clear; scale and grade of hospitals and grade and density of roads have a great influence on accessibility; Accessibility is generally good in places near the county seat and have a dense road network; With the increase of the time impedance, accessibility gets better within the county but deteriorates at the peripherals of the villages and towns. The range of accessibility is lower,differentiation of spatial accessibility of medical services shrink, and the influences of the villages and towns with sufficient medical resources on accessibility of surrounding villages and towns increase.
Keywords/Search Tags:Poverty-stricken mountainous area, Medical network, spatial pattern dynamics, influence factor, space accessibility, sensitivity, Shizhu county
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