我国各省份卫生投入空间分布及预测研究

目的:分析我国2007—2017年人均政府卫生投入的空间分布,观察政府卫生投入的公平性,提出改善和优化的建议,促进政府卫生投入的优化配置。方法:利用空间自相关法、LISA指数法、Getis-Ord Gi^和Kriging插值预测法等对政府卫生投入空间分布进行分析,并对政府卫生投入分布的公平性进行预测与评价。结果:我国人均政府卫生投入省际间存在明显差异;2007—2017年人均政府卫生投入的全局Moran’s I指数为正值(0.216),具有统计学意义(P=0.001,Z=3.092)。LISA指数研究显示,我国人均政府卫生投入省际间存在局部聚集性;Getis-Ord*Gi进一步研究显示,中南部省份为人均政府卫生投入的热点聚集区,无明显的冷点聚集区。Kriging插值预测分析显示,未来人均政府卫生投入的冷热点将发生明显的变化,热点区集中在中部地区,而冷点区集中在西部和东部地区。结论:我国人均政府卫生投入省际间分布存在局部空间自相关,人均政府卫生投入存在聚集区,仍需进一步优化财政支付手段,因地制宜制定不同的财政帮扶政策。

Research on the Spatial Distribution and Prediction of Health Input of Provincial Governments in China

Objective:Analyzing the spatial distribution and equity of Chinese government health investment in recent 10 years,and then to find out the existing problems and put forward Suggestions for improvement and optimization.Methods:Spatial autocorrelation method,LISA index method,Getis-ord*Gi method and Kriging interpolation method are used to analyze the spatial distribution of government health input,and to predict and evaluate the fairness of the distribution of government health input.Results:There is a significant difference in per capita government health input between provinces.The global Moran's I indexes of per capita government health input from 2007 to 2017 are positive(0.216),with statistical significance(P=0.001,Z=3.092).LISA index shows that the per cap让a government health input in China has a local aggregation among provinces.Further studies by Getis-ord*Gi shows that the central and southern provinces are hot spots for per capita government health input,and there are no obvious cold spots.Kriging interpolation prediction analysis shows that the hot and cold points of per capita government health input will change significantly in the future.Hot spots are concentrated in the central region,while cold spots are concentrated in the western and eastern regions.Conclusion:Local spatial autocorrelation exists in the inter-provincial distribution of per capita government health input in China,and per capita government health input has aggregation areas.Therefore,it is still necessary to further optimize the means of financial payment and formulate different financial support policies according to local conditions.