我国医疗卫生机构收入与支出空间分布变化分析
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摘要
目的:比较我国新医改前后医疗卫生机构收入与支出的空间分布变化情况,为改善区域性医疗服务平衡发展提供科学参考。方法:整理我国医疗卫生机构收入支出的各年度数据,利用ArcGIS 10.2软件对该数据进行空间自相关分析。结果:2007—2016年(除2015年外),收入、支出的全局Moran’s I指数均为正值,差异有统计学意义(P<0.05),且在2010年后减弱。局部自相关分析显示,东部省份为收支热点聚集区,西部省份为冷点聚集区,十年间聚集地区明显减少。截止到2016年,收支冷点区域减少了甘肃、四川,仅剩新疆,热点区域减少了福建、浙江、江西,仅剩江苏、上海、山东、安徽。结论:省际医疗卫生机构收支差距悬殊,新医改之后有缩小趋势。医疗卫生机构收入、支出存在空间聚集性,表现为高收入(支出)省份毗邻,低收入(支出)省份毗邻。新医改之后空间自相关性呈减弱趋势,且冷热点聚集区域均明显减少,医疗卫生区域平衡发展初见成效,区域卫生服务利用公平性有所提升。
Objective: To compare the spatial distribution of medical and health institutions` income and expenditure before and after the new medical reform in China, in order to provide scientific references for improving the balanced development of regional medical services. Methods: It sorted out the annual data of the medical and health institutions` income expenditure in China, and used ArcGIS10.2 Software to analyze the spatial autocorrelation of the data. Results: In 2007—2016(except 2015), the overall Moran's I index of income and expenditure was positive, which was statistically significant(P<0.05, Z >1.96), and weakened after 2010. Spatial autocorrelation showed that the eastern provinces were the hotspots for the income and expenditure, and the western were the cold. Up to 2016, the cold spot area had been reduced to Gansu and Sichuan, while Xinjiang remained. The hotspots reduced Fujian, Zhejiang,and Jiangxi, while Jiangsu, Shanghai, Shandong and Anhui remained. Conclusion: Provincial medical and health institutions had a disparity in income and expenditure, and there was a narrowing trend after the new reform. The data were spatially clustered, showing the high income(expenditure) provinces adjacent to each other and low-income(expenditure) provinces adjacent. After the new medical reform, the spatial autocorrelation was weakened, and the cold hot spot gathering area was significantly reduced. The balanced development of the medical and health areas was initially effective, and the equity of regional health service utilization was improved.
Objective: To compare the spatial distribution of medical and health institutions` income and expenditure before and after the new medical reform in China, in order to provide scientific references for improving the balanced development of regional medical services. Methods: It sorted out the annual data of the medical and health institutions` income expenditure in China, and used ArcGIS10.2 Software to analyze the spatial autocorrelation of the data. Results: In 2007—2016(except 2015), the overall Moran's I index of income and expenditure was positive, which was statistically significant(P<0.05, Z >1.96), and weakened after 2010. Spatial autocorrelation showed that the eastern provinces were the hotspots for the income and expenditure, and the western were the cold. Up to 2016, the cold spot area had been reduced to Gansu and Sichuan, while Xinjiang remained. The hotspots reduced Fujian, Zhejiang,and Jiangxi, while Jiangsu, Shanghai, Shandong and Anhui remained. Conclusion: Provincial medical and health institutions had a disparity in income and expenditure, and there was a narrowing trend after the new reform. The data were spatially clustered, showing the high income(expenditure) provinces adjacent to each other and low-income(expenditure) provinces adjacent. After the new medical reform, the spatial autocorrelation was weakened, and the cold hot spot gathering area was significantly reduced. The balanced development of the medical and health areas was initially effective, and the equity of regional health service utilization was improved.
引文
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[15]马桂峰,蔡伟芹,王培承,等.我国不同社会医疗保险参保群体卫生服务利用不平等研究[J].中国卫生经济,2017,36(12):28-31.
[2]孟庆跃,江启成,刘国祥.卫生经济学[M].北京.人民卫生出版社,2013.
[3]魏娜娜,鲍俊哲,宇传华,等.中国卫生总费用空间分布特征与趋势分析[J].中国卫生资源,2016,19(1):47-51.
[4]Cliff A D,ORD J K.Spatial autocorrelation[M].London:Pion,1973:11-23.
[5]GOODCHILD M F.Spatial Autocorrelation[M].Nor-wich:GeoBooks,1986:5-12.
[6]宋琳,董春,胡晶,等.基于空间统计分析与GIS的人均GDP空间分布模式研究[J].测绘科学,2006,31(4):123-125.
[7]毕育学,颜虹.基于ArcGIS的数字地图制作技术[J].中国卫生统计,2011,28(5):602-603.
[8]张松林,张昆.空间自相关局部指标Moran指数和G系数研究[J].大地测量与地球动力学,2007,27(3):31-34.
[9]张松林,张昆.局部空间自相关指标对比研究[J].统计研究,2007,24(7):65-67.
[10]唐咸艳,黄天壬,朱小东,等.应用空间自相关分析研究广西壮族自治区肝癌的空间异质性分布特征[J].中华流行病学杂志,2009,30(2):167-170.
[11]国家卫生和计划生育委员会.2013中国卫生和计划生育统计年鉴[M].北京:中国协和医科大学出版社,2013.
[12]刘国祥,谢小平,贺长志,等.医疗卫生机构公共卫生费用核算方法研究[J].中国卫生经济,2008,27(5):19-21.
[13]中华人民共和国卫生部.2009中国卫生统计年鉴[M].北京:中国协和医科大学出版社,2009.
[14]程杨杨,许敏兰,井淇,等.基于省际视角的我国卫生筹资结构空间分布研究[J].中国卫生经济,2016,35(1):53-56.
[15]马桂峰,蔡伟芹,王培承,等.我国不同社会医疗保险参保群体卫生服务利用不平等研究[J].中国卫生经济,2017,36(12):28-31.