基于空间自相关技术的我国2015年卫生总费用分析
|
摘要
目的:探究我国卫生总费用空间规律,观察空间分布情况与特征。方法:对我国2015年包含政府、社会、个人与合计项支出在内的卫生总费用各项条目进行空间自相关检验,包括全局自相关与局部自相关检验。结果:全局空间检测显示2015年我国政府、社会、个人与合计项卫生总费用Moran’s I指数分别为0.224839、0.239297、0.201960、0.229333(Moran’s I>0),表明我国卫生总费用总体呈全局空间正相关态势,即呈高支出地域包围高支出地域、低支出地域包围低支出地域的总体空间分布趋势。局部空间检测显示我国局部地区存在空间异质现象(P<0.05)。通过LISA图的可视化效果可知,我国局部地区卫生总费用存在高支出地域包围低支出地域、低支出地域包围高支出地域的情况。结论:2015年我国卫生总费用存在空间分布规律,具体表现为总体卫生费用呈现东高西低趋势、部分地区出现"热点"与"冷点"的现象。
Objective: To explore whether there is a spatial rule of the total health expenditure in China recently and observe its spatial distribution and characteristics. Methods: The spatial auto-correlation tests was carried out, including global auto-correlation and local auto-correlation tests, on the items of China's total health expenditure, including government, society, individuals and total expenditure. Results: Global space detection showed that in 2015 the Moran's I index of Chinese government, society, individual and the total health expense were 0.224839, 0.239297, 0.201960, 0.229333(Moran's I>0), which shows that China's total health expenses was positively related to the global space, i.e., the overall trend of high expenditure areas surrounding high expenditure areas and low expenditure areas surrounding low expenditure areas. Local spatial detection revealed spatial heterogeneity in local areas of China(P<0.05). Based on the visualization effect of LISA diagram, it can be seen that some high-expenditure areas surround low-expenditure areas and low-expenditure areas surround high-expenditure areas. Conclusion: In 2015, China's total health expenditure has a spatial distribution pattern, which is reflected in the trend of overall health expenditure being "high in the east and low in the west", and the characteristics of "hot spots" and "cold spots" in some regions.
Objective: To explore whether there is a spatial rule of the total health expenditure in China recently and observe its spatial distribution and characteristics. Methods: The spatial auto-correlation tests was carried out, including global auto-correlation and local auto-correlation tests, on the items of China's total health expenditure, including government, society, individuals and total expenditure. Results: Global space detection showed that in 2015 the Moran's I index of Chinese government, society, individual and the total health expense were 0.224839, 0.239297, 0.201960, 0.229333(Moran's I>0), which shows that China's total health expenses was positively related to the global space, i.e., the overall trend of high expenditure areas surrounding high expenditure areas and low expenditure areas surrounding low expenditure areas. Local spatial detection revealed spatial heterogeneity in local areas of China(P<0.05). Based on the visualization effect of LISA diagram, it can be seen that some high-expenditure areas surround low-expenditure areas and low-expenditure areas surround high-expenditure areas. Conclusion: In 2015, China's total health expenditure has a spatial distribution pattern, which is reflected in the trend of overall health expenditure being "high in the east and low in the west", and the characteristics of "hot spots" and "cold spots" in some regions.
引文
[1]黄冠.建立卫生筹资公平性新视角[J].中国卫生经济,2011,30(5):22-24.
[2]王昕.我国卫生总费用筹资分析与建议[J].中国软科学,2013(11):10-17.
[3]万泉,谢小平,赵郁馨.卫生总费用与卫生资源配置研究[J].中国卫生经济,2009,28(4):21-23.
[4]陈沛军,黎东生.基于ARIMA模型的中国卫生总费用预测分析[J].医学与社会,2016,29(3):18-20.
[5]张毓辉,万泉,王秀峰,等.2009-2014年中国卫生总费用分析[J].中国卫生经济,2016,35(3):5-8.
[6]马明媛,韩玉珍,刘国栋,等.基于Elman神经网络的我国卫生总费用预测研究[J].中国医院管理,2018,38(6):52-54.
[7]张晓溪,宗莲,李芬,等.2016年上海市卫生总费用核算结果及特点分析[J].中国卫生经济,2018,37(8):45-49.
[8]蒋艳,满晓玮,赵丽颖,等.基于时间序列数据的北京市卫生筹资水平、构成趋势研究[J].中国卫生政策研究,2018,11(7):1-6.
[9]蒲英霞,葛莹,马荣华,等.基于ESDA的区域经济空间差异分析——以江苏省为例[J].地理研究,2005(6):965-974.
[10]徐旳,柯文前,陈培阳.基于ESDA的河南艾滋病空间格局[J].地理研究,2013,32(7):1199-1208.
[11]苏宝利,时涛.基于时空尺度的公共卫生资源配置均等化测度研究[J].中国卫生统计,2014,31(2):307-311.
[12]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.
[13]程杨杨,山珂,井淇,等.城乡视角下我国居民医疗保健支出空间分布研究[J].中国卫生经济,2015,34(11):54-58.
[14]郭锋,张毓辉,万泉,等.2015年中国卫生总费用核算结果与分析[J].中国卫生经济,2017,36(4):13-16.
[15]张毓辉,万泉,王秀峰,等.“十三五”时期中国卫生总费用监测预警研究[J].卫生经济研究,2017(1):8-13.
[16]崔晴川,蒋炜.国际视角剖析中国卫生总费用筹资结构的“适宜性”[J].重庆大学学报(社会科学版),2016,22(6):62-69.
[17]陈渝,张泰瑞.卫生筹资中社会卫生支出的预测与分析[J].中国卫生政策研究,2018,11(7):13-18.
[18]李相荣,汤榕,张晨曦,等.我国卫生总费用影响因素分析[J].卫生软科学,2018,32(1):50-53.
[19]陶春海,王梦颖.基于Lasso回归模型的我国个人卫生支出占比影响因素分析[J].统计与决策,2017(21):100-103.
[2]王昕.我国卫生总费用筹资分析与建议[J].中国软科学,2013(11):10-17.
[3]万泉,谢小平,赵郁馨.卫生总费用与卫生资源配置研究[J].中国卫生经济,2009,28(4):21-23.
[4]陈沛军,黎东生.基于ARIMA模型的中国卫生总费用预测分析[J].医学与社会,2016,29(3):18-20.
[5]张毓辉,万泉,王秀峰,等.2009-2014年中国卫生总费用分析[J].中国卫生经济,2016,35(3):5-8.
[6]马明媛,韩玉珍,刘国栋,等.基于Elman神经网络的我国卫生总费用预测研究[J].中国医院管理,2018,38(6):52-54.
[7]张晓溪,宗莲,李芬,等.2016年上海市卫生总费用核算结果及特点分析[J].中国卫生经济,2018,37(8):45-49.
[8]蒋艳,满晓玮,赵丽颖,等.基于时间序列数据的北京市卫生筹资水平、构成趋势研究[J].中国卫生政策研究,2018,11(7):1-6.
[9]蒲英霞,葛莹,马荣华,等.基于ESDA的区域经济空间差异分析——以江苏省为例[J].地理研究,2005(6):965-974.
[10]徐旳,柯文前,陈培阳.基于ESDA的河南艾滋病空间格局[J].地理研究,2013,32(7):1199-1208.
[11]苏宝利,时涛.基于时空尺度的公共卫生资源配置均等化测度研究[J].中国卫生统计,2014,31(2):307-311.
[12]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.
[13]程杨杨,山珂,井淇,等.城乡视角下我国居民医疗保健支出空间分布研究[J].中国卫生经济,2015,34(11):54-58.
[14]郭锋,张毓辉,万泉,等.2015年中国卫生总费用核算结果与分析[J].中国卫生经济,2017,36(4):13-16.
[15]张毓辉,万泉,王秀峰,等.“十三五”时期中国卫生总费用监测预警研究[J].卫生经济研究,2017(1):8-13.
[16]崔晴川,蒋炜.国际视角剖析中国卫生总费用筹资结构的“适宜性”[J].重庆大学学报(社会科学版),2016,22(6):62-69.
[17]陈渝,张泰瑞.卫生筹资中社会卫生支出的预测与分析[J].中国卫生政策研究,2018,11(7):13-18.
[18]李相荣,汤榕,张晨曦,等.我国卫生总费用影响因素分析[J].卫生软科学,2018,32(1):50-53.
[19]陶春海,王梦颖.基于Lasso回归模型的我国个人卫生支出占比影响因素分析[J].统计与决策,2017(21):100-103.