中国卫生筹资水平地域性特征及影响因素Lasso回归分析

Lasso regression analysis on regional characteristics and influencing factors of health financing in China

目的研究中国31个省级行政区域卫生总费用筹集水平的地域性特征与影响因素,为改进卫生筹资政策提供参考。方法基于2019年-2020年《中国卫生健康统计年鉴》及《中国统计年鉴》数据,采用Q型聚类方法,对2018年中国内陆31个省级行政区域人均卫生总费用(TEH)与TEH/GDP分别进行聚类;运用Lasso回归模型,从社会人口、经济、卫生系统3个维度提取9个自变量,分析卫生总费用筹集水平的影响因素。结果聚类结果显示,第1类为西藏等3个西部地区,其TEH/GDP均高于9.5%;北京等21个省市为第2类,其TEH/GDP均在6.0%以上;第3类地区为江苏等7个省,TEH/GDP在4.34%~5.94%之间,低于2018年全国平均水平。可见沿海地区与西部地区存在明显的投入差距。2018年北京的人均TEH最高,为11609.06元,安徽最低,为3159.72元,高投入地区人均TEH高于低投入地区近3倍;TEH/GDP西藏最高,为11.36%,福建最低,为4.34%,全国TEH/GDP平均水平为6.43%;Lasso回归分析中,城镇化水平影响程度最大,其次为病床使用率,回归系数分别为-11.76和10.80。每千人口卫生技术人员数对人均TEH和TEH/GDP均产生正向影响,城镇基本医疗保险参保人数与人均TEH和TEH/GDP均呈现显著的负向关系。结论2018年中国31个省级行政区域卫生总费用筹集水平存在显著的地域差异,卫生供给能力与城镇化水平是其增长的主要原因。

Objective To investigate the regional characteristics and influencing factors of total health expenditure in 31 provincial-level administrative divisions in China's Mainland to provide reference for improving health financing policies.Methods Based on the data from"China Health Statistical Yearbook"and"China Statistical Yearbook"from 2019 to 2020,we used the Q-type clustering method to separately cluster the per capita total expenditure on health(TEH)and TEH/GDP in 31 provincial-level administrative divisions in China's Mainland in 2018.Using the Lasso regression model,we extracted nine independent variables from three dimensions(i.e.,socio-demographics,economy,and health systems)to analyze the influencing factors of health funding.Results Clustering results showed that the first category included Tibet and other two western provinces/autonomous regions,with a TEH/GDP of higher than 9.5%;Beijing and other 20 provinces/municipalities were in the second category,with their TEH/GDP above 6.0%;the third category included seven provinces(e.g.,Jiangsu),with TEH/GDP ranging from 4.34%to 5.94%,which was lower than the national average for that year.Therefore,there was a significant investment gap between the coastal area and the western area.In 2018,Beijing had the highest per capita TEH(11,609.06 RMB yuan),and Anhui's was the lowest(3,159.72 yuan).The per capita TEH in high-input areas was nearly three times higher than that in low-input areas.The TEH/GDP was the highest in Tibet(11.36%)and the lowest in Fujian(4.34%).The national average TEH/GDP was 6.43%.In the Lasso regression analysis,the urbanization level had the greatest impact on health funding,followed by the utilization rate of hospital beds,with regression coefficients of-11.76 and 10.80,respectively.The number of health technicians per thousand population had a positive impact on per capita TEH and TEH/GDP,and the number of urban residents covered by urban basic medical insurance was negatively associated with per capita TEH and TEH/GDP.Conclusion In 2018,there were significant regional differences in the level of TEH in 31 provincial-level administrative divisions in inland China,mainly due to health supply capacity and urbanization level.