摘要
在基本医保制度全覆盖之后,政府对城乡居民的财政补贴规模持续扩大,却相对忽视了对产出结果的追踪。文章以Z省16个地级市为样本,采用因子分析和DEA方法对基本医保财政补贴绩效进行定量分析。研究发现,财政补贴投入冗余和产出不足并存,且超过一半的样本地区都存在不同程度的投入冗余;大部分样本地区的财政补贴绩效远未达到理想状态,平均有34.5%的补贴资源未能得到有效运用。为此,本文提出财政补贴标准应当进一步差异化,政府间补贴责任分摊应当合理化,财政补贴绩效评价应当常态化。并且,在"开源"的同时更要强化"节流",控制医疗费用的不合理增长。
After universal coverage of basic medical insurance system is achieved,the scale of government financial subsidies provided for urban and rural residents medical insurance have been continually expanding,but relatively neglecting the performance evaluation of subsidies output results.Based on data from 16 cities of Z province,the paper used the methods of Factor Analysis and DEA to perform the quantitative analysis of the performance of basic medical insurance financial subsidies.The results revealed that redundant input and insufficient output coexist in fiscal subsidies and more than half of the sample cities showed input redundancy.The financial subsidy performance in most of the sample areas was far from ideal,with an average of 34.5%subsidies being ineffectively used.As a result,input redundancy and output insufficiency coexisted in many cities.To this end,this paper suggests that the financial subsidy standards should be further differentiated,the duty share mechanism between the governments should be rationalized,and it s necessary to evaluate subsidy performance regularly.Meanwhile,in addition to“open source”,“cutting expense or throttling”should also be strengthened,and great efforts should be made to control the unreasonable increase of medical care expenses.
作者
罗耀
李亚青
LUO Yao;LI Ya-qing(Guangdong Mechanical and Electrical Polytechnic,Guangzhou Guangdong 510550,China;School of Finance,Guangdong University of Finance and Economics,Research Institute of Innovation Competitiveness of Guangdong,HongKong and Macao Bay Area,Guangzhou Guangdong 510320,China)
出处
《中国卫生政策研究》
CSCD
北大核心
2020年第6期34-42,共9页
Chinese Journal of Health Policy
基金
国家社科基金年度项目(18BJY215)。
关键词
医疗保险
财政补贴
绩效
因子分析
DEA
Medical insurance
Financial subsidies
Performance
Factor analysis
DEA
