摘要
[目的]探究中国卫生总费用的影响因素并预测其未来发展趋势,为促进中国卫生事业发展提供相关建议。[方法]构建关于1990-2019年的时间序列,运用VAR模型和ARIMA模型研究GDP、医疗资源、城市化水平、人口老龄化、政府卫生支出等5个因素与中国卫生总费用的动态关系并预测卫生总费用未来发展趋势。[结果]通过ADF检验(P<0.05)后的VAR模型的AR根小于1,脉冲函数响应分析显示医疗资源、GDP、城市化水平、人口老龄化、政府卫生事业费与卫生总费用存在长期动态均衡关系;ARIMA模型预计2030年我国人均卫生总费用将达到14129.2162元。[结论]中国卫生总费用总额不断增长,增速有所减缓,但绝对增量大,政府调控任务艰巨;在我国现阶段,卫生总费用增长的最大影响因素是城市化水平,虽然老龄化在短期内对卫生总费用的影响不明显,但从长远角度对卫生总费用的影响不容忽视。政府部门应深化医疗体制改革,控制卫生费用合理增长,注重医疗资源的合理配置,并做好准备工作积极应对未来人口老龄化加剧带来的挑战。
Objective To explore the influencing factors and future development trends of China s total health expenditure so as to provide relevant suggestions for promoting the development of China s health services.Methods It built a time series from 1990 to 2019,studied the dynamic relationship between GDP,medical resources,urbanization level,population aging,government health expenditure and the total health expenditure in China by VAR and ARIMA model,and predicted future development trend of total health expenditure.Results After passed the ADF test(P<0.05),the AR root of the VAR model was less than 1,impulse function response analysis showed that there was a long-term dynamic equilibrium relationship between medical resources,GDP,urbanization level,population aging,government health service expenditures and total health expenditures.The ARIMA model predicts that our country s total per capita health expenditure will reach 1,4129.2162 yuan in 2030.Conclusions The total health expenditure in China is increasing continuously,growth speed has slowed,but the absolute increase is large.The task of government regulation is arduous.At this stage,the biggest factor influencing the growth of total health expenditure is the level of urbanization.Although it is not obvious of aging for influencing total health expenditure in short order,it cannot be ignored that the impact on total health expenditure in the long run.Government departments should deepen the reform of the medical system,control the reasonable growth of health expenses,pay attention to the reasonable allocation of medical resources,and make preparations to actively respond to the challenges of an aging population in the future.
作者
郭芮绮
胡依
闵淑慧
成晓芬
李贝
GUO Rui-qi;HU Yi;MIN Shu-hui;CHENG Xiao-fen;LI Bei(Health Management School of Southern Medical University,Guangzhou Guangdong 510515,China)
出处
《卫生软科学》
2022年第7期35-39,55,共6页
Soft Science of Health
基金
2020年广东省自然基金项目-珠三角城市流动老人社会融合度测量模型与干预路径研究(2020A1515011134)
2020年广州市哲学社会科学发展“十三五”规划项目-广州市流动老人社会融合度测量模型与干预路径研究(2020GZGJ130)。