Health systems efficiency in China and ASEAN, 2015–2020: a DEA-Tobit and SFA analysis application

托比模型 数据包络分析 全要素生产率 索引(排版) 马尔奎斯特指数 效率低下 随机前沿分析 国内生产总值 中国 生产力 经济 医学 经济增长 计量经济学 地理 统计 宏观经济学 考古 微观经济学 万维网 生产(经济) 计算机科学 数学
作者
Jing Kang,Rong Peng,Jun Feng,Junyuan Wei,Li Zhen,Huang Fen,Yu Fu,Xiaorong Su,Yu-Jung Chen,Xianjing Qin,Qiming Feng
出处
期刊:BMJ Open [BMJ]
卷期号:13 (9): e075030-e075030 被引量:1
标识
DOI:10.1136/bmjopen-2023-075030
摘要

Objective To evaluate the health systems efficiency in China and Association of Southeast Asian Nations (ASEAN) countries from 2015 to 2020. Design Health efficiency analysis using data envelopment analysis (DEA) and stochastic frontier approach analysis. Setting Health systems in China and ASEAN countries. Methods DEA-Malmquist model and SFA model were used to analyse the health system efficiency among China and ASEAN countries, and the Tobit regression model was employed to analyse the factors affecting the efficiency of health system among these countries. Results In 2020, the average technical efficiency, pure technical efficiency and scale efficiency of China and 10 ASEAN countries’ health systems were 0.700, 1 and 0.701, respectively. The average total factor productivity (TFP) index of the health systems in 11 countries from 2015 to 2020 was 0.962, with a decrease of 1.4%, among which the average technical efficiency index was 1.016, and the average technical progress efficiency index was 0.947. In the past 6 years, the TFP index of the health system in Malaysia was higher than 1, while the TFP index of other countries was lower than 1. The cost efficiency among China and ASEAN countries was relatively high and stable. The per capita gross domestic product (current US$) and the urban population have significant effects on the efficiency of health systems. Conclusions Health systems inefficiency is existing in China and the majority ASEAN countries. However, the lower/middle-income countries outperformed high-income countries. Technical efficiency is the key to improve the TFP of health systems. It is suggested that China and ASEAN countries should enhance scale efficiency, accelerate technological progress and strengthen regional health cooperation according to their respective situations.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
昏睡的绮梅完成签到 ,获得积分10
刚刚
大模型应助一一采纳,获得10
刚刚
852应助契约采纳,获得10
刚刚
科研通AI2S应助liu采纳,获得10
刚刚
1秒前
H2O发布了新的文献求助10
1秒前
1秒前
华仔应助背后的丹云采纳,获得10
2秒前
2秒前
大模型应助愉快的绮梅采纳,获得10
2秒前
芬达发布了新的文献求助10
2秒前
科研通AI6.1应助yooo采纳,获得30
2秒前
2秒前
wxm完成签到,获得积分10
2秒前
2秒前
珺珺应助嘻嘻采纳,获得10
3秒前
3秒前
3秒前
4秒前
鲤鱼访梦完成签到 ,获得积分10
5秒前
5秒前
何科萱发布了新的文献求助10
6秒前
不会读文献的研究生完成签到,获得积分10
6秒前
vv发布了新的文献求助10
6秒前
浮浮世世发布了新的文献求助10
7秒前
7秒前
7秒前
华仔应助三分之一星辰采纳,获得10
7秒前
咚巴拉发布了新的文献求助10
7秒前
春风发布了新的文献求助10
8秒前
YuSun完成签到,获得积分10
8秒前
8秒前
大模型应助Louise采纳,获得10
8秒前
8秒前
bkagyin应助zzczbc采纳,获得10
9秒前
就这完成签到,获得积分10
9秒前
Orange应助小小青椒采纳,获得10
9秒前
wang发布了新的文献求助10
9秒前
桐桐应助223311采纳,获得10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Rheumatoid arthritis drugs market analysis North America, Europe, Asia, Rest of world (ROW)-US, UK, Germany, France, China-size and Forecast 2024-2028 500
17α-Methyltestosterone Immersion Induces Sex Reversal in Female Mandarin Fish (Siniperca Chuatsi) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6364719
求助须知:如何正确求助?哪些是违规求助? 8178803
关于积分的说明 17238989
捐赠科研通 5419755
什么是DOI,文献DOI怎么找? 2867783
邀请新用户注册赠送积分活动 1844819
关于科研通互助平台的介绍 1692321