Mind the gap: population ageing and health financing sustainability

人口老龄化 收入 业务 人口 人口健康 公共卫生 卫生政策 持续性 医疗保健 财务 公共经济学 经济增长 经济 环境卫生 医学 生态学 护理部 生物
作者
Jonathan Cylus,Gemma Williams,Sarah Barber,Tomáš Roubal
出处
期刊:European journal of public health [Oxford University Press]
卷期号:31 (Supplement_3) 被引量:1
标识
DOI:10.1093/eurpub/ckab164.558
摘要

Abstract Background Models used to forecast the effects of population ageing on health financing usually only explore effects on health spending, while neglecting effects on health revenues. Methods Using publicly available data, we construct simulation models to project how changes in the population age mix affect both public sector health revenues and expenditures across a range of countries representing a diverse mix of health financing systems in Europe as well as the Western Pacific (Australia, Bulgaria, Japan, Slovenia, United Kingdom and Vietnam). Results By 2100, the largest gap between health revenues and expenditures due to population ageing under current health financing arrangements is expected in Vietnam; the majority of that health financing gap (87.1%) is attributable to expected growth in health expenditures. In Slovenia and Japan, the financing gaps are forecast to reach less than half that of Vietnam by 2100; however, the reasons for the increases in gaps vary. In Slovenia, nearly half of the increase in the gap (44.2%) is due to reductions in health revenues compared with just under one-third (28.7%) in Japan. Conclusions There is a perception that population ageing will have deleterious effects on the sustainability of public sector health financing. However, this is highly dependent on how financing systems are designed. Our simulation models demonstrate that comparative analyses that give equal attention to both health expenditures and revenues provide decision makers a balanced set of policy options for addressing the challenges of population ageing. The options range from targeting expenditures and utilization of services to diversifying revenue generation.

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
彭于晏应助yae采纳,获得10
1秒前
1秒前
李健的小迷弟应助yciDo采纳,获得30
2秒前
3秒前
3秒前
yun完成签到,获得积分20
4秒前
生动从丹发布了新的文献求助10
6秒前
6秒前
不是函数发布了新的文献求助30
9秒前
10秒前
kyou发布了新的文献求助10
11秒前
rmbsLHC发布了新的文献求助10
11秒前
Cc发布了新的文献求助10
11秒前
无情愫发布了新的文献求助10
14秒前
zjw完成签到,获得积分10
15秒前
15秒前
tiptip应助mxy126354采纳,获得10
17秒前
贪玩的秋柔应助mxy126354采纳,获得10
17秒前
贪玩的秋柔应助mxy126354采纳,获得10
17秒前
cc2004bj应助rockyshi采纳,获得10
17秒前
科研girl应助大熊采纳,获得10
20秒前
fly发布了新的文献求助10
22秒前
jeff发布了新的文献求助10
23秒前
23秒前
24秒前
26秒前
舒适的淇完成签到,获得积分10
26秒前
yciDo发布了新的文献求助30
26秒前
echo完成签到 ,获得积分10
28秒前
知悉发布了新的文献求助10
28秒前
上官若男应助Hantheex采纳,获得10
30秒前
pingpinglver完成签到 ,获得积分10
31秒前
蔡徐坤完成签到,获得积分10
32秒前
38秒前
40秒前
大熊发布了新的文献求助30
41秒前
贪玩的秋柔应助smy采纳,获得10
41秒前
张菲菲发布了新的文献求助10
42秒前
42秒前
44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
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Mass participant sport event brand associations: an analysis of two event categories 500
Photodetectors: From Ultraviolet to Infrared 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 6354689
求助须知:如何正确求助?哪些是违规求助? 8169797
关于积分的说明 17197939
捐赠科研通 5410637
什么是DOI,文献DOI怎么找? 2864105
邀请新用户注册赠送积分活动 1841625
关于科研通互助平台的介绍 1690050