The effects of ageing population on health expenditure and economic growth in China: A Bayesian-VAR approach

Wang

2021

Front. Public Health

This paper discusses the impact of air pollution on medical expenditure in eastern, central, and western China by applying the fixed-effect model, random-effect model, and panel threshold regression model. According to theoretical and empirical analyses, there are different relationships between the two indexes in different regions of China. For eastern and central regions, it is obvious that the more serious the air pollution is, the more medical expenses there are. However, there is a non-linear single threshold effect between air pollution and health care expenditure in the western region. When air pollution is lower than this value, there is a negative correlation between them. Conversely, the health care expenditure increases with the aggravation of air pollution, but the added value is not enough to make up for the health problems caused by air pollution. The empirical results are basically consistent with the theoretical analysis, which can provide enlightenment for the government to consider the role of air pollution in medical expenditure. Policymakers should arrange the medical budget reasonably, according to its situation, to make up for the loss caused by air pollution.

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Does Industrial Air Pollution Increase Health Care Expenditure? Evidence From China

Wang

2021

Front. Public Health

“…An estimate of the CET of a QALY provides a rationale for scientifically rigorous healthcare decision-making [17]. In light of this, it is recommended for each country to develop its own CET to enable the alignment of clinical and economic value with the efficiency frontier under a fixed budget within each healthcare system [18], which is of fundamental importance for China that is facing increasing pressure of healthcare expenditure [19].…”

Section: Introductionmentioning

confidence: 99%

Estimation of the cost-effective threshold of a quality-adjusted life year in China based on the value of statistical life

et al. 2021

Cost-effective threshold (CET) is essential for health technology assessment and decision-making based on health economic evaluations. Recently, it has been argued that the commonly used once and three times of gross domestic product (GDP) per capita CETs of a quality-adjusted life year (QALY) are not necessarily empirically supported in all countries. Therefore, we aimed to estimate the CET of a QALY as times of GDP per capita in China, of which the reimbursement coverage decisions are increasingly engaging economic evaluations. Estimates on the value of statistical life (VSL) in China were identified from several studies in the literature and converted to times of GDP per capita, the weighted average of which was used for subsequent calculation. By pooling data on population mortality, health utility, and age distribution, we estimated the value of a statistical QALY (VSQ) from VSL using an established mathematical process, which represented the theoretical upper bound of CET. The corresponding point estimate and theoretical lower bound were obtained using their numerical relationships with the upper bound. Scenarios analyses were also conducted. The estimated CET, its upper bound, and its lower bound were 1.45, 2.90, and 1.16 times of GDP per capita in China, respectively. In different scenarios, the estimated CET varied but was greater than once GDP per capita in most cases. As such, the CET of a QALY in China is close to 1.5 times of GDP per capita, which should be benchmarked for future ICER-based coverage decisions.

“…Judging from the development trajectory of most countries with ageing populations, continued population ageing will profoundly change the economy, society, and medical insurance system [3][4][5]. Along with the rapid ageing of the population, the medical needs of the elderly population are increasing [6]. According to the Statistical Yearbook of China's Health and Family Planning 2019, in 2013, the gap between the two-week consultation rate and hospitalization rate of elderly people aged 65 and above in the surveyed areas and those aged 15-34 was as high as 6-8 times, and this gap is still on the rise.…”

Section: Introductionmentioning

confidence: 99%

The effect of the universal two-child policy on medical insurance funds with a rapidly ageing population: evidence from China’s urban and rural residents’ medical insurance

2021

Background With the rapid growth of the ageing population, the operating burden of China’s basic medical insurance fund is becoming increasingly heavy. To counter rapid population ageing and ameliorate a series of problems, China has adjusted its fertility policies several times. On January 1, 2016, the universal two-child policy was implemented. This study analysed the impacts of the adjustment to the fertility policy and potential improvements in fertility intention on the insured population and medical insurance fund sustainability. Methods We used an actuarial science method and took the urban and rural residents’ basic medical insurance (URRBMI) of China, which covers most urban and rural residents, as an example to build a dynamic forecast model of population growth and a dynamic actuarial model of medical insurance funds. Results Compared with the original policy, under the current fertility intention (40%) with the universal two-child policy, the ageing of the population structure of URRBMI participants will decline significantly after 2026, and individuals aged 65 and over will account for only 19.01% of the total participants in 2050. The occurrence of the current deficit and accumulated deficit of the URRBMI fund will be postponed for one year to 2022 and 2028, respectively. If fertility intentions continue to rise, the ageing degree of the population structure will decrease, and the deficit would be further delayed. Conclusions The universal two-child policy is conducive to improving the degree of overall population ageing, delaying the occurrence of a URRBMI fund deficit, and improving the sustainability of URRBMI funds. If fertility intention increases, the effects would be stronger. However, since the adjustment of the universal two-child policy has a certain time lag, it will take time to demonstrate this impact. Therefore, while actively promoting the universal two-child policy, other measures should be taken, such as improving the fertility desire among couples of childbearing age and reforming medical insurance payment methods.