Since the 1990s, health poverty has been officially adopted as an important agenda worldwide.35The Sustainable Development Goals (SDGs) clearly demonstrate that health protection policies should be developed for the most vulnerable populations.36In 2016, “Guiding Opinions on Implementing a Healthy Poverty Alleviation Project” clearly stated that the Health Poverty Alleviation Project was key to preventing IME.37
The rate of CHE for middle-aged elderly people in China (20.3%) was higher than in other low and middle income countries. Amaya-Lara found that,9.6 % of Colombian households had catastrophic expenditure.38In India, the incidence of catastrophic health expenditure for older people over 65 was only 7%, much lower than in China.39And in Iran,the rate of catastrophic health expenditure headcount ratio varied from 0.5% to 14.3% and from 0.48% to 13.27% for rural and urban households, respectively.40 The incidences of IME (7.4%) and CHE (20.5%) participating in medical insurance were 2.6% higher than those of uninsured households (4.8% and 17.9%). Our research also found that families with mental illness, elderly people > 75, inpatients, disabled, and chronic patients have a higher risk of falling into poverty due to medical expenses.
Against the background of population aging, the prevalence of chronic diseases, hospitalization rate, and disability due to illness increase the health needs of the elderly. However, the elderly is disadvantaged in the process of obtaining resources. Therefore, it is crucial to determine the risk characteristics of this important group with physiological, social, and health vulnerability and to maximize the effectiveness of the dividend effect of welfare policies. Through our comprehensive analysis, we find that the vulnerable middle-aged and elderly people population in China is characterized by the following characteristics:
Regional level: Inter-regional macroeconomics is not the main driver for reducing the risk of health poverty.
When the original poverty rate is at the same level, there is a tendency for IME to occur in the central and western regions due to the purchase of health services. The incidence of IME is significantly higher in the central and western regions than in the east, which is consistent with the distribution of poverty-stricken populations in China. Guo also demonstrated significant regional differences in the rural poverty-stricken groups and gradually gather in the central and western regions over time in China between 1978–2014.41
Inter-regional macroeconomics is not the main driver for reducing the risk of health poverty. For example, Shaanxi and Jiangsu belong to different regions but have the same poverty rate. In 2015, Shaanxi’s GDP was 180.218 billion-yuan, accounting for only a quarter of Jiangsu (70,116.38 billion yuan), but the incidence of IME (5.26%) was lower than in Jiangsu (6.13%).
Thus, the economic development-centered approach to regional poverty alleviation has not reached the maximum point of convergence with China’s current demand for health. Basu found that, in India, when poverty develops to a certain stage, the poverty reduction effect incurred by the increase in economic income would reduce under the influence of other specific factors (1951-1991).42 Our data can better explain that residents’ physiological characteristics and medical insurance impact a family’s IME and CHE more than the overall macroeconomic level. The indiscriminate poverty alleviation policy has reduced poverty in provinces and regions, but there are still differences in poverty caused by the use of health services.
Therefore, while paying attention to economic development and driving poverty alleviation, we should accurately target the characteristics of the poor, capture the poverty-reducing characteristics at the individual, family, and institutional levels, prioritize vulnerability, and improve the targeting accuracy of poverty alleviation policies for the poor.43
Individual Level: the superposition of multiple health vulnerabilities exacerbated the risk of poverty among middle-aged and elderly people.
High health service needs and utilization households with chronic disease and disability members, but with lower reimbursement ratio increase the difficulty for residents to obtain health rights. For example, the prevalence and hospitalization rates of respiratory disease patients were 17.4% and 16.7%, respectively, but the OOP proportion was as high as 46.7%, nearly 10% higher than for diabetic patients (37.1%). Callander calculated that Australian households with chronic disease (COPD) pay 109% more for care than those without health problems.44Middle-aged and elderly patients with chronic diseases will increase the demand and utilization of health services as the outpatient visit rate and hospitalization rate increase. If there is a low actual reimbursement ratio and a high proportion of OOP, it will inevitably lead to a catastrophic increase in health expenditure risk.This shows that, people with chronic diseases or low social status have a heavy burden of disease due to low co-payments or no compensation.45,46,47 Therefore, higher cost sharing is important for reducing the burden on residents.
The age of the head of household affects the incidence of IME. As the head of the household grows,the risk of IME increases by 1.83 percentage point. Thus, aging is one of the key factors hindering poverty reduction. Income inequality and reduced autonomy have increased the sensitivity of older groups to health rights and health equity.48 According to the Global Burden of Disease Study, 23% of the global burden of disease occurs in older people, and chronic non-communicable diseases have a major impact on this burden.49
Although the health vulnerability of the middle-aged and elderly people is often regarded as an intrinsic property, individuals can reduce their exposure to health rights by providing corresponding social support. More importantly, such support reduces barriers to entry for health services for the elderly, including raising the government’s high co-payments and deductibles, and strengthening the policy inclination of the elderly.50
Family Level: Families with low risk of mutual aid.
Family size is negatively correlated with incidence of IME,as the member of family grows, the risk of IME is reduced by 1.5 percentage points. Connie noted that family size is related to the number of individuals entering the labor market, and the two are negatively correlated. Once the family faces unemployment, it prolongs the poverty time and poverty rate.51
Medical insurance is less effective for low-income families. The proportion of OOP in poor households accounted for 21.5% of the household’s ability, which is 6% higher than the wealthiest households (15.1%). Furthermore, for every 1% increase in household income, the incidence of IME is reduced by 0.6%. Sujin Kim also found that after the implementation of medical insurance, the coefficient of change of the CHE rate in high-income groups (1.424) exceeded that in low-income groups (0.544); that is, the policy protection of low-income groups was less than that of high-income groups.52
The rural poor remain the key target group for poverty alleviation. The incidence of IME in rural areas (7.72%) is higher than in urban areas (5.39%). Living in the city reduces the rate of IME by 2.8%. The hospitalized reimbursement ratio of MIUE is 68.07%, while that of the NCMS is only 37.1%, accounting for only half of the MIUR (25.0%). Urban households with higher income levels are better able to withstand the burden of health expenditures. Ye Li used China’s fourth health service survey data to calculate that the CHE of MIUE and MIUR were 9.4% and 8.5% respectively, far lower than the NCMS (14.8%).53
Medical Insurance Level:The design of medical insurance lacks policy inclination for special populations.
Participating in medical insurance increased the risk of IME by 16.5 percentage points.The protective effect of the medical insurance system has been offset by the rapid rise in medical expenses,health-care needs and service utilization.It can be seen that the medical insurance system has not played a full protective role and is likely to increase the medical burden,other scholars have reached similar conclusions.Some scholars have found that under the 30% threshold for catastrophic medical expenditures, rural residents participating in basic medical insurance will increase the risk of catastrophic medical expenditures for families by 31.8%.54Wagstaff et al found that,insurance significantly increases the risks of catastrophic expenditures(at the 10% thresholds )by 42.2%.55To explore the failure of medical insurance, we analyzed the top five factors affecting different medical insurances and found that chronic patients, inpatients, disabled people, and people over 65 are the key populations in need of poverty alleviation. The specific reasons for failure are as follows:
- The medical insurance does not impose policy inclinations on the middle-aged and elderly people groups with high health service demand and utilization, but only reduces the access standards of this group.
According to our data, the overall hospitalization reimbursement ratio for the elderly over 45 years old is 49.7%, which is lower than the .European Commission(EU)’s standard for the reimbursement of major illnesses of not less than 60%.56 In the case of cancer patients, the hospitalization reimbursement ratio for cancer patients is only 57.4%. Goss calculated the cancer costs in different countries and found that the proportion of household expenses for patients in the US was only 20.9%, while in China it was as high as 78.8%.57 Because it is difficult to design access mechanisms for major diseases that cover all chronically ill patients with large medical expenses, MIUE and MIUR with higher income levels are also suffering from IME, and poverty is as high as 25%. Simultaneously, the difference in reimbursement ratio for chronic diseases caused by medical insurance introduces risks within the system, which makes the reimbursement of mental illness patients (53.9%) of MIUE nearly 28.4% lower than those with low-grade diabetes (81.5%). Some chronic drugs are not included in the reimbursement range, which increases patients’ OOP expenses. Meanwhile, the patient’s transportation expenses, nursing expenses, lost time, and preventive health care expenses are not within the scope of reimbursement, which greatly increases the household’s disease burden.
- The difference between the type and internal design of the medical insurance leads to a certain gap between different income groups. There is a lack of policy inclination for low-income groups, while high income groups have a more advantageous compensation level by medical insurance.
First, the difference between the medical insurances leads to different risks of IME. According to our data, the NCMS has a high incidence of IME, reaching 7.9%, approximately 2.42 times that of MIUE. Although medical insurance integration has been implemented in some places to alleviate the huge differences between groups, the incidence of IME is the highest (8.5%), at 0.6 percent higher than the NCMS. Therefore, it has not been possible for residents to achieve equal access to healthcare services. Su, Min reached the same conclusion.58 The fundamental reason for this lack of equality is the low financing level, combined with a reimbursement package that does not consider the traffic, economic level, and family-mutual aid capabilities.
Additionally, the internal system design of medical insurance lacks economic support for low-income families and protects the rich more. In our study, the sub-poor group had a hospitalization reimbursement ratio of only 42%, lower than the highest at 50.5%. A similar phenomenon occurred in India. With only government expenditure, the poorest households receive only 10% of medical care, while the wealthiest families receive up to 33% of social subsidies.59
- The medical insurance system has not yet transformed regional poverty alleviation into individual alleviation. Therefore, it fails to accurately target vulnerable groups, and there are weak links in the connection with the existing poverty alleviation related systems.
China’s health poverty alleviation system is a muti-path health protection system that integrates a basic medical insurance scheme, major illness insurance scheme, medical assistance scheme, and disease emergency assistance scheme. It aims to improve the health protection level of poverty-stricken areas and poor people. However, examining our results, chronic patients, the elderly, and other groups have increased the risk of IME after using health services. Thus, the health insurance still has a long way to go to improve health poverty alleviation. Firstly, since 7.4% of the middle-aged and elderly people are unable to enjoy health insurance rights, we should adhere to the basic guarantee function of the basic medical insurance for the over 45 age-group, and create a guarantee for vulnerable and poverty-stricken groups. Secondly, the poverty line should be changed before accurately measuring the poverty levels of different age-groups, incomes, and special needs through quantitative analysis methods. The government should improve the medical assistance policies for major diseases, and consider the poverty-stricken population and personal medical economic burden on the basis of main classification. Thirdly, the effective connection between the basic medical insurance scheme and major disease insurance scheme and medical assistance system should be strengthened. Participation in basic medical insurance should be enforced for the elderly over 65 years old, mental illness, cancer, diabetes, inpatients, and disabled people who are high-risk groups for IME. They should also participate voluntarily in the supplementary medical insurance for major illnesses. Insured persons who are hospitalized due to illness meet the scope of payment for the major illness supplementary medical insurance fund. Moreover, to provide reimbursement, a payment line should be established, with proportional segmentation, cumulative calculation, and the highest capping method.