Research on Financing Mechanism of Long-Term Care Insurance in Xiamen, China: A System Dynamics Simulation

Life expectancy, long-term care demand and dynamic financing mechanism simulation: an empirical study of Zhejiang Pilot, China

BACKGROUND

China has piloted Long-Term Care Insurance (LTCI) to address increasing care demand. However, many cities neglected adjusting LTCI premiums since the pilot, risking the long-term sustainability of LTCI. Therefore, using Zhejiang Province as a case, this study simulated mortality-adjusted long-term care demand and the balance of LTCI funds through dynamic financing mechanism under diverse life expectancy and disability scenarios.

METHODS

Three-parameter log-quadratic model was used to estimate the mortality from 1990 to 2020. Mortality with predicted interval from 2020 to 2080 was projected by Lee-Carter method extended with rotation. Cohort-component projection model was used to simulate the number of older population with different degrees of disability. Disability data of the older people is sourced from China Health and Retirement Longitudinal Study 2018. The balance of LTCI fund was simulated by dynamic financing actuarial model.

RESULTS

Life expectancy of Zhejiang for male (female) is from 80.46 (84.66) years in 2020 to 89.39 [86.61, 91.74] (91.24 [88.90, 93.25]) years in 2080. The number of long-term care demand with severe disability in Zhejiang demonstrates an increasing trend from 285 [276, 295] thousand in 2023 to 1027 [634, 1657] thousand in 2080 under predicted mean of life expectancy. LTCI fund in Zhejiang will become accumulated surplus from 2024 to 2080 when annual premium growth rate is 5.25% [4.20%, 6.25%] under various disability scenarios, which is much higher than the annual growth of unit cost of long-term care services (2.25%). The accumulated balance of LTCI fund is sensitive with life expectancy.

CONCLUSIONS

Dynamic growth of LTCI premium is essential in dealing with current deficit around 2050 and realizing Zhejiang's LTCI sustainability in the long-run. The importance of dynamic monitoring disability and mortality information is emphasized to respond immediately to the increase of premiums. LTCI should strike a balance between expanding coverage and controlling financing scale. This study provides implications for developing countries to establish or pilot LTCI schemes.

Growing old in China in socioeconomic and epidemiological context: systematic review of social care policy for older people

BACKGROUND

From 2020 to 2050, China's population aged ≥65 years old is estimated to more than double from 172 million (12·0%) to 366 million (26·0%). Some 10 million have Alzheimer's disease and related dementias, to approach 40 million by 2050. Critically, the population is ageing fast while China is still a middle-income country.

METHODS

Using official and population-level statistics, we summarise China's demographic and epidemiological trends relevant to ageing and health from 1970 to present, before examining key determinants of China's improving population health in a socioecological framework. We then explore how China is responding to the care needs of its older population by carrying out a systematic review to answer the question: 'what are the key policy challenges to China achieving an equitable nationwide long-term care system for older people?'. Databases were screened for records published between 1st June 2020 and 1st June 2022 in Mandarin Chinese or English, reflecting our focus on evidence published since introduction of China's second long-term care insurance pilot phase in 2020.

RESULTS

Rapid economic development and improved access to education has led to widescale internal migration. Changing fertility policies and household structures also pose considerable challenges to the traditional family care model. To deal with increasing need, China has piloted 49 alternative long-term care insurance systems. Our findings from 42 studies (n = 16 in Mandarin) highlight significant challenges in the provision of quality and quantity of care which suits the preference of users, varying eligibility for long-term care insurance and an inequitable distribution of cost burden. Key recommendations include increasing salaries to attract and retain staff, introduction of mandatory financial contributions from employees and a unified standard of disability with regular assessment. Strengthening support for family caregivers and improving smart old age care capacity can also support preferences to age at home.

CONCLUSIONS

China has yet to establish a sustainable funding mechanism, standardised eligibility criteria and a high-quality service delivery system. Its long-term care insurance pilot studies provide useful lessons for other middle-income countries facing similar challenges in terms of meeting the long-term care needs of their rapidly growing older populations.

Research on the optimization of financing scheme of long-term care insurance in China based on system dynamics simulation

Objective

The aging population in China highlights the significance of long-term care insurance (LTCI). This study provides policy suggestions for China to establish a sustainable LTCI financing mechanism by predicting the trend of funds balance and screening the appropriate financing scheme.

Method

A system dynamics model (SDM) of LTCI funds was constructed by clarifying the current situation and its main influencing factors of revenue and expenditure of LTCI funds in China. Also, through literature research and expert consultation, we found the intervention goals and predicted the changing trend of LTCI fund balance from 2020 to 2050 under different intervention schemes.

Results

The SDM of LTCI financing passes the dimensional consistency test, structural test, and historical test. Therefore, it can objectively reflect the structure and behavior of the financing system. It is found that the factors affecting the revenue and expenditure system of LTCI funds mainly include economic factors, demographic factors, and other factors. By adjusting three intervention indicators, namely, individual payment rate, reimbursement proportion, and severe disability rate, this study produces 45 financing combination schemes. By comparing the changing trend of LTCI fund balance under different intervention schemes, according to the screening principle, five better financing schemes are finally selected. These five financing schemes have no deficit and excessive balance in the forecast period, which is in line with the principle of sustainability. It can provide a reference for the selection of financing schemes in pilot areas.

Discussion

This study has optimized the policy of the LTCI financing mechanism, determined the suitable LTCI participants, financing channels and levels, and screened out the suitable LTCI financing policy optimization scheme for China. By appropriately increasing the individual payment rate, strengthening the disability intervention of the elderly, formulating scientific and objective disability evaluation standards, and finally establishing a dynamic financing adjustment mechanism of LTCI. This study can provide a basis for the scientific formulation of the LTCI financing mechanism in China and provide a reference for developing countries to establish a sustainable LTCI.

Identifying the Service Capability of Long-Term Care Facilities in China: An e-Delphi Study

Objective

This study develops a group of service capability indicators for long-term care facilities to assess their current conditions and makes it the first step toward the improvement of service capability in China.

Methods

We constructed an initial indicator framework based on the characteristics of long-term care services and a literature review. Potential indicators were collected, and a 2-round modified web-based Delphi process was conducted by a national multidisciplinary expert panel to construct a service capability evaluation index system. The accepted competencies of indicators were established with mean scores in all three scoring criteria (importance, feasibility, and sensitivity) ≥ 4.0, consensus rate reached 70.0%, and a coefficient of variation ≤ 0.25.

Results

A new indicator framework covering 2 dimensions of inputs and activities was developed in this study. The initial 35 indicators formed an indicator pool for the Delphi questionnaire. According to the final consensus of the expert panel, the Delphi consultation resulted in an index system comprised 31 tertiary indicators across six subdimensions (i) staffing; (ii) facilities and equipment; (iii) funding; (iv) medical inspection services; (v) health management services; (vi) institutional standard management.

Conclusion

This study developed a set of indicators suitable for the long-term care system in China and is expected to be applied to measure and improve the service capability of long-term care facilities. In addition, these indicators can be used for comparisons between different LTCFs and provide an evidence basis for the further development of capability assessment tools.