Dataset Information

Interpretation of China's 2017 health expenditure: a latent profile analysis of panel data.

ABSTRACT:

Objective

To explore the latent structure of health financing and the institutional distribution of health expenditure (focused on hospital expenditure) in provinces, autonomous regions and municipalities of mainland China, and to examine how these profiles may be related to their externalising and internalising characteristics.

Study design

The study used panel data harvested from the China National Health Accounts Report 2018.

Methods

Mainland China's provincial data on health expenditure in 2017 was studied. A latent profile analysis was conducted to identify health financing and hospital health expenditure profiles in China. Additionally, rank-sum tests were used to understand the difference of socioeconomic indicators between subgroups.

Results

A best-fitting three-profile solution for per capita health financing was identified, with government health expenditure (?²=10.137, p=0.006) and social health expenditure (?²=6.899, p=0.032) varying significantly by profiles. Health expenditure in hospitals was subject to a two-profile solution with health expenditure flow to urban hospitals, county hospitals and community health service centres having significant differences between the two profiles (p<0.001).

Conclusions

Per capita health financing and health expenditure spent in hospitals have discrepant socioeconomic characteristics in different profiles, which may be attributed to macroeconomic factors and government policies. The study provided new and explicit ideas for health financing and health policy regulation in China.

SUBMITTER: Zang S

PROVIDER: S-EPMC7328737 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Interpretation of China's 2017 health expenditure: a latent profile analysis of panel data.

Zang Shuang S Zhao Meizhen M OuYang Jing J Wang Xin X

BMJ open 20200630 6

<h4>Objective</h4>To explore the latent structure of health financing and the institutional distribution of health expenditure (focused on hospital expenditure) in provinces, autonomous regions and municipalities of mainland China, and to examine how these profiles may be related to their externalising and internalising characteristics.<h4>Study design</h4>The study used panel data harvested from the China National Health Accounts Report 2018.<h4>Methods</h4>Mainland China's provincial data on h ...[more]

PMID: 32606058

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Project description:BackgroundCatastrophic health expenditures (CHE) are out-of-pocket payments (OOP) that exceed a predefined percentage or threshold of a household's resources, usually 40 %, that can push households into poverty in China. We analyzed the trends in the incidence and intensity, and explored the determinants, of CHE, and proposed policy recommendation to address CHE.MethodsA unique 5-year national urban-rural panel database was constructed from the China Family Panel Studies (CFPS) surveys. CHE incidence was measured by calculating headcount (percentage of households incurring CHE to the total household sample) and intensity was measured by overshoot (degree by which an average out of pocket health expenditure exceeds the threshold of the total sample). A linear probability model was employed to assess the trend in the net effect of the determinants of CHE incidence and a random effect logit model was used to analyse the role of the characteristics of the household head, the household and household health utilization on CHE incidence.ResultsCHE determinants vary across time and geographical location. From 2010 to 2018, the total, urban and rural CHE incidence all showed a decreasing tend, falling from 14.7 to 8.7 % for total households, 12.5-6.6 % in urban and 16.8-10.9 % in rural areas. CHE intensity decreased in rural (24.50-20.51 %) and urban (22.31-19.57 %) areas and for all households (23.61-20.15 %). Inpatient services were the most important determinant of the incidence of CHE. For urban households, the random effect logit model identified household head (age, education, self-rated health); household characteristics (members 65 + years, chronic diseases, family size and income status); and healthcare utilization (inpatient and outpatient usage) as determinants of CHE. For rural areas, the same variables were significant with the addition of household head's sex and health insurance.ConclusionsThe incidence and intensity of CHE in China displayed a downward trend, but was higher in rural than urban areas. Costs of inpatient service usage should be a key intervention strategy to address CHE. The policy implications include improving the economic level of poor households, reforming health insurance and reinforcing pre-payment hospital insurance methods.

Project description:INTRODUCTION:Although health expenditure in sub-Saharan African countries is the lowest compared with other regions in the world, most African countries have improved their budget allocations to health care over the past 15 years. The majority of health care sources in sub-Saharan Africa are private and largely involve out-of-pocket expenditure, which may prevent healthcare access. Access to healthcare is a known predictor of infant mortality. Therefore the objective of this study is to determine the impact of health care expenditure on infant mortality in sub-Saharan Africa. METHODS:The study used panel data from World Bank Development Indictors (WDI) from 2000 to 2015 covering 46 countries in sub-Saharan Africa. The random effects model was selected over the fixed effects model based on the Hausman test to assess the effect of health care expenditure on infant and neonatal mortality. RESULTS:Both public and external health care spending showed a significant negative association with infant and neonatal mortality. However, private health expenditure was not significantly associated with either infant or neonatal mortality. In this study, private expenditure includes funds from households, corporations and non-profit organizations. Public expenditure include domestic revenue as internal transfers and grants, transfers, subsidies to voluntary health insurance beneficiaries, non-profit institutions serving households or enterprise financing schemes as well as compulsory prepayment and social health insurance contributions. External health expenditure is composed of direct foreign transfers and foreign transfers distributed by government encompassing all financial inflows into the national health system from outside the country. CONCLUSION:Health care expenditure remains a crucial component of reducing infant and neonatal mortality in sub-Saharan African countries. In the region, where health infrastructure is largely underdeveloped, increasing health expenditure will contribute to progress towards reducing infant and neonatal mortality during the Sustainable Development Goals (SDGs) era. Therefore, governments in the region need to increase amounts allocated to health care service delivery in order to reduce infant mortality.

Project description:BackgroundMultimorbidity, the presence of two or more mental or physical chronic non-communicable diseases, is a major challenge for the health system in China, which faces unprecedented ageing of its population. Here we examined the distribution of physical multimorbidity in relation to socioeconomic status; the association between physical multimorbidity, health-care service use, and catastrophic health expenditures; and whether these associations varied by socioeconomic group and social health insurance schemes.MethodsIn this population-based, panel data analysis, we used data from three waves of the nationally representative China Health and Retirement Longitudinal Study (CHARLS) for 2011, 2013, and 2015. We included participants aged 50 years and older in 2015, who had complete follow-up for the three waves. We used 11 physical non-communicable diseases to measure physical multimorbidity and annual per-capita household consumption spending as a proxy for socioeconomic status.FindingsOf 17 708 participants in CHARLS, 11 817 were eligible for inclusion in our analysis. The median age of participants was 62 years (IQR 56-69) in 2015, and 5766 (48·8%) participants were male. 7320 (61·9%) eligible participants had physical multimorbidity in China in 2015. The prevalence of physical multimorbidity was increased with older age (odds ratio 2·93, 95% CI 2·71-3·15), among women (2·70, 2·04-3·57), within a higher socioeconomic group (for quartile 4 [highest group] 1·50, 1·24-1·82), and higher educational level (5·17, 3·02-8·83); however, physical multimorbidity was more common in poorer regions than in the more affluent regions. An additional chronic non-communicable disease was associated with an increase in the number of outpatient visits (incidence rate ratio 1·29, 95% CI 1·27-1·31), and number of days spent in hospital as an inpatient (1·38, 1·35-1·41). We saw similar effects in health service use of an additional chronic non-communicable disease in different socioeconomic groups and among those covered by different social health insurance programmes. Overall, physical multimorbidity was associated with a significantly increased likelihood of catastrophic health expenditure (for the overall population: odds ratio 1·29, 95% CI 1·26-1·32, adjusted for sociodemographic variables). The effect of physical multimorbidity on catastrophic health expenditures persisted even among the higher socioeconomic groups and across all health insurance programmes.InterpretationConcerted efforts are needed to reduce health inequalities that are due to physical multimorbidity, and its adverse economic effect in population groups in China. Social health insurance reforms must place emphasis on reducing out-of-pocket spending for patients with multimorbidity to provide greater financial risk protection.FundingNone.

Project description:ObjectivesTo examine non-communicable diseases (NCDs) multimorbidity level and its relation to households' socioeconomic characteristics, health service use, catastrophic health expenditures and productivity loss.DesignThis study used panel data of the Indonesian Family Life Survey conducted in 2007 (Wave 4) and 2014 (Wave 5).SettingThe original sampling frame was based on 13 out of 27 provinces in 1993, representing 83% of the Indonesian population.ParticipantsWe included respondents aged 50 years and above in 2007, excluding those who did not participate in both Waves 4 and 5. The total number of participants in this study are 3678 respondents.Primary outcome measuresWe examined three main outcomes; health service use (outpatient and inpatient care), financial burden (catastrophic health expenditure) and productivity loss (labour participation, days primary activity missed, days confined in bed). We applied multilevel mixed-effects regression models to assess the associations between NCD multimorbidity and outcome variables, RESULTS: Women were more likely to have NCD multimorbidity than men and the prevalence of NCD multimorbidity increased with higher socioeconomic status. NCD multimorbidity was associated with a higher number of outpatient visits (compared with those without NCD, incidence rate ratio (IRR) 4.25, 95% CI 3.33 to 5.42 for individuals with >3 NCDs) and inpatient visits (IRR 3.68, 95% CI 2.21 to 6.12 for individuals with >3 NCDs). NCD multimorbidity was also associated with a greater likelihood of experiencing catastrophic health expenditure (for >3 NCDs, adjusted OR (aOR) 1.69, 95% CI 1.02 to 2.81) and lower participation in the labour force (aOR 0.23, 95% CI 0.16 to 0.33) compared with no NCD.ConclusionsNCD multimorbidity is associated with substantial direct and indirect costs to individuals, households and the wider society. Our study highlights the importance of preparing health systems for addressing the burden of multimorbidity in low-income and middle-income countries.

Dataset Information

Interpretation of China's 2017 health expenditure: a latent profile analysis of panel data.

Objective

Study design

Methods

Results

Conclusions

Publications

Interpretation of China's 2017 health expenditure: a latent profile analysis of panel data.

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