Inequality of opportunity in healthcare expenditures: evidence from China

Will urban scale affect health services inequity? The empirical evidence from cities in China

Background

The equity of public resources triggered by city shrinkage is a global challenge. Significantly, the impact of city shrinkage on the allocation of health service resources needs to be better understood. This study explores the impact of population change on government investment and health service delivery in shrinking cities.

Data and method

Using data from China's Urban Statistical Yearbook (2010-2020), we employ regression discontinuity (RD) and fixed-effect models to examine the causal relationship between city shrinkage and health service provision.

Result

Shrinking cities show significant disparities in health resources, particularly in bed numbers (-1,167.58, p < 0.05) and doctor availability (-538.54, p < 0.05). Economic development (p < 0.01) and financial autonomy (p < 0.01) influence hospital bed distribution. Investments in public services (primary schools and teachers, p < 0.01) affect health resource delivery. Robustness tests support our results.

Conclusion

This study reveals how city shrinkage disrupts health service provision and equity, establishing a causal relationship between city shrinkage/expansion and health resource allocation, emphasizing the imbalance caused by urban population changes. City expansion intensifies competition for health resources, while shrinking cities struggle to provide adequate resources due to government reluctance. Policymakers should adapt health resource allocation strategies to meet patient demands in changing urban landscapes.

Enhancing pooling levels strengthens the risk resilience of healthcare insurance: a case study of basic medical insurance fund operations data in Gansu, China

BACKGROUND

In China, enhancing the pooling levels of basic health insurance has consistently been regarded as a pivotal measure to promote the refinement of the healthcare insurance system. From 2020 to 2022, the widespread outbreak of COVID-19 posed new challenges to China's basic health insurance.

METHODS

The research utilizes Data Envelopment Analysis (DEA), Malmquist index assessment, and fixed-effects panel Tobit models to analyze panel data from 2020 to 2022, assessing the efficiency of basic health insurance in Gansu Province.

RESULTS

From 2020 to 2022, the average overall efficiency of the municipal pooling of Basic Medical Insurance for Urban and Rural Residents was 0.941, demonstrating a stable trend with a modest increase. The efficiency frontier regions have expanded from 5 (35.71%) to 7 (50%). Operational efficiency exhibited a negative correlation with per capita hospitalization expenses and per capita fund balance but a positive correlation with per capita accumulated fund balance and reimbursement rates for hospitalized patients. In 2021, compared to 2020, the county-pooling Basic Medical Insurance for Urban Employees saw a decline of 0.126 in overall efficiency, reducing the efficiency frontier regions from 8 to 3. However, from 2021 to 2022, the municipal-coordinated Basic Medical Insurance for Urban Employees experienced a 0.069 increase in overall efficiency, with the efficiency frontier regions expanding from 3 to 5. Throughout 2020 to 2022, the operational efficiency of the Urban Employee Basic Medical Insurance showed a consistent negative correlation with per capita fund balance.

CONCLUSION

From 2020 to 2022, the overall operational performance of basic health insurance in Gansu Province was satisfactory, and enhancing the pooling level is beneficial in addressing the impact of unforeseen events on the health insurance system.

Direct and indirect costs for families of children with autism spectrum disorder in China

LAY ABSTRACT

This is the first comprehensive national study to explore the direct and indirect costs for families of children with autism spectrum disorder in China. The increasing prevalence of autism spectrum disorder highlights a growing need for resources to provide care for families of children with autism spectrum disorder. The medical and nonmedical costs and parents' productivity loss have caused a serious burden on their families. Our objective is to estimate the direct and indirect costs for the families of children with autism spectrum disorder in China. The target population was parents of children with autism spectrum disorder. We analyzed the costs using cross-sectional data from a Chinese national family survey with children aged 2-6 years (N = 3236) who were clinically diagnosed with autism spectrum disorder. Family data from 30 provinces in China were obtained. Cost items included direct medical costs, direct nonmedical costs, and indirect costs. In this study, we found that the largest part of family costs for autism spectrum disorder are nonmedical costs and productivity loss. Autism spectrum disorder has imposed a huge economic burden on parents having children with autism spectrum disorder in China, who need more support than the current health care system provides.

Inequality of opportunity in outpatient expenditure among the elderly with multimorbidity: evidence from China

BACKGROUND

Inequality of opportunity (IOp) stemming from social circumstances exists in outpatient service utilization for the multimorbid elderly in China. However, little is known regarding the magnitude of the IOp and its composition. Therefore, this study aims to measure the IOp in outpatient expenditure and provide potential pathways for policy reform by assessing the contribution of each circumstance.

METHODS

This study included 3527 elderly aged ≥ 65 years with multimorbidity from the Chinese Longitudinal Healthy Longevity Study conducted in 2017-2018. An ordinary least squares regression model was used to analyze the circumstance-influencing factors of outpatient expenditure. The parametric approach was performed to quantify the IOp in outpatient expenditure and the Shapley value decomposition method was employed to determine the contribution of each circumstance. By extracting heterogeneity in the residual of the circumstance-dependent equation of outpatient expenditure across circumstance groups divided based on cluster analysis, we captured the effect of unobserved circumstances.

RESULTS

Except for pension and distance to health facilities, all the associations between circumstance and outpatient expenditure were statistically significant. The inequality caused by circumstances accounted for 25.18% of the total inequality. The decomposition results revealed that the reimbursement rate contributed 82.92% of the IOp, followed by education duration (4.55%), household registration (3.21%), household income (3.18%), pension (1.49%), medical insurance (1.26%), physical labor (0.99%), unobserved circumstances (0.86%), distance to health facilities (0.83%) and region (0.71%).

CONCLUSIONS

The priority of policy enhancement is to effectively improve the outpatient reimbursement benefit for treating chronic diseases. Additional crucial actions include enhancing the health literacy of the multimorbid elderly to promote the shift from medical needs to demands and accelerating the construction of rural capacity for providing high-quality healthcare to the elderly with multimorbidity.

A generalized deep learning model for heart failure diagnosis using dynamic and static ultrasound

Objective

Echocardiography (ECG) is the most common method used to diagnose heart failure (HF). However, its accuracy relies on the experience of the operator. Additionally, the video format of the data makes it challenging for patients to bring them to referrals and reexaminations. Therefore, this study used a deep learning approach to assist physicians in assessing cardiac function to promote the standardization of echocardiographic findings and compatibility of dynamic and static ultrasound data.

Methods

A deep spatio-temporal convolutional model r2plus1d-Pan (trained on dynamic data and applied to static data) was improved and trained using the idea of "regression training combined with classification application," which can be generalized to dynamic ECG and static cardiac ultrasound views to identify HF with a reduced ejection fraction (EF < 40%). Additionally, three independent datasets containing 8976 cardiac ultrasound views and 10085 cardiac ultrasound videos were established. Subsequently, a multinational, multi-center dataset of EF was labeled. Furthermore, model training and independent validation were performed. Finally, 15 registered ultrasonographers and cardiologists with different working years in three regional hospitals specialized in cardiovascular disease were recruited to compare the results.

Results

The proposed deep spatio-temporal convolutional model achieved an area under the receiveroperating characteristic curve (AUC) value of 0.95 (95% confidence interval [CI]: 0.947 to 0.953) on the training set of dynamic ultrasound data and an AUC of 1 (95% CI, 1 to 1) on the independent validation set. Subsequently, the model was applied to the static cardiac ultrasound view (validation set) with simultaneous input of 1, 2, 4, and 8 images of the same heart, with classification accuracies of 85%, 81%, 93%, and 92%, respectively. On the static data, the classification accuracy of the artificial intelligence (AI) model was comparable with the best performance of ultrasonographers and cardiologists with more than 3 working years (P = 0.344), but significantly better than the median level (P = 0.0000008).

Conclusion

A new deep spatio-temporal convolution model was constructed to identify patients with HF with reduced EF accurately (< 40%) using dynamic and static cardiac ultrasound images. The model outperformed the diagnostic performance of most senior specialists. This may be the first HF-related AI diagnostic model compatible with multi-dimensional cardiac ultrasound data, and may thereby contribute to the improvement of HF diagnosis. Additionally, the model enables patients to carry "on-the-go" static ultrasound reports for referral and reexamination, thus saving healthcare resources.

Inequality of opportunity in health service utilization among middle-aged and elderly community-dwelling adults in China

BACKGROUND

The inequality caused by circumstances is known as "inequality of opportunity" (IOp). Many scholars have studied IOp in the health field, but few studies have quantified contributors to the IOp of health service utilization among middle-aged and elderly people. This study measured the IOp of health service utilization and decomposed the contributors to IOp present among Chinese middle-aged and elderly people.

METHODS

Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) in 2013, 2015 and 2018. A mean-based regression method was adopted to measure the IOp of health service utilization. Shapley-Shorrocks decomposition was used to analyze the main contributors to IOp seen among the middle-aged and elderly.

RESULTS

Although the absolute IOp of health service utilization decreased over time, IOp still explains the total inequality to a large extent. The absolute IOp and relative IOp were greatest in the areas of self-treatment and inpatient care utilization, respectively. Shapley decomposition results showed that the out-of-pocket (OOP) ratio contributed most to the IOp of outpatient care utilization; and the residence area highly explains the IOp of inpatient service utilization. Meanwhile, social and economic factors such as work status and income contribute more to the IOp of inpatient care utilization than outpatient and self-treatment.

CONCLUSIONS

Strategies aimed at achieving equal opportunities remain necessary to ensure the fairness of health service utilization. Policies and measures should further adjust the medical insurance compensation policies, and pay more attention to the middle-aged and elderly residents in rural areas, optimize health resource allocation, improve the social security systems, and narrow the socioeconomic gap between urban and rural areas in China.

Place of death and phenomenon of going home to die in Chinese adults: A prospective cohort study

BACKGROUND

China is embracing an ageing population without sustainable end-of-life care services. However, changes in place of death and trends of going home to die (GHTD) from the hospital remains unknown.

METHODS

A total of 42,956 participants from the China Kadoorie Biobank, a large Chinese cohort, who died between 2009 and 2017 was included into analysis. GHTD was defined as death at home within 7 days after discharge from the hospital. A modified Poisson regression was used to investigate temporal trends of the place of death and GHTD, and estimate prevalence ratios (PRs) and 95% confidence intervals (CIs) for the association of GHTD with health insurance (HI) schemes.

FINDINGS

From 2009 to 2017, home remained the most common place of death (71·5%), followed by the hospital (21·6%). The proportion of GHTD for Urban and Rural Residents' Basic Medical Insurance (URRBMI) beneficiaries was around six times higher than that for Urban Employee Basic Medical Insurance (UEBMI) beneficiaries (66·0% vs 11·6%). Besides, a substantial increase in the proportion of GHTD throughout the study period was observed regardless of HI schemes (4·4% annually for URRBMI, and 5·4% for UEBMI). Compared with UEBMI beneficiaries, URRBMI beneficiaries were more likely to experience GHTD, with an adjusted PR (95% CI) of 1·19 (95% CI: 1·12, 1·27) (P<0·001).

INTERPRETATION

In China, most of deaths occurred at home, with a large proportion of decedents GHTD from the hospital, especially for URRBMI beneficiaries. Substantial variation in the phenomenon of GHTD across HI schemes indicates inequalities in end-of-life care utilization.

FUNDING

The National Natural Science Foundation of China, the Kadoorie Charitable Foundation, the National Key R&D Program of China, the Chinese Ministry of Science and Technology.

The intervention dilemma and high burden of children with autism in Guizhou province, Southwest China

BACKGROUND

Autism spectrum disorder (ASD) is a highly disabling neurodevelopmental disorder, and the burden is high. Data on the burden of ASD are limited in China, especially in the southwest. Therefore, the aims of this study were to investigate the intervention status and burden of children with ASD in Southwest China.

MATERIALS AND METHODS

Families of children with ASD were recruited from hospitals, special education schools, and private rehabilitation centers; they participated in the survey and completed the questionnaire. Descriptive analysis was conducted on the questionnaire results, which included basic demographic characteristics, rehabilitation status, and burden. Multivariate analysis was used to analyze the association of basic family demographic characteristics, rehabilitation status, and costs of ASD.

RESULTS

A total of 231 families of children with ASD participated in this survey, and 78.35% (181/231) of the children with ASD were male. The mean age was 4.34 ± 2.09 years. A total of 55.84% (129/231) of the children with ASD had an intellectual disability. Only 46.32% (107/231) started receiving intervention within 1 month after diagnosis. The institutions for rehabilitation interventions for children with ASD were mainly tertiary hospitals (39.39%), special education schools (29.87%) and private rehabilitation institutions (21.64%). For a total of 42.86% (99/231) of the children with ASD, the duration of the intervention was less than 10 h per week. A total of 74.89% (173/231) of the children with ASD received a rehabilitation intervention at home. A total of 66.67% of the parents were satisfied with the treatment. The monthly cost of medical intervention for the patients of children with autism was 7,225 ± 474 RMB ($1,134 ± 74), and the non-medical intervention cost was 2,133 ± 107 RMB ($334 ± 17). The annual burden of patients with autism was 86,700 ± 5,688 RMB ($13,596 ± 892). The estimated total annual burden of ASD was 5.548 billion RMB ($870 million) in Guizhou province.

CONCLUSION

The results revealed that rehabilitation resources are limited and that the burden of ASD is high in Guizhou province; therefore, improving the rehabilitation status and easing the burden of children with ASD is urgent in these regions.

From conventional healthcare to e-health: Social and spatial transformation. Using a comparison between Hong Kong and Mainland China

BACKGROUND AND AIM

Does spatial organization of healthcare access still matter in China? I assess how e-health has transformed the notion of healthcare access and what spatial dimension of healthcare means in China today and in the near future. I also consider a dynamic perspective to propose keys to anticipate upcoming changes. Hong Kong has a very efficient healthcare system with a dense network of high-level hospitals and a high level of healthcare access. In major Chinese urban centers, a deliberate policy to improve healthcare availability has resulted in a spectacular increase in the number of healthcare structures over the last two decades. This includes urban healthcare centers and outpatient clinics. Nevertheless, the most of the population faces explicit and implicit financial penalties to get full healthcare access. To solve the problem, a digital health revolution is emerging.

METHODS

I use a qualitative case study approach. I conducted a series of semi-structured, face-to-face interviews to evaluate experiences, expectations, and opinions of patients regarding healthcare access and its associated financial burden as well as their use of digital health.

RESULTS

I assessed how e-health has transformed the notion of healthcare access and what spatial dimension of healthcare means today and in the near future in China. I also considered a dynamic perspective to propose keys to anticipate upcoming changes. Healthcare centers tend to shift from a place to get cured to a link within an e-healthcare pathway. For instance, this is a place to get e-prescribed medication. Advantages of this shift include a reduction in the cost of healthcare and remote access to highly qualified medical staff, bypassing the lack of trust in the quality of care offered in local hospitals.

CONCLUSION

A forward-looking approach suggests that e-healthcare is becoming the entry point to healthcare for a large part of the population.

RELEVANCE TO PATIENTS

This study informs the policy makers of upcoming changes, and contributes to understanding and anticipating modifications needed in the healthcare system.

Private Healthcare Expenditure in China: A Regional Comparative Analysis

Private (out-of-pocket) healthcare expenditure (PHCE) is a complex phenomenon that is shaped by many different factors. In this paper, we analyzed the influencing factors of PHCE in China, with a specific focus on regional differences. We found that old-age dependency ratio, income, and education have significant impacts on PHCE in all regions, whereas public HCE, number of beds in medical institutions, and economic development levels have significant impacts only in some regions. The results indicate that the government should pay attention to regional inequality and implement targeted adjustments for improving the health service system. In particular, we recommend: (1) monitoring regional inequality in PHCE and other healthcare issues to unmask geographical differences in healthcare interventions; (2) adopting regional-specific policy measures—the government should divert some resources from eastern to western and central regions to increasing the support for public health undertakings and improve the quality of the local health services while providing matching medical resources by targeting the needs of the residents; (3) paying more attention to the healthcare demand of the elderly population; and (4) improving the education level of residents to improve public health and avoid high PHCE.