The healthcare inequality among middle-aged and older adults in China: a comparative analysis between the full samples and the homogeneous population

Exploring unmet healthcare needs and associated inequalities among middle-aged and older adults in Eastern China during the progression toward universal health coverage

BACKGROUND

Given the rapid population aging in China, achieving universal health coverage (UHC) presents a primary challenge in addressing unmet healthcare needs and associated inequalities among middle-aged and older adults. Several studies have focused on healthcare utilization and its inequalities, but little attention has been paid to the inequality in unmet healthcare needs. This study aimed to analyze the inequalities in unmet the healthcare needs of middle-aged and older adults in eastern China during the progression toward UHC.

METHODS

Data were obtained from the fourth, fifth, and sixth National Health Service Survey (NHSS) of Jiangsu Province, located in eastern China, during the years 2008, 2013, and 2018, respectively. Logistic regression models were used to assess the associated factors of unmet healthcare needs. The inequality was measured according to the concentration index (CI) and its decomposition.

RESULTS

In this study, we found that 12.86%, 2.22%, and 48.89% of middle-aged and older adults reported unmet needs for outpatient and inpatient services and physical examinations, respectively. The prevalence of unmet outpatient needs increased from 2008 to 2018, while the prevalence of unmet inpatient services was lower but maintained. The prevalence of unmet needs for physical examinations among middle-aged and older adults markedly decreased since 2008. Rural areas had a higher prevalence of unmet needs for inpatient services and physical examinations than urban areas. Unmet healthcare needs were more prevalent among the poor. The pro-poor inequalities of unmet healthcare needs have been mitigated during the progression toward UHC; however, they remain predominant among rural middle-aged and older adults for outpatient and inpatient services. Socioeconomic factors significantly influenced unmet healthcare needs and contributed to their inequalities.

CONCLUSIONS

The findings characterize the prevalence and inequality of unmet healthcare need among middle-aged and older adults in eastern China during the progression toward UHC. Policy interventions should be actively advocated to effectively mitigate the unmet healthcare needs and address the associated inequalities.

Healthcare utilization and its association with socioeconomic status in China: Evidence from the 2011-2018 China Health and Retirement Longitudinal Study

INTRODUCTION

Healthcare utilization often favors the higher-socioeconomic status (SES) and having chronic diseases may exacerbate this inequality. This study aims to examine the trends in health service use over time, the effect of SES on healthcare utilization, and the role of chronic diseases in this association.

METHODS

Data used in this study were from the China Health and Retirement Longitudinal Study (CHARLS) in 2011, 2013, 2015, and 2018, which is the first nationally representative survey of the middle-aged and older. The sample included people aged 45 years and older who responded to all the waves. A total of 10,922 adults were included in this study. Healthcare utilization was categorized into outpatient and inpatient service use and SES was measured by per-capita household expenditure. A multilevel zero-inflated negative binomial regression model was performed to analyze outpatient and inpatient service use, separately.

RESULTS

The rates of outpatient service use in 2011, 2013, 2015, and 2018 were 19.11%, 21.45%, 20.12%, and 16.32%, respectively, while the rates of inpatient service use were 8.40%, 13.04%, 14.17%, and 18.79%, respectively. Compared to individuals in the lowest quintile of per-capita household expenditure, those in higher quintiles had higher odds of outpatient service use (Q2: odds ratio = 1.233, p < 0.0001; Q3: 1.416, p < 0.0001; Q4: 1.408, p < 0.0001; or Q5: 1.439, p < 0.0001) and higher rates of inpatient service use (Q2: incidence rate ratio = 1.273, p < 0.0001; Q3: 1.773, p < 0.0001; Q4: 2.071, p < 0.0001; or Q5: 1.992, p < 0.0001). Additionally, having morbidity generally increased healthcare utilization, but did not play a significant role in moderating the relationship between SES and healthcare utilization.

CONCLUSIONS

Healthcare utilization rates were overall low in China, but relatively high for people in higher quintiles of per-capita household expenditure or those with morbidity, compared to their counterparts. Policy actions are required to provide more health education to the public, to further optimize health insurance schemes targeting outpatient services, especially for the low-SES, and to establish new health delivery models for NCD management in the primary health care setting.

Effects of Urban and Rural Resident Basic Medical Insurance on Healthcare Utilization Inequality in China

Objectives: This study aims to evaluate the effects of Urban and Rural Resident Basic Medical Insurance (URRBMI) integration on healthcare utilization and explore the contribution of URRBMI to healthcare utilization inequality among middle-aged and older adults. Methods: Using data from the China Health and Retirement Longitudinal Study (CHARLS) 2011-2018. The difference-in-difference model, concentration index (CI), and decomposition method were adopted. Results: The results suggested that the probability of outpatient visits and the number of outpatient visits had decreased by 18.2% and 10.0% respectively, and the number of inpatient visits had increased by 3.6%. However, URRBMI had an insignificant effect on the probability of inpatient visits. A pro-poor inequality for the treatment group was observed. The decomposition revealed that the URRBMI contributed to the pro-poor inequality in healthcare utilization. Conclusion: The findings suggest that URRBMI integration has decreased outpatient care utilization and improved the number of inpatient visits. While the URRBMI has improved healthcare utilization inequality, some challenges still exist. Comprehensive measures should be taken in the future.

Clinical decision support system for quality of life among the elderly: an approach using artificial neural network

Background

Due to advancements in medicine and the elderly population’s growth with various disabilities, attention to QoL among this age group is crucial. Early prediction of the QoL among the elderly by multiple care providers leads to decreased physical and mental disorders and increased social and environmental participation among them by considering all factors affecting it. So far, it is not designed the prediction system for QoL in this regard. Therefore, this study aimed to develop the CDSS based on ANN as an ML technique by considering the physical, psychiatric, and social factors.

Methods

In this developmental and applied study, we investigated the 980 cases associated with pleasant and unpleasant elderlies QoL cases. We used the BLR and simple correlation coefficient methods to attain the essential factors affecting the QoL among the elderly. Then three BP configurations, including CF-BP, FF-BP, and E-BP, were compared to get the best model for predicting the QoL.

Results

Based on the BLR, the 13 factors were considered the best factors affecting the elderly’s QoL at P < 0.05. Comparing all ANN configurations showed that the CF-BP with the 13-16-1 structure with sensitivity = 0.95, specificity  =  0.97, accuracy = 0.96, F-Score = 0.96, PPV = 0.95, and NPV = 0.97 gained the best performance for QoL among the elderly.

Conclusion

The results of this study showed that the designed CDSS based on the CFBP could be considered an efficient tool for increasing the QoL among the elderly.