Background: The fragmentation of health insurance schemes in China has undermined equity in access to health care. To achieve universal health coverage by 2020, the Chinese government has decided to consolidate three basic medical insurance schemes. This study aims to evaluate the effects of integrating Urban and Rural Residents Basic Medical Insurance schemes on health care utilization and its equity in China. Methods: The data for the years before (2013) and after (2015) the integration were obtained from the China Health and Retirement Longitudinal Study. Respondents in pilot provinces were considered as the treatment group, and those in other provinces were the control group. Difference-in-difference method was used to examine integration effects on probability and frequency of health care visits. Subgroup analysis across regions of residence (urban/rural) and income groups and concentration index were used to examine effects on equity in utilization. Results: The integration had no significant effects on probability of outpatient visits (β = 0.01, P > 0.05), inpatient visits (β = 0.01, P > 0.05), and unmet hospitalization needs (β =0.01, P > 0.05), while it had significant and positive effects on number of outpatient visits (β = 0.62, P < 0.05) and inpatient visits (β = 0.39, P < 0.01). Moreover, the integration had significant and positive effects on number of outpatient visits (β = 0.77, P < 0.05) and inpatient visits (β = 0.49, P < 0.01) for rural residents but no significant effects for urban residents. Furthermore, the integration led to an increase in the frequency of inpatient care utilization for the poor (β = 0.78, P < 0.05) among the piloted provinces but had no significant effects for the rich (β = 0.25, P > 0.05). The concentration index for frequency of inpatient visits turned into negative direction in integration group, while that in control group increased by 0.011. Conclusions: The findings suggest that the integration of fragmented health insurance schemes could promote access to and improve equity in health care utilization. Successful experiences of consolidating health insurance schemes in pilot provinces can provide valuable lessons for other provinces in China and other countries with similar fragmented schemes.
Background: Equitable utilization of health care is a primary goal of the Chinese health system. This study aimed to examine horizontal inequity in health care utilization and identify the factors resulting in inequity among the middle-aged and elderly in China. Methods: The data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). We employed the concentration index (CI) and horizontal inequity (HI) to measure inequity in health care utilization. Non-linear regression models were used to decompose the CI into the contribution of each factor. Results: The CIs for the probability of and total number of outpatient visits were 0.0642 and 0.0780, respectively, and those for inpatient visits were 0.1418 and 0.1471, respectively. The HIs were also significantly positive. Living standard was the most important contributor. The contribution of health insurance varied between plans. Conclusions: This study supported the presence of pro-rich inequity in health care utilization for both probability and frequency among the middle-aged and elderly in China. Narrowing the living standard gap and improving the health insurance benefit package for the elderly should help to resolve these inequities.
Background: Multimorbidity is a significant contributor to inequalities in healthcare and has become a major unaddressed challenge for the health system in China. The aim of this study is to assess the socio-demographic distribution of multimorbidity and the relationships between multimorbidity, primary healthcare, hospitalization and healthcare spending. Methods: We conducted this nationwide population-based panel data study in China. Study participants included 12,306 residents aged ≥45 years from the China Health and Retirement Longitudinal Study in 2011, 2013 and 2015. Random-effects logistic regression models were applied to estimate the association between multimorbidity and primary healthcare as well as admission to the hospital. We used log-linear regression models to investigate the association between multimorbidity and health spending. Results: Overall, 46.2% of total interviewees reported multimorbidity. Random-effects logistic regression analyses showed that multimorbidity was associated with a higher likelihood of medication use (Adjusted odds ratio (AOR) =19.19, 95% CI = 17.60, 20.93), health check (AOR = 1.51, 95% CI = 1.43, 1.59), outpatient care (AOR = 2.39, 95% CI = 2.23, 2.56) and admission to hospital (AOR = 2.94, 95% CI = 2.68, 3.21). Log-linear regression models showed that multimorbidity was also positively associated with spending for outpatient care (coefficient = 0.64, 95% CI = 0.59, 0.68) and hospitalization (coefficient = 0.65, 95% CI = 0.60, 0.71). Conclusions: Multimorbidity is associated with higher levels of primary care, hospitalization and greater financial burden to individuals in China. Health systems need to shift from single-disease models to new financing and service delivery models to more effectively manage multimorbidity.
Background: Basic public health services for diabetes play an essential role in controlling glycemia in patients with diabetes. This study was conducted to understand the urban-rural disparities in the utilization of basic public health services for people with diabetes and the factors influencing them. Methods: The data were obtained from the 2018 China Health and Retirement Longitudinal Study (CHARLS) with 2976 diabetes patients. Chi-square tests were used to examine the disparities in the utilization of diabetes physical examination and health education between urban and rural areas. Logistic regression was performed to explore the factors associated with the utilization of diabetes public health services. Results: Among all participants, 8.4% used diabetes physical examination in the past year, and 28.4% used diabetes health education services. A significant association with age (OR = 0.64, 95% CI:0.49–0.85; P < 0.05) was found between patients’ use of health education services. Compared with diabetes patients living in an urban area, diabetes patients living in a rural area used less diabetes health education. (χ2= 92.39, P < 0.05). Patients’ self-reported health status (OR = 2.04, CI:1.24–3.35; P < 0.05) and the use of glucose control (OR = 9.33, CI:6.61–13.16; P < 0.05) were significantly positively associated with the utilization of diabetes physical examination. Patients with higher education levels were more likely to use various kinds of health education services than their peers with lower education levels (OR = 1.64, CI:1.21–2.22; P < 0.05). Conclusion: Overall, urban-rural disparities in the utilization of public health services existed. Vulnerable with diabetes, such as those in rural areas, are less available to use diabetes public health services. Providing convenient health service infrastructure facilitates the utilization of basic public health services for diabetes in older patients with diabetes, especially in rural areas.
Objective: Metabolic diseases have been a clinical challenge worldwide and a major public health issue. Very few studies from China investigated the impact of metabolic multimorbidity on healthcare and health outcomes at the national level. This study aims to examine the association of metabolic multimorbidity with health service utilization, spending, functional and mental health.Materials and Methods: This is a nationally representative cross-sectional study, utilizing the data from the China Health and Retirement Longitudinal Study in 2015, including 11,377 participants aged 45 years and older. Multivariable regression models were used to assess the association of metabolic multimorbidity with healthcare, out-of-pocket expenditure (OOPE), the activities of daily living (ADL) limitation, the instrumental activities of daily living (IADL) limitation, and depression.Results: Overall, 30.50% of total participants had metabolic multimorbidity in 2015 in China. Compared with single disease, metabolic multimorbidity were associated with the number of outpatient visits [incident rate ratio (IRR) = 1.30, 95% CI = 1.05, 1.62] and days of inpatient care (IRR = 1.52, 95% CI = 1.28, 1.81). Metabolic multimorbidity was positively associated with the OOPE on outpatient care (coefficient = 82.99, 95% CI = 17.70, 148.27) and physical functional difficulties, including ADL limitation (odds ratio = 1.36, 95% CI = 1.18, 1.57).Conclusions: Metabolic multimorbidity is associated with higher levels of health-care service use, greater expenditure for outpatient care, and more difficulties in ADL among Chinese adults. China's health-care systems need to shift from single-disease models to new financing and service delivery models to effectively manage metabolic multimorbidity.
Background: The lower job satisfaction of health-care staff will lead to more brain drain, worse work performance, and poorer health-care outcomes. The aim of this study was to identify patterns of job satisfaction among health-care staff in rural China, and to investigate the association between the latent clusters and health-care staff’s personal and professional features; Methods: We selected 12 items of five-point Likert scale questions to measure job satisfaction. A latent-class analysis was performed to identify subgroups based on the items of job satisfaction; Results: Four latent classes of job satisfaction were identified: 8.9% had high job satisfaction, belonging to “satisfied class”; 38.2% had low job satisfaction, named as “unsatisfied class”; 30.5% were categorized into “unsatisfied class with the exception of interpersonal relationships”; 22.4% were identified as “pseudo-satisfied class”, only satisfied with management-oriented items. Low job satisfaction was associated with specialty, training opportunity, and income inequality. Conclusions: The minority of health-care staff belong to the “satisfied class”. Three among four subgroups are not satisfied with income, benefit, training, and career development. Targeting policy interventions should be implemented to improve the items of job satisfaction based on the patterns and health-care staff’s features.