Inequalities In Health Care Utilization Research Articles

Long-run measurement of income-related inequalities in health care under universal coverage: evidence from longitudinal analysis in Korea

BackgroundMany countries have sought to promote well-being for their entire populations through the implementation of universal health coverage (UHC). To identify the extent to which UHC has been attained, it is necessary to evaluate equity of access to use of needed care and the cost burden of health services for the country’s entire population. This study considers income-related inequalities in health care utilization and spending in a long-term perspective for the case of the Republic of Korea.MethodsExploiting longitudinal data from a nationally representative health survey from 2008 to 2018, this study investigates how income-related inequalities in health care in Korea have varied over time and examines the extent to which need and non-need factors contribute those inequalities, using an in‐depth decomposition analysis, allowing for heterogeneous responses across income groups.ResultsThe empirical results show that overall health care utilization is disproportionately concentrated among the poor over both the short and long run. Income-group differences and non-need determinants, such as marital status and private health insurance, make larger pro-poor contributions to inequality in inpatient care use, while chronic disease prevalence greatly pushes outpatient care utilization in a pro-poor direction. The results regarding inpatient care expenses indicate a similar pattern of pro-poor bias. Long-run inequality favors the better-off in terms of outpatient care expenses, where the contribution of income-group differences has the largest impact.ConclusionMy findings suggest that it is important for health care policy in Korea to focus on improvements in the health status and well-being of low-income groups, as poor people are likely to be in poorer health. Non-need contributors could worsen pro-poor inequalities if the economic disparity across households were to increase due to the demographic transition. Higher spending on inpatient care may be a heavier financial burden for low-income people. Additional supportive measures should be provided to prevent them from suffering economic hardship. By contrast, people in high-income groups may spend most on costly services in outpatient care, including uninsured services, with the help of private health insurance. Nevertheless, the expansion of income disparity should be alleviated even from a health care policy perspective.

Horizontal Inequality in Healthcare Utilisation in Rural Sabah, Malaysia

Ensuring universal access to healthcare is essential for societal equity. However, significant inequalities exist within global healthcare systems, resulting in unequal access to services and divergent health outcomes. Socioeconomic inequity, poor living conditions, and inadequate healthcare infrastructure perpetuate poor health among poor communities. Despite greater healthcare needs, economically disadvantaged populations face substantial barriers to obtaining necessary services. This research evaluates the equitable aspect of healthcare utilisation in Sabah’s rural areas to guide policy formulation. Nabawan, a rural area in Sabah with high poverty rates, was selected to assess income-related inequality and inequity in healthcare utilisation. Using the horizontal equity index and decomposition analysis, it was found that economic status significantly influences healthcare distribution, typically favouring the affluent. Central to this analysis is the concept of “equal treatment for equal need,” ensuring individuals with similar healthcare needs receive similar care regardless of economic status. Results indicate that wealthier individuals are slightly more likely to utilise healthcare services, although the difference is minimal. To address disparities, enhancing targeted financial assistance programs like PeKa B40 could reduce out-of-pocket expenses for low-income households. Additionally, increasing healthcare funding for rural infrastructure and training local healthcare workers can ensure equitable access for all households.

Socio-economic inequality in the distribution of health care in the UK

Abstract This commentary begins with a discussion of how health care is modelled in a human capital approach and what that implies for inequality in the distribution of health care. This is followed by an outline of some of the key issues in the measurement of inequalities in health care. It ends with a brief review of what the empirical literature shows on inequality in health-care utilization in the UK by socio-economic status.1

Rural–urban inequalities in health care utilization in Bhutan: a decomposition analysis

Background and objectiveOn the trajectory towards universal health coverage in Bhutan, health equity requires policy attention as significant disparities exist between urban and rural health outcomes. This paper examines health services utilization patterns, inequalities and their socio-economic determinants in rural and urban areas and decomposes the factors behind these differences.MethodsWe used the Bhutan Living Standard Survey 2017 to profile health services utilization patterns and equalities. We employed two different decomposition analyses: decomposition of mean differences in utilization using the Oaxaca–Blinder decomposition framework and differences in the income-related distribution in utilization using recentered influence function regressions between rural and urban areas.ResultsSignificant differences exist in the type of outpatient services used by the rural and urban population groups, with those living in rural areas having 3.4 times higher odds of using primary health centers compared to outpatient hospital care. We find that the use of primary health care is pro-poor and that outpatient hospital resources is concentrated among the more affluent section of the population, with this observed inequality consistent across settings but more severe in rural areas. The rural–urban gap in utilization is primarily driven by income and residence in the eastern region, while income-related inequality in utilization is influenced, aside from income, by residence in the central region, household size, and marriage and employment status of the household head. We do not find evidence of significant mean differences in overall utilization or inequality in utilization of inpatient health care services.ConclusionsWhile the differences in average contacts with health services are insignificant, there are prominent differences in the level of services availed and the associated inequality among rural and urban settings in Bhutan. Besides, while there are obvious overlaps, factors influencing income-related inequality are not necessarily the same as those driving the utilization gaps. Cognizance of these differences may lead to better informed, targeted, and potentially more effective future research and policies for universal health coverage.

Utilisation of public healthcare services by an indigenous group: a mixed-method study among Santals of West Bengal, India.

A barrier to meeting the goal of universal health coverage in India is the inequality in utilisation of health services between indigenous and non-indigenous people. This study aimed to explore the determinants of utilisation, or non-utilisation, of public healthcare services among the Santals, an indigenous community living in West Bengal, India. The study holistically explored the utilisation of public healthcare facilities using a framework that conceptualised service coverage to be dependent on a set of determinants - viz. the nature and severity of the ailment, availability, accessibility (geographical and financial), and acceptability of the healthcare options and decision-making around these further depends on background characteristics of the individual or their family/household. This cross-sectional study adopts ethnographic approach for detailed insight into the issue and interviewed 422 adult members of Santals living in both rural (Bankura) and urban (Howrah) areas of West Bengal for demographic, socio-economic characteristics and healthcare utilisation behaviour using pre-tested data collection schedule. The findings revealed that utilisation of the public healthcare facilities was low, especially in urban areas. Residence in urban areas, being female, having higher education, engaging in salaried occupation and having availability of private allopathic and homoeopathic doctors in the locality had higher odds of not utilising public healthcare services. Issues like misbehaviour from the health personnel, unavailability of medicine, poor quality of care, and high patient load were reported as the major reasons for non-utilisation of public health services. The finding highlights the importance of improving the availability and quality of care of healthcare services for marginalised populations because these communities live in geographically isolated places and have low affordability of private healthcare. The health programme needs to address these issues to improve the utilisation and reduce the inequality in healthcare utilisation, which would be beneficial for all segments of Indian population.

The Divergence of Inequality in Healthcare Utilization Between Poor- and Rich-Medical Resource Regions: Evidence from the Middle-Aged and Older Adults in China

The Divergence of Inequality in Healthcare Utilization Between Poor- and Rich-Medical Resource Regions: Evidence from the Middle-Aged and Older Adults in China

Inequalities in healthcare utilisation among adults with type 2 diabetes

AimsTo examine inequality in dentist, ophthalmologist, and podiatrist attendance among adults with type 2 diabetes in a country with varying degrees of co-payment. Research design and methodsWe conducted a cross-sectional study with a population of 41,181 people with type 2 diabetes resident in the Central Denmark Region in 2019, identified through Danish registers using a prespecified diabetes algorithm. Descriptive statistics and multiple logistic regression were used to examine the attendance at dentist, ophthalmologist, and podiatrist, controlling for sociodemographic and clinical factors. Attendance at dentist, ophthalmologist, and podiatrist were examined separately. ResultsThe majority (59.7 %) had attended the ophthalmologist at least once in the preceding year, whereas 46.5 % and 34.2 % had visited the dentist/dental hygienist and podiatrist, respectively. Disposable household income increased attendance significantly, with a clear gradient in the OR of attending the dentist (p < 0.001), whereas age significantly magnified the OR of podiatrist and ophthalmologist attendance (p < 0.001). ConclusionsThis study provides circumstantial evidence that co-payment can increase inequality in health care attendance, especially for dental attendance, and it further shows that there is significant sociodemographic inequality in healthcare utilisation among people with type 2 diabetes.

Socioeconomic differences in the perception of inequalities in healthcare utilization and health in South Korea

This study investigated the lay perception of inequalities in society, healthcare utilization, and health in Korea. We also examined the association between socioeconomic status (SES) and perception of inequalities. Data from an online survey on the perception of health and healthcare inequalities related to cancer conducted between October 19, 2021, and November 12, 2021, were used. Data of 3,769 participants aged 20 to 74 years from 17 provinces were analyzed. We examined the perceived level of inequalities according to SES or residential area using frequency analysis, a t-test or analysis of variance (ANOVA), multiple linear regression analysis, and multiple logistic regression analysis. The mean score for perception of social inequality was 5.99 [Standard Deviation (SD) = 1.95] and that for perception of healthcare utilization inequality was 4.75 (SD = 1.96). The perception rate of health inequality according to SES and residential area was approximately 59 % and 61 %, respectively. Higher the income level, lower the level of perception of social inequalities β = -0.22, p < 0.01). Higher the education level, higher the level of perception of healthcare utilization inequalities (β = 0.21, p < 0.01). Higher the education level, higher the level of perception of health inequalities according to SES or residential area [adjusted odds ratio (aOR): 2.33 (95 % CI: 1.48, 3.66); aOR: 2.73 (95 % CI: 1.73, 4.31)]. Socioeconomic inequalities were observed in the perception of inequalities in healthcare utilization and health. Policymakers should establish policies to bridge the gap between perceived healthcare utilization inequalities and health inequalities. Future research should investigate the perception of healthcare utilization and health inequalities.

Socioeconomic Inequality and Associated Factors Affecting Health Care Utilization among the Elderly: Evidence from the China Health and Retirement Longitudinal Study

Background: Elderly population is particularly vulnerable to socioeconomic disparities. This study assessed inequalities in health care utilization among the elderly in China and identified contributing factors. Methods: This study used data from the 2018 China Health and Retirement Longitudinal Study survey. A non-linear probit regression model based on the Andersen Health Care Utilization Model was used to identify determinants of health care utilization among the elderly. The concentration index (CI) and the decomposition of the CI were calculated to evaluate inequalities in health care utilization among the elderly and identify related contributors. Results: The CI for actual and standardized outpatient visits was 0.0889 and 0.0945, respectively, and the corresponding values for inpatient service utilization were 0.1134 and 0.1176, respectively. Factors that contributed to greater inequalities in the utilization of outpatient and inpatient service included income (73.68% for outpatient service; 85.20% for inpatient service), Urban Employee Basic Medical Insurance (UEBMI) (40.75% for outpatient service; 32.03% for inpatient service) and non-agricultural Hukou status (12.63% for outpatient service; 18.73% for inpatient service). New Rural Cooperative Medical Scheme (NRCMS) (−34.30% for outpatient service; −33.18% for inpatient service) and poor health status (−7.36% for outpatient service; −8.30% for inpatient service) reduced inequalities in outpatient and inpatient utilization. Conclusions: This study found that a key contributor to these inequalities was income, followed by UEBMI coverage. Meanwhile, health care coverage through NRCMS was associated with fewer disparities in health care utilization.

Inequalities in healthcare utilization among older adults during the second year of covid-19 pandemic: findings from the share cohort

Inequalities in healthcare utilization among older adults during the second year of covid-19 pandemic: findings from the share cohort

Contribution of the Ghana National Health Insurance Scheme to Inequality in Healthcare Utilisation

Inequality in healthcare utilisation contributes to socio-economic disparities in health outcomes. The government of Ghana rolled out the Ghana National Health Insurance Scheme (NHIS) as a pro-poor health policy to reduce the financial barrier to accessing healthcare to increase healthcare utilisation, especially among the poor. Evidence showed a pro-rich utilisation inequality in Ghana prior to the nationwide start of the NHIS in 2005. This article applied the concentration index and decomposition methods to the round six of the Ghana Living Standard Survey data to investigate the contribution of the NHIS to utilisation inequality. The results showed the rich to benefit more than the poor from the NHIS and the NHIS contributed to about half of the pro-rich utilisation inequality. The NHIS increased utilisation but more so for the rich than the poor. A policy implication of the article is that pro-poorness of the NHIS might require separate NHIS schemes for the poor and non-poor to enable different policies implemented in the schemes to increase the distributional disparity of health subsidies in favour of the poor.

The socioeconomic inequity in healthcare utilization among individuals with cardiovascular diseases in India.

We assess the effects of socioeconomic inequity on healthcare utilization among individuals with cardiovascular diseases (CVDs) in India using the indirect standardization method with Erreygers' corrected concentration index. We analyze both horizontal and vertical inequities and linearly decompose the respective inequities to identify the major factors driving both kinds of inequities. Our findings show that actual healthcare utilization is highly concentrated among rich CVD individuals. After controlling for the confounding effects of health needs, horizontal inequity is found to be significantly pro-rich, and income and urban concentration are found to be the major factors driving this inequity. However, the direction and magnitude of vertical inequity vary, depending on the selection of the target group. When we use healthcare utilization of the richest 20 percent as the target, we find no significant vertical inequity among CVD individuals. However, when we take the richest 10 percent as the target, we observe a significant pro-rich differential effect of health needs on healthcare utilization between all individuals and the target group. Decomposition reveals an inappropriate differential effect of health needs and age in driving vertical inequity. Hence, the presence of vertical inequity may trigger further pro-rich socioeconomic inequity in healthcare utilization if not supported by any targeted healthcare coverage.

The impact of medical financial assistance on healthcare expenses and the medical financial burden: Evidence from rural China.

The medical financial burden has become a key limitation to accessing healthcare in rural areas of China as healthcare expenses continue to rise. To ensure that low-income people have access to basic healthcare services, China has implemented medical financial assistance (MFA) policy, which provides social health insurance and medical cash assistance for low-income people. Using data from the 2014 China Family Panel Studies (CFPS), the propensity score matching (PSM) method was applied to estimate the impact of MFA on healthcare expenses and the medical financial burden. Empirical results showed that the total annual healthcare expenditure of MFA beneficiaries is significantly higher than that of non-beneficiaries after matching. Although low-income individuals are now covered by MFA, neither the out-of-pocket expenditure to per capita household non-food expenditure ratio nor the likelihood of catastrophic healthcare expenditure (CHE) decrease significantly. Medical financial assistance (MFA) has reduced the inequality in healthcare utilization to a certain extent by improving access to healthcare for low-income people. However, people with low income still face a heavy medical financial burden even when they are covered by MFA. Policymakers should pay attention to raising the standards of MFA in rural areas and providing higher subsidies for the reasonable healthcare expenditures of low-income people.

Income-Related Inequality in Health Care Utilization and Out-of-Pocket Payments in China: Evidence from a Longitudinal Household Survey from 2000 to 2015

In recent decades, China has experienced rapid economic growth and rising health inequality. The government has introduced a nationwide health care reform aimed at achieving affordable and equitable basic health care for all. This paper investigates income-related inequality in health care utilization and out-of-pocket (OOP) payments and explores the underlying factors that drive the inequalities. Using data running from 2000 to 2015 and covering nine of thirty-one provinces in China, we calculate indices to measure income-related inequality and adopt a regression-based decomposition approach to explore the sources of inequality. We find pro-rich inequality in the use of preventive care and pro-poor inequality in the use of folk doctors. In addition, the better-off have preferential access to higher level hospitals, while the use of primary care facilities is more concentrated among the poor. The poor are also found to face a heavier financial burden since they tend to spend a larger share of their income on OOP payments. Education, employment and geographic regions all appear to contribute to the total inequality. Our results indicate that affordability remains a common barrier for the poor to access health care, and that the inequality is largely driven by socio-economic factors.

Impact of Social Deprivation on Hospitalization and Intensive Care Unit Admission among COVID-19 Patients: A Systematic Review and Meta-Analysis.

The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected socially disadvantaged groups; however, the association between socioeconomic status and healthcare utilization among COVID-19 patients remains unclear. Therefore, a systematic review and meta-analysis was conducted to assess the association between socioeconomic status and hospitalization and intensive care unit admission among COVID-19 patients. PubMed, Embase, and the Cochrane Register of Controlled Trials were searched for relevant literature (updated to Jun 2022). Studies that investigated the association of social deprivation with hospitalization and intensive care unit admission in COVID-19 patients were included. The primary outcomes included risk of hospitalization and intensive care unit admission, measured by odds ratio. Eleven studies covering 2,423,095 patients were included in the meta-analysis. Socially disadvantaged patients had higher odds of hospitalization in comparison to socially advantaged patients (odds ratio 1.25, 95% confidence interval: 1.14 to 1.38; P<0.01). The odds of intensive care unit admission among more deprived patients was not significantly different from that of less deprived patients (odds ratio 1.03, 95% confidence interval: 0.78 to 1.35; P=0.85). These findings were proven robust through subgroup and sensitivity analyses. Socially disadvantaged populations have higher odds of hospitalization if they become infected with COVID-19. More effective medical support and interventions for these vulnerable populations are required to reduce inequity in healthcare utilization and alleviate the burden on healthcare systems.

Income, education, and hospitalization in Canada: results from linked census and administrative data

BackgroundAddressing population health inequities begins with quantifying how social factors affect the health and health care utilization of individuals. Such quantification relies on the availability of detailed health and demographic data. Unfortunately, administrative health care data rarely includes detailed demographic information. Data linkage, which combines administrative health data with national-level census or survey data, enables researchers to examine socio-economic inequalities in health care utilization in greater detail.Data and methodsWith access to a unique Canadian dataset linking data from the Hospital Discharge Database (DAD) from 2006 to 2007 with detailed individual-level socio-demographic data from the 2006 Canadian Census, we are able to examine the patterning of hospitalization in Canada in the early 2000s across a variety of socio-demographic variables. We examine the association of education and income, controlling for immigration status, rural residence, marital status and ethnicity, with hospitalization rates for both ambulatory care sensitive conditions (ACSCs) and non-ambulatory care sensitive conditions (non-ACSCs) for children and youth, working-age adults, and older adults, in models stratified by sex.ResultsAge standardized hospitalization rates show that there is a clear socio-economic gradient in hospitalization in Canada in the 2000s. Education and income are independently, inversely associated with hospitalization for males and females across three broad age groups. These associations are stronger for ACSCs than non-ACSCs. The association of other socio-demographic variables, such as immigrant status, and rural residence is also stronger for hospitalization for ACSCs. The association of socio-economic status with hospitalization for ACSCs is strongest for working age women and men, and is somewhat attenuated for older adults.ConclusionsLower socio-economic status is associated with a higher likelihood of hospitalization for men and women in Canada across three broad age groups in the 2000s. These associations are stronger for ACSCs, suggesting that in addition to increased likelihood of disease, decreased access to preventative care may be driving up hospitalization rates for marginalized groups. We conclude with the recommendation that in order to track progress in reducing health inequities, health systems should either collect detailed individual-level socio-demographic data or link their administrative health data to existing demographic data sets.

Does community HIV combination prevention (HPTN 071 (PopART)) impact healthcare inequity?

Abstract Background This research explores the impact of the HIV Prevention Trials Network (HPTN) 071 combination prevention (PopART) trial on horizontal inequity in Zambia and South Africa. Evidence suggests there is often inequality in healthcare utilisation in relation to socioeconomic characteristics, such as wealth. This paper is the first to address such distributional outcomes and inequities in a randomised trial setting. Methods We utilise horizontal inequity as a key performance metric to make value judgements with regards to the distribution of healthcare utilisation in a health system. Additionally, we supplement this index by estimating the impact of PopART on inequality in healthcare utilisation and HIV prevalence, estimating concentration curves and indices. Results We find a pro-rich inequity in healthcare utilisation, as ranked by wealth, before and after the trial is implemented. Pro-rich implies, for example, the 20% poorest make up less than 20% of healthcare utilisation. This suggests the trial enabled the wealthier subset of the population to take better advantage of accessing healthcare. Conclusions Given the high prevalence of HIV in lower-income households in Zambia and South Africa, these results strengthen the case for interventions tailored to informing poorer households about the benefits of prevention and after-care. Key messages • The PopART trial demonstrates as with any intervention, there is a risk of exacerbating an underlying inequity. Policies directed at these problems specifically may help alleviate such burdens. • This paper shows one example of a distributional imbalance in the HIV population. Given the absence of work on RCT interventions, the findings may also be used to inform future trial design.

The role of regional health policy for socioeconomic inequality in health services utilization

Abstract Background “J1” is a preventative routine examination in Germany recommended for adolescents at the age of 12-14 years. In contrast to the well-established U1-U9 examinations for younger children, with participation rates above 90%, the attendance of the J1 examination is approximately only 40%. The most frequent reason for not attending J1 is the unawareness of this examination. “Ticket to J1” is an intervention including an information leaflet introduced in Bavaria in 2017 to inform adolescents about J1. The aims of the present analysis are to investigate (1) if the regional policy was effective in increasing the attendance in J1, (2) if the effects vary by family socioeconomic status (SES), and (3) which meso-level characteristics of the healthcare system correlate with attendance rates in J1. Methods We used anonymised data of a large statutory health insurance in Germany for the timeframe of 2016-2018. To investigate the effect of the policy, a difference-in-differences design at the individual level was used. Assuming a parallel trend at the level of federal states, the likelihood of attendance in J1 of 13- and 14-year-olds was compared between Bavaria and other federal German states before and after policy introduction. All analyses were additionally stratified by SES. Results The introduction of “Ticket to J1” increased participation in J1 by 1% after controlling for all confounders. Furthermore, the effect was stronger for children from families with lower SES (an increase of 5%). Density of pediatricians was positively significantly correlated with participation in J1. Discussion Regional health policy intervention had a significant positive impact on attendance of J1 and appears to have the potential to reduce socioeconomic inequalities in healthcare utilization. Informing adolescents about J1 seems to increase the attendance, in particular for children from families with lower SES.

Decomposing the rural–urban gap in the prevalence of undiagnosed, untreated and under-treated hypertension among older adults in India

BackgroundAlthough awareness and treatment rates of hypertension have significantly improved in recent years, the prevalence of undiagnosed and untreated hypertension remains a major public health concern for Indian policymakers. While the urban–rural variation in the prevalence, diagnosis, control, and treatment of hypertension is reasonably well-documented, the explanation behind such variation remains poorly understood given the dearth of studies conducted on exploring the determinants of the rural–urban gap in the prevalence of undiagnosed, untreated, and uncontrolled hypertension in India. In view of this research gap, our paper aims to decompose the inter-group differences between rural and urban areas in undiagnosed, untreated, and undertreated hypertension among older adults in India into the major contributing factors.MethodsNationally representative data collected in the Longitudinal Ageing Study of India, Wave-1 (2017–18), was utilized for this study. Maximum-likelihood binary logistic-regression models were employed to capture the crude and adjusted associations between the place of residence and prevalence of undiagnosed, untreated, and undertreated hypertension. Fairlie’s decomposition technique was used to decompose the inter-group differences between rural and urban residents in the prevalence of undiagnosed, untreated, and undertreated hypertension among the older population in India, into the major contributing factors, in order to explore the pathways through which these differences manifest.ResultsThe overall prevalence rates of undiagnosed, untreated, and undertreated hypertension among older adults were 42.3%, 6%, and 18.7%, respectively. However, the prevalence of undiagnosed and untreated hypertension was higher in rural areas, by 12.4 and 1.7 percentage-points, respectively, while undertreated hypertension was more prevalent in the urban areas (by 7.2 percentage-points). The decomposition analysis explained roughly 41% and 34% of the urban advantage over rural areas in the case of undiagnosed and untreated hypertension, while it explained 51% of the urban disadvantage in respect of undertreated hypertension. The rural–urban differentials in education and comorbidities accounted for the majority of the explained rural disadvantage in the prevalence of undiagnosed hypertension, explaining 13.51% and 13.27% of the gap, respectively. The regional factor was found to be the major driver behind urban advantage in the prevalence of untreated hypertension, contributing 37.47% to the overall gap. In the case of undertreated hypertension, education, comorbidities, and tobacco consumption were the major contributors to the urban–rural inequality, which accounted for 12.3%, 10.6%, and 9.8% of the gap, respectively.ConclusionSocio-economic and lifestyle factors seemed to contribute significantly to the urban–rural gap in undiagnosed, untreated and undertreated hypertension in India among older adults. There is an urgent need of creating awareness programmes for the early identification of hypertensive cases and regular treatment, particularly in under-serviced rural India. Interventions should be made targeting specific population groups to tackle inequality in healthcare utilization.

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

BackgroundIn the Chinese population, the middle-aged and older adults are the two main segments that utilize a large portion of healthcare. With the fast growth of the two segments, the demands of healthcare services increases significantly. The issue related to inequality in utilization of healthcare emerges with the growth and it deserves more attention. Most existing studies discuss overall inequality. Less attention is paid to inequality among subdivisions, that is, relative inequality. This study focuses on the inequality of healthcare utilization among the homogeneous population and the inequality of the full samples in China.MethodsData were obtained from four waves of the China Health and Retirement Longitudinal Study (CHARLS): 2011, 2013, 2015 and 2018. First, the Concentration Index (CI) was used to measure the inequality of outpatient, inpatient and preventive care for the samples, and regression analysis was applied to decompose the contributing factors of inequality. Then SOM is introduced to identify homogeneous population through clustering and measure the inequality in three types of healthcare utilization among homogeneous population. Based on this, the difference between absolute inequalities and relative inequalities was discussed.ResultsThe preventive care is shown to have the highest degree of inequality inclined to the rich and has the largest increase (CI: 0.048 in 2011 ~ 0.086 in 2018); The inequality degree in outpatient care appears to be the smallest (CI: -0.028 in 2011 ~ 0.014 in 2018). The decomposition results show that age, education, income, chronic disease and self-reported health issues help explain a large portion of inequality in outpatient and inpatient care. And the contribution of socioeconomic factors and education to the inequality of preventive care is the largest. In regards to three types of healthcare among the homogeneous population, the degree of inequality seems to be higher among group with high socioeconomic status than those with lower socioeconomic status. In particular, for the people who are in the high socioeconomic group, the degree of inequality in preventive care is consistently higher than in outpatient and inpatient care. The inequality degree of preventive care in the low socioeconomic status group varies significantly with the flexibility of their response to policies.ConclusionsKey policy recommendations include establishing a health examination card and continuously improving the fit of free preventive care with the needs of the middle-aged and older adults; developing CCB activities to avoid people’s excessive utilization in the high socioeconomic status group or insufficient utilization in the low socioeconomic status group; reasonable control of reimbursement and out-of-pocket payments.