Decomposition of Healthcare Utilization Inequality in Iran: The Prominent Role of Health Literacy and Neighborhood Characteristics

Abstract

Unequal utilization in healthcare can potentially affect the right to health. Access to healthcare services and achieving positive health outcomes and health equity are essential principles in promoting human rights. This study aims to assess and analyze socioeconomic-related inequalities in outpatient health services utilization (OHSU) among various socio-demographic subgroups to inform policies that foster health equity. Data were collected through a cross-sectional survey of 1200 households in Tehran, Iran. Inequality in OHSU among the socio-demographic subgroups was calculated by concentration, Wagstaff, and Erigers indices. Decomposition was used to identify the factors contributing to inequality in OHSU. Marginal effect and elasticity were used to calculate the relative absolute shares of socio-demographic variables in the inequality. The rate of OHSU was 63.61% (CI: 60-66.80) which concentrated among households with better socioeconomic status. Based on the results, living in an affluent neighborhood (Relative share (RS): 85.48) and having a disabled member in the household (RS: 6.58) were the most important factors in the concentration of OHSU in favor of the privileged groups. In contrast, very low levels of health knowledge (RS: −83.79) and having basic insurance coverage (RS: −3.92) concentrated OHSU in favor of the lower socioeconomic households. The study was conducted based on survey data, and this may lead to some limitations. Given that this study was a cross-sectional study, we were unable to establish causal relationships between explanatory variables and outpatient health service utilization and its relevant predictors. Households with disabled member(s), as well as a member(s) with chronic diseases, may experience severe inequalities in access to healthcare services. Policies that facilitate access to health services for these households can play a significant role in improving health equity.

• What do we already know about this topic?

• Unequal healthcare utilization, particularly concerning outpatient health services, has been an ongoing concern across various demographics.

• How does your research contribute to the field?

• This research extends our understanding of socioeconomic-related disparities in outpatient health services utilization (OHSU) among diverse socio-demographic subgroups.

• What are your research’s implications toward theory, practice, or policy?

• Recognizing the pronounced impact of factors such as “disability” within households or “health literacy” on unequal access to healthcare services suggests the need for targeted policies addressing these vulnerable groups.

Introduction

Access to high-quality healthcare services is a basic human right. ¹ However, research has shown that over 1 billion individuals in low- and middle-income countries are unable to access the healthcare services they need for various reasons. ² As such, ensuring equal access to health services is an essential goal for any health system, as it helps to address the gap in health outcomes between rich and poor households.^3,4

In Iran, healthcare services are provided by both the private and public sectors, as well as by non-profit organizations. The Ministry of Health and Medical Education plays a significant role in coordinating the different participants. Iran has the lowest health expenditure per capita compared to other countries. ⁵ More than 90% of the population has health insurance, and the government has made universal coverage by 2018 a priority. In general, health insurance covers 70% of the cost of drugs on the insurers’ coverage list, and 90% of public hospital costs, with extra provision for those with rare diseases or in remote areas. ⁶ Although Iran’s public healthcare system, which was developed in 1984, has been considered a remarkable success, public access to services at the secondary and tertiary levels has not improved. ⁷ Iranians continue to face inequalities in health expenditure and access to healthcare. ⁸ To address this issue, Iran’s health system has been working to provide universal health coverage. ⁹ Despite the increase in health services provision, however, the problem of unequal health service utilization persists as a major social problem. ¹⁰

Lower socioeconomic status is directly linked to reduced utilization of health services and poorer health outcomes.^11-13 Evidence suggests that equal access and utilization of health services can prevent the need for more complex and costly medical treatment. ¹⁴ Inequality in health service utilization not only affects individuals, but also has a negative impact on labor market productivity and ultimately, gross domestic product. ¹⁵ There is clear evidence showing that healthcare services utilization has not been equally distributed among different socioeconomic groups^16-18 that goes against basic human rights.^4,19,20 Studies conducted in both developed and developing countries have demonstrated that residents in affluent areas are more likely to utilize health services when they become sick compared to their counterparts in poorer areas.^3,21,22

It is well-established that individuals in lower socio-economic groups experience more adverse health outcomes than those in higher socio-economic groups. ²³ Such studies shed light on the possible connections between individuals’ circumstances and characteristics and their health outcomes. However, to gain insight into why health services are or are not utilized by households, it is essential to explore health outcomes from the perspective of health services utilization. This approach will provide health service providers and planners with vital information on how and why services are utilized or not utilized by households. One strategy is to break down the inequity issue into smaller problems that can be addressed. Several studies have done this, such as studies on access to dental services,^24,25 general physicians, specialists, and health workers, ²⁶ infant mortality, ²⁷ health reform, ²⁸ mental health, ²⁹ health inequalities, ³⁰ health expenditure. ³¹

Anderson’s^32,33 three-stage model presents a comprehensive framework for understanding healthcare utilization patterns. The model encompasses predisposing, enabling, and need components, which collectively explain the variations in families’ use of medical care services. Anderson’s model postulates that healthcare utilization occurs when families are predisposed to receive medical care, conditions facilitate healthcare accessibility, and families perceive a need for services and subsequently respond to it. This 3-stage process ultimately leads to healthcare utilization, a resultant component of the model. Expanding upon Anderson’s model, a wealth of literature examines the determinants of healthcare utilization.^34-37 Key determinants include health status, wherein individuals with chronic diseases or greater healthcare needs are more likely to seek medical services more frequently.^19,38,39 Socioeconomic factors, including income, education, health literacy and occupation, play a pivotal role in healthcare access, with lower socioeconomic status often leading to reduced utilization due to financial constraints and limited access to information.^26,40-42 Health insurance coverage as a key determinant, significantly influences healthcare utilization, with adequate coverage enabling individuals to afford essential medical services and treatments.^43-45 Health insurance in Iran is provided through both social insurance and supplementary insurance schemes. Social insurance is mandatory and mainly covers formal economic workforce and some informal occupational groups. Supplementary insurance, on the other hand, is offered by private insurers to expand coverage, but it only includes individuals with basic insurance coverage. The neighborhood socioeconomic condition and spatial accessibility is also a critical factor, as proximity to healthcare facilities impacts the likelihood of timely care seeking.^46-48 Health literacy emerges as a pivotal determinant, as individuals with higher health literacy are better equipped to understand healthcare options, make informed decisions, and follow medical advice. ⁴⁹ Previous healthcare experiences, chronic disease management, and functional limitations further contribute to healthcare utilization.^50-52 Notably, these determinants interact within different populations, cultures, and healthcare systems, necessitating tailored interventions to optimize healthcare utilization among the population.

The current study employed meso-level data to decompose inequality and prioritize the determinants of inequality based on their significance. While various studies have explored health service utilization inequality, a few of them have specifically examined socio-economic inequality within households using the decomposition method applied in this study. This study aims to address this gap by decomposing outpatient health services utilization inequality by households’ socio-economic status. Considering the limited resources, the present study tried to identify the most relevant factors and emphasize the inequality in the household, so it is possible to plan a paper route for policy makers to define where to start.

Methods

Study Design

The present study is an observational descriptive-analytical study. All households living in 22 municipal districts (368 neighborhoods) of Tehran between winter 2018 and spring 2019 were considered as study’s population. Tehran, the capital and largest city of Iran with a population of 9 million people, has 22 districts. The city of Tehran is the largest immigrant-friendly city in Iran, and due to the high cultural and social diversity of its residents, it is chosen as a representative sample of the country in many studies. ⁵³ This study received approval from the Research Ethics Committee of the University of Social Welfare and Rehabilitation Sciences, Tehran, Iran (IR.USWR.REC.1397.029). The committee oversaw and endorsed all stages of the study design, implementation, and result reporting.

Sampling

According to the 40% health service utilization in Iran, ⁵⁴ a 95% confidence interval (α = .05), and the desired precision (d = 0.03), the sample size was estimated to be 1024 households. To ensure a sufficient number of the estimated samples, the final sample size was considered 1200 households. ³⁷

The samples were selected based on multistage cluster sampling method, by dividing the city of Tehran into 5 zones depending on the socioeconomic development status, based on the Kamal, Harouni and Basakha ⁵⁵ study. Between 1 and 3 districts were randomly by cluster sampling selected from each zone to give a total of 10 districts. Districts 3, 6, 5, 22, 13, 10, 20, 16, 18, and 19 were selected. The sample size assigned to each zone was based on the population share of the selected districts. From each of the 10 selected districts, 2 neighborhoods were randomly selected by cluster sampling. Then 1200 households were selected systematic randomly from the neighborhoods.

Data Management

The inclusion criteria for the households included having lived in Tehran for at least 1 year at the time of data collection and giving informed consent to participate in the study. Institution-based households, such as individuals living in barracks, boarding houses, and nursing homes, as well as non-Iranian households were not included in this study. Given the role of women in the family and their more extensive knowledge about family members’ health status, health costs, and health service utilization, ⁵⁶ women (the mothers or the women of the family) were selected as the informed and responsible respondents in this study. Data were collected using the inventory of demographic, socioeconomic, health behavior variables, and the World Health Organization’s health service utilization tool.^57,58 This tool has already been used in several national researches on health service utilization in Iran.^26,59,60

Outcome Variable as Health Service Utilization

OHSU, as the outcome variable in this study, includes referrals to healthcare centers, receiving outpatient health services provided by general practitioners, specialists, or other healthcare providers at health centers, physicians’ offices, polyclinics, outpatient units at hospitals, diagnostic imaging centers, and laboratories during the previous month. In this study, the status of outpatient health service utilization of household members over the past month before the survey was measured using the health service utilization tool, through 3 yes-no questions.

The first question was about the needs of each household member for health services in the last month, the second question investigated the referral status, and the third question inquired about the status of receiving services.

In this study, the outpatient health service utilization status of the household was determined by aggregating the last 3 needs of the family during the last month. In cases where a family member had not received any health services or had been referred for at least one health need during the past month but had not yet received a service (ie, having at least one unmet need), it was considered to be health service non-utilization.

Explanatory Variables

Considering the Anderson’s model and the literature, the variables such as gender and marital status of the household’s head, having a person with a chronic disease in the household (Yes/No), having a person with a disability in the household (Yes/No), health literacy of the family members (Categorical: very low to very high), socioeconomic level of the neighborhood, ⁵⁵ respondents’ education level (lower or higher than high-school diploma), and basic health insurance coverage (Yes/No), used as explanatory variable as proxies of predisposing, enabling, and need components of healthcare utilization.

Another vital variable required for inequality decomposition is the asset index. This index ranks households based on their assets, determining their socioeconomic statuses. This index was calculated through the principal component analysis (PCA) technique and according to household assets, including dishwashers, laptops, tablets, side-by-side refrigerators, personal cars, and real estate. The Z-scores of this index were saved and divided into 3 categories of low, medium, and high, according to quartile points and the inequality indexes were calculated based on this rank variable. ³⁷

Statistical Analysis

The sample data was analyzed descriptively, including demographic characteristics and distribution of health service utilization among sub-groups. The mean, standard deviation, and Chi-square test were used for analysis, and the results are presented in Tables 1 and 2. Wagstaff and Erigers indexes^61-64 were calculated using STATA v.14, and results are presented in Table 3. The concentration index is a number between 1 and −1. The closer the number to the boundaries, the more inequality is indicated. Zero indicates the perfect equality. ⁶⁵ If OHSU was concentrated among the privileged groups (in the present study, households with higher socioeconomic status), the concentration index would have a positive sign and vice-versa. Through inequality decomposition, the study sought to determine whether the inequality in OHSU is dissimilar among different sub-groups. Inequality in OHSU decomposed by using a Logit or Probit regression model estimation ⁶⁶ and the results are shown in Table 4.

Table 1.

Demographic Features and Outpatient Health Services Utilization Among the Participants.

Variable/class	M(SD) (N = 803)
Duration of residence (year)	17.45 (14.5)
Family size (person)	3.18 (1.20)
Mother’s age (year)	49 (13.95)
	Percentage (95% CI) (N = 803)
Mother’s job
Housewife	74.30
Others	25.70
Mother’s education level
Below high school diploma education	55.41
High school diploma and higher education	44.59
Family socio-economic status
Low	20.73
Middle	56.41
High	22.86
Health service utilization status
Utilized	63.61 (60-66.80)
Non-utilized	36.39 (33-39.70)

Table 2.

Descriptive Statistics of Outpatient Health Services Utilization Among Different Subgroups.

		Utilized (%)	Non-utilized (%)	P-Value
Gender of the head of the household	Male	299 (67.0%)	147 (33.0%)	.052
	Female	58 (56.9%)	44 (43.1%)
Education of the head of the household	Below high school diploma education	171 (64.3%)	94 (35.7%)	.107
	High school diploma and higher education	181 (67.3%)	88 (32.7%)
Marital status of the head of the household	Married	287 (67.1%)	141 (32.9%)	.146
	Divorced/widow	47 (56.0%)	37 (44.0%)
	Single	12 (63.2%)	7 (36.8%)
Having a person with a chronic disease in the family	Yes	197 (67.7%)	94 (32.3%)	.079
	No	313 (61.5%)	167 (38.95%)
Having a person with a disability in the family	Yes	62 (73.8%)	22 (26.2%)	.048
	No	421 (62.8%)	249 (37.2%)
Basic insurance	Yes	315 (66.2%)	161 (33.8%)	.133
	No	32 (56.1%)	25 (43.9%)
Family knowledge about health issues	Very low	69 (63.3%)	40 (36.7%)	.026
	Low	136 (64. 2%)	76 (35.8%)
	Moderate	261 (68.0%)	123 (32.0%)
	High	40 (48.8%)	42 (51.2%)
	Very high	4 (57.1%)	3 (42.9%)
Level of development of the residence	The lowest	162 (65.3%)	83 (34.7%)	.000
	Low	130 (81.2%)	30 (18. 8%)
	Middle	73 (74.5%)	25 (25.5%)
	High	63 (49.6%)	64 (50.4%)
	The highest	90 (49.7%)	91 (50.3%)
Socio-economic STATUS	Low	92 (55.8%)	73 (44.2%)	.137
	Lower middle	127 (64.1%)	71 (35.9%)
	Middle	249 (66.2%)	127 (33.8%)
	Upper middle and high	40 (64.5%)	22 (35.5%)

Table 3.

Inequality in Health Services Utilization Among Different Socio-Demographic Groups.

		N	CI	Erreygers	Wagstaff	F	P-Value
Total Samples		801	0.021	0.053	0.055
Gender of the head of the household	Male	441	0.049 ***	0.131 ***	0.146 ***	0.025	.875
	Female	97	−0.004	−0.010	−0.011
Education of the head of the household	Below high school diploma education	257	0.062 **	0.159 **	0.174 **	1.945	.163
	High school diploma and higher education	268	0.039 *	0.104 *	.117 *
Marital status of the head of the household	Married	422	0.052 ***	0.137 ***	0.153 ***	0.116	.890
	Divorced/widow	82	0.051	0.113	.114
	Single	18	−0.040	−0.113	−0.136
Having a person with a chronic disease in the family	Yes	284	0.066 ***	0.179 ***	0.204 ***	4.274	.039
	No	508	0.005	0.012	.013
Having a person with a disability in the family	Yes	82	0.085 **	0.261 **	0.365 **	3.115	.078
	No	664	0.018	0.048	.051
Basic insurance	Yes	468	0.046 ***	0.123 ***	0.139 ***	12.960	.000
	No	56	−0.082	−0.173	−0.173
Family knowledge about health issues	Very high	7	−0.102	−0.302	−0.393	2.308	.055
	High	80	0.109 *	0.221 *	.221 *
	Moderate	381	0.021	0.057	.065
	Low	209	−0.002	−0.004	−0.004
	Very low	108	0.019	0.051	.055
Level of development of the residence	The lowest	242	0.013	0.034	0.038	1.587	.175
	Low	158	0.008	0.027	.046
	Middle	95	0.036	0.106	.135
	High	127	0.141 ***	0.272 ***	.272 ***
	The highest	179	0.108 ***	0.213 ***	.213 ***

Note. *, **, and *** show significance at the levels of 10%, 5%, and 1%, respectively.

Table 4.

Inequality Decomposition for Outpatient Health Services Utilization.

Variables	Marginal effect	Elasticity	Concentration index	Absolute share	Relative share
Gender of the head of the household (Ref: male)
Female	−0.216 **	−0.063	0.049	−0.003	1.08
Education of the head of the household (Ref: below high school diploma)
High school diploma and higher	−0.007	−0.017	0.039	−0.001	0.37
Marital status of the head of the household (Ref: married)
Divorced/widow	0.067	0.129	0.051	0.007	−3.86
Single	0.119	0.230	−0.040	−0.009	5.38
Having a person with a chronic disease in the family (Ref: yes)
No	0.001	0.001	0.066	0.000	−0.04
Having a person with a disability in the family (Ref: no)
Yes	−0.095 **	−0.133	0.085	−0.011	6.58
Basic insurance (Ref: no)
Yes	0.104 **	0.146	0.046	0.007	−3.92
Family knowledge about health issues (Ref: moderate)
Very low	−0.271 *	−1.457	−0.102	0.149	−83.79
Low	−0.085	−0.457	0.109	−0.050	29.09
High	0.006	0.032	−0.001	0.000	0.02
Very high	0.165 ***	0.887	0.019	0.017	−9.84
Level of development of the residence (Ref: middle)
The lowest	−0.077 **	−0.338	0.013	−0.004	2.56
Low	0.061	0.268	0.008	0.002	−1.25
High	−0.206 ***	−0.904	0.141	−0.127	74.04
The highest	−0.309 ***	−1.355	0.108	−0.146	85.48
Error Term					0.19

Note. *, **, and *** show significance at the levels of 10%, 5%, and 1%, respectively.

Findings

Table 1 shows the participants’ demographic features, including length of residence in Tehran; family size; the age, occupation, and education of the family’s mother (woman responding); as well as socioeconomic status and OHSU for the families. Results show that 63.61% of participants have utilized outpatient health services during the past month. According to the household asset index, 21%, 56.5%, and 33% were in the lower, middle, and upper classes, respectively.

Table 2 describes the OHSU among the different socio-demographic subgroups. Based on the descriptive statistics, OHSU rates in male-headed households, households with heads of household with high school diplomas and higher education, households with disabled members, households with a member who has a chronic disease, households with insurance coverage, those with an average level of health knowledge, those residing in areas with a low level of development, and households with moderate socioeconomic status had higher OHSU than that in other socio-demographic groups.

The significance of the differences in OHSU among different socio-demographic subgroups was tested using the chi-square test. According to the results, factors including the gender of the household head, having a person with a disability in the household, family health knowledge level, and the development level of the residential neighborhood were variables that showed significant differences in health service utilization among the households.

To calculate inequality in OHSU among Iranian households, concentration, Wagstaff and Erigers indices of inequality were calculated for those socio-demographic subgroups where differences were observed in the previous step. To calculate different indices of inequality, the rank variable of socioeconomic status of households was calculated for different socio-demographic subgroups and used as the basis for ranking the sample households. To calculate different inequality indices, each household was weighted based on the household size. According to the results, the concentration index has a positive sign in all 3 indices. Thus, it can be stated that OHSU is concentrated among households with a higher socioeconomic status. Table 3 shows the inequality indices and the significance of the difference between the inequalities of each subgroup. The results show that in some cases, OHSU has been in favor of the households with lower socioeconomic status (subgroups for whom inequality indices had negative signs). Nevertheless, those were not statistically significant. Thus, it could be argued that the OHSU has been concentrated among groups with higher socioeconomic status. Differences in inequality among the households of each subgroup were tested based on the F-statistic. Accordingly, it is observed that inequality in OHSU was significant only when the households were grouped in terms of having a disabled member and having basic health insurance coverage. Other socio-demographic variables did not lead to a significant difference in inequality.

Table 3 shows that having a member with a chronic disease, having basic health insurance coverage, and family health knowledge level were variables that lead to a significant difference in the households’ OHSU. However, other forms of the households grouping could not explain significant differences in their inequality.

Table 4 shows the results of inequality decomposition and the share of the explanatory variables in OHSU. The absolute share of each variable in inequality has been calculated by multiplying the respective elasticity (the explanatory variable’s weight) and its concentration index. In addition, the relative share of each variable has been calculated according to its descriptive ratio from the definitive component of the concentration index. Living in districts with very high and high levels of urban development is the major factor in the concentration of OHSU in favor of the privileged groups. However, health knowledge level also plays a pivotal role in inequality of OHSU. As it can be seen from the results, inequality in the health knowledge level has been in favor of the less privileged groups. In this way the very low level of health knowledge may result in unnecessary demands among the less privileged households and their referrals to the healthcare centers.

Having a disabled member in the household and basics insurance coverage are also variables that should be considered. Access to health services among the households with such characteristics has led to a higher concentration in favor of families with higher and lower socioeconomic status, respectively.

Figure 1 show the absolute and relative shares of various explanatory variables for inequality in OHSU and their significance level.

Figure 1.

The main determinants of inequality in outpatient health services utilization.

Discussion

Irrespective of the type of healthcare system, equitable access to healthcare services is considered a fundamental goal. ²⁴ In response to this importance, this study aimed to examine the socioeconomic inequality in outpatient healthcare service utilization among households living in Tehran. Our findings revealed that disadvantaged households had lower utilization of outpatient care compared to advantaged households, which is consistent with other studies conducted at the national and international levels.^{14,27,42,67-70} The lower rate of OHSU among households with lower socioeconomic status is concerning and should be addressed, as previous studies have suggested.^27,71-73 Despite essential healthcare reforms, Iran’s healthcare system has not succeeded in providing equal access to healthcare services for all citizens regardless of their socioeconomic status.

This study found that health service utilization is skewed toward groups with higher socioeconomic status in male-headed households, while among the female-headed households, the utilization had a decentralized distribution. Due to higher income and better job opportunities, male-headed households have higher socioeconomic status and a larger wealth index than female-headed ones. Thus, owing to their higher financial ability and the possibility of purchasing supplementary health insurance, HSU is higher in male-headed households than in female-headed ones. Significant inequality in health service utilization was observed only for households with a married head, with more deprived classes being disproportionately affected. These findings are consistent with previous studies ⁷⁴ that reported higher dental service utilization among male-headed households and households with a married head. The education level of the households’ heads was also found to be a factor in OHSU, which was in favor of the more privileged households. However, no significant differences in the inequality of OHSU were found in households with a university-graduated head. These findings are consistent with Hassanzadeh et al, ⁵⁹ and Zakeri et al ⁷⁵ which showed that less educated individuals had more OHSU compared to highly educated ones. Unlike our findings, Homaie Rad et al ⁷⁶ and Rezaei et al ²⁴ showed that when the education level of individuals or heads of households increased, the dental health service utilization increased as well, with this inequality being to the detriment of the less privileged classes in terms of their socioeconomic status. The reason for this difference could be the unified financial abilities of people of higher education levels and their higher ability to purchase more dental services as luxury and expensive services. This difference could be explained as, the current study considered all outpatient health services instead of dental services.

This study found that households with disabled or chronically ill members experience significant healthcare inequalities favoring higher socioeconomic status groups.^24,77,78

Accordingly, it is necessary for households with lower socioeconomic status, who have a member with a disability or a chronic disease, to be considered as the target groups in policymaking to facilitate their access to health services. The study also identified basic insurance coverage as a significant factor in healthcare inequality, with low and middle-socioeconomic-class households being the most affected.^10,59,79,80 Policymakers must prioritize these vulnerable groups and ensure that basic insurance coverage translates to equitable access to healthcare services.

Low health literacy and insufficient information from healthcare centers at the place of residence, can lead to the non-utilization of health services. Our study found significant differences in health service utilization among households with different levels of health knowledge and significant intra-household inequality among households of different socioeconomic subgroups. Expressly, different levels of health knowledge led to a significant difference in health service utilization in favor of the less privileged groups. It could be inferred that very low levels of health knowledge have created a stronger and higher feeling of (mostly unnecessary) need among the less privileged groups, thereby causing them to make more demands and referrals to health centers. Therefore, policymakers could reduce the burden of referrals to the healthcare system by increasing health knowledge levels among less privileged social groups. The reduced burden of referrals to the healthcare system, make it possible to provide more and better services to targeted groups through reorganizing the resources.

Households living in developed neighborhoods experienced significantly different inequality in OHSU. However, OHSU in more developed neighborhoods was more concentrated among higher socioeconomic classes, this inequality observed among households living in more privileged districts could be due to the heterogeneity of socioeconomic conditions within these households, in other words, there are more differences in the income range and type of occupation in privileged and affluent districts than in less privileged ones.^69,77,81

Besides, it seems that availability and physical accessibility to health services are different based on the development level of the zones. The condensation of health centers resulting easier access to health services in developed neighborhoods. The findings of Geo et al (2020) also confirm these results. ⁷⁷

Socioeconomic inequality can lead to adverse health outcomes, such as a lack of access to healthcare services, unfriendly healthcare systems, and insufficient information and education. Accessing healthcare services may require multiple trips to distant providers, leading to inequality in outpatient health service utilization. Future studies should investigate the impact of these variables. Developing telehealth services and prioritizing “location,” “public transport,” and “free services at the point of delivery” could improve healthcare access and reduce health inequalities.

This study had some limitations. Since the mother of the family was selected as the informed respondent in this study, the mother as human subject may lead to potential recall bias. In order to reduce the effect of this limitation, it is suggested that in future studies, the need and status of utilizing health services in each family member should be investigated individually.

Additionally, this study only examined outpatient service utilization and did not consider inpatient service utilization or specific subgroups such as migrants, prisoners, and the homeless. Future studies should consider using all household members as respondents to reduce potential recall bias.

Conclusion

The utilization of a decomposition method is essential in analyzing complex issues, particularly in healthcare utilization, and it enables a more comprehensive understanding of the relationship between an individual’s health status and their utilizing of health services. The results of our study showed that having a member with a chronic disease, having basic health insurance coverage, and family health knowledge level were the most significant factors that lead to a significant inequality in the households’ OHSU.

It is vital to ensure that everyone, regardless of their socioeconomic status, has access to quality healthcare services, as healthcare is a fundamental human right. By examining factors such as health literacy, disability, and chronic illness status, policymakers can ensure that vulnerable groups can receive the necessary healthcare services they need. Additionally, promoting health literacy among the lower socioeconomic classes can reduce the burden of unnecessary healthcare utilization. These insights can inform policymakers to develop effective strategies for reducing healthcare disparities and promoting social justice, ultimately improving healthcare access and reducing inequalities between different socioeconomic groups.