The comparison of healthcare utilization inequity between URRBMI and NCMS in rural China

Amartya Sen once noted that “health is the necessary basis for people to realize other capabilities”. Healthcare service, as the post intervention in diseases, is the last “safety net” to guarantee health, and the equalization of healthcare utilization is an important approach to guarantee health equity [29]. Since the reform and opening up of China, the medical industry and technology have developed rapidly, which also led to an increase in medical expenses. As a result, the inequity in healthcare utilization has also intensified among people of different income groups. Compared to high-income groups, low-income groups have a higher need for healthcare services due to their poor health status [20]. But constrained by income, the healthcare utilization for low-income groups is much less than that of high-income groups.

In China, the inequity in healthcare utilization is more serious in rural areas because there are a large number of low-income groups there [23]. Moreover, for low-income groups, a low level of healthcare utilization can consume most of their wealth, so some of them dare not see a doctor when they are ill. To reduce the inequity in healthcare utilization in rural areas, the Chinese government established the New Cooperative Medical Scheme (NCMS) for rural populations in 2003. By bearing a portion of the medical expenses of the insured, NCMS aims to reduce the economic barriers in healthcare utilization and to improve equity of healthcare services for rural populations regardless of individual socioeconomic factors such as marital status, education and income.

Although the coverage of NCMS has been above 90% since 2008, its services coverage and financial protections are less than those of the Urban Resident Basic Medical Insurance (URBMI) available to the urban populations. According to statistics, “urban residents per capita healthcare expenditure paid by medical insurance is around three times as much as that of the rural residents in 2012”.¹ The segmentation of the urban-rural medical insurance scheme has become a main factor that caused the urban-rural inequity in healthcare utilization and it is hardly to ensure the healthcare demands of low-income groups in rural areas [24]. This will be harmful to the implementation of rural revitalization strategies and poses a serious threat to social stability in that China is in a critical period of social and economic transformation.

Therefore, the integration of urban-rural medical insurance has gained governmental attention since 2008, and the government established the Urban and Rural Resident Basic Medical Insurance (URRBMI) based on NCMS and URBMI to make residents participate in the same medical insurance regardless of household registration. In 2016, the central government announced that the URRBMI was gradually implemented nationwide in China. Against this backdrop, comparing the inequity in healthcare utilization between URRBMI and NCMS can provide important information for the implementation and development of URRBMI.

Previous studies have revealed that inequity in healthcare utilization exists widely in the world [4, 6, 16]. Apart from inequity between countries, it also exists between regions within one country [1, 3, 21, 25]. The influencing factors of inequity in healthcare utilization are different because of differences in the economy, medical insurance systems and cultures between countries and regions. In previous studies, scholars investigated the relationship between income and the inequity in healthcare utilization, and they found that the inequity is pro-rich in both developed and developing countries, causing an interest transfer between the rich and the poor [4, 6, 17]. Some scholars have also taken other socioeconomic factors into consideration, and they found that factors like medical insurance can also influence the inequity in healthcare utilization [2, 24].

Theoretically, medical insurance can reduce inequity as it provides a financial support in healthcare utilization and covers a large proportion of medical expenses for low-income groups. In China, although medical insurance schemes are a major payment system for healthcare utilization, there are conflicting opinions about the relationship between medical insurance and healthcare utilization inequity. First, some of the studies claim that the implementation of medical insurance narrowed the gap of healthcare utilization [11‐13]; second, others argue that medical insurance failed to reduce the degree of inequity in healthcare utilization [17, 18, 26‐28, 31], and some scholars also found that medical insurance has intensified the inequity of healthcare utilization instead of narrowing it [2, 23].

The reason that medical insurance fails to reduce healthcare utilization inequity is that the top-level design of the Chinese medical insurance system pays more attention to economic efficiency during the period of primitive accumulation of capital. Studies have shown that the income gap, the fragmentation management of medical insurance and the difference in medical insurance benefits have become the main factors of healthcare utilization inequity [8, 9, 14, 15, 24]. In China, the urban-rural segmentation of the medical insurance system ensures that the rural population experiences lower medical insurance benefits than the urban population. Meanwhile, the proportion of low-income groups in rural areas is higher than that in urban areas. As a result, NCMS cannot meet the healthcare demands of low-income groups and improve the healthcare utilization inequity completely in rural China.

The aim of URRBMI is to provide the same services coverage and financial protections to both urban and rural residents. We assume that the healthcare utilization inequity in rural areas will be reduced as URRBMI improves the medical insurance benefits of rural populations. Referring to URRBMI, some studies found that the opportunity inequity of healthcare utilization was reduced in URRBMI [13], and it also promoted the healthcare utilization of the insured [7, 14, 19, 30]. Meanwhile, other studies implied that the effect of URRBMI on outpatient and inpatient care utilization is not significant [22] and that the rural regional difference in medical insurance benefits still exists under URRBMI [10, 22].

In summary, the previous studies have analyzed the influence of socioeconomic factors on the inequity of healthcare utilization comprehensively, and most of them employed the Concentration Index (CI) to quantify the degree of inequity. Moreover, they also revealed the profound reasons for the healthcare utilization inequity in rural areas by analyzing the urban-rural segmentation of medical insurance, which provided a reference for this article. However, few of them focus on the healthcare utilization inequity in rural areas under URRBMI. Although Ma Chao et al. measured the opportunity inequity of healthcare utilization between urban and rural areas after the integration of urban-rural medical insurance, their research was only limited to three counties in Jiangsu Province of China and did not analyze the inequity within rural areas [13].

Based on the existing studies, this paper analyzes the relationship between URRBMI and the inequity of healthcare utilization in rural areas by comparing the inequity in healthcare utilization under URRBMI and NCMS. Theoretically, the degree of inequity in URRBMI will be lower than in NCMS in that the services coverage and financial protections of URRBMI are better than those of NCMS, but the assumption needs to be verified by data analysis in the next section. This paper is organized as follows:

First, as the fact that healthcare utilization is mainly affected by health status and socioeconomic factors, we use the chi-square test to make a comparison of differences in healthcare utilization and other influence factors among the individuals who were insured by URRBMI and NCMS.

Second, as the dependent variables in this paper are discrete, and the inequity in healthcare utilization is income-related, the binary logistic regression model is employed in this paper to analyze the differences in healthcare utilization among different income levels under the two medical insurance schemes.

Third, the concentration index (CI) and horizontal inequity index (HI index) are used to quantify the degree of inequity in healthcare utilization under the two groups, the decomposition of the concentration index is used to present the contribution of each independent variable to the concentration index.

The urban-rural segmentation of medical insurance schemes has become an important factor of healthcare utilization inequity in rural China. To provide better coverage services and financial protection for the rural population and to reduce the healthcare utilization inequity in rural areas, China began to establish Urban and Rural Resident Basic Medical Insurance (URRBMI) based on Urban Resident Basic Medical Insurance (URBMI) and the New Cooperative Medical Scheme (NCMS) nationwide in 2016. Against this backdrop, it is worth analyzing the changes in inequity in healthcare utilization after the implementation of URRBMI.

Using the national representative data from the China Health and Retirement Longitudinal Study (CHARLS) that was conducted in 2015, this paper compares the inequity of healthcare utilization between the URRBMI insured and the NCMS insured in rural China. The results reveal that there is no significant difference in healthcare utilization under the two medical insurance schemes. When comparing the inequity under the two medical insurance schemes, we find that the richest utilize more outpatient care in URRBMI, but the difference is not significant. Besides, in the NCMS group, the high-income group tends to utilize significantly more outpatient care. The horizontal inequity index (HI index) also shows that there is a pro-rich inequity of outpatient care in both the URRBMI and NCMS groups and that the HI index of URRBMI is larger than that of NCMS; the result is similar to Chen’s study, which also found that the individuals insured by NCMS have a pro-rich inequity in outpatient utilization [3]. The reason may be related to the characteristics of medical insurance policy in China. As the main aim of NCMS is to reduce the financial barriers in hospitalization and the critical diseases of outpatients, and the URRBMI in rural China was established on the basis of NCMS, so its reimbursement policy also places a higher emphasis on inpatient care initially. The individuals who are insured by URRBMI and NCMS in rural China need to pay most of their outpatient fees. Besides, the high-level hospitals mean better quality of healthcare, so people are more inclined to seek healthcare in high-level hospitals if it is possible. As a result, the individuals who are insured by URRBMI tend to seek outpatient care in high-level hospitals because they think the URRBMI has a higher benefit, which leads to higher medical expenses and a serious pro-rich inequity [5]. For the individuals who are insured by NCMS, most of them seek outpatient care in village clinics. Although the expenses of outpatient care are lower overall, some low-income populations still cannot afford of them.

In terms of inpatient utilization, binary logistic regression shows no significant difference among different income levels in both URRBMI and NCMS. However, the horizontal inequity index (HI index) reveals the inequity behind it, that pro-poor inequity exists in inpatient utilization under the two medial insurance schemes, indicating that the poor utilize more inpatient care than the rich. The absolute value of the HI index in URRBMI is larger than the absolute value in NCMS, meaning that the degree of inequity of URRBMI is higher than that of NCMS. Additionally, the degree of inequity in inpatient is higher than that in outpatient care. The result on inequity of inpatient care among those insured by NCMS is different than those reported for other studies, such as Chen (2018) and Pan (2017), who both found a pro-rich inequity in inpatient care in NCMS [3, 18]. The reason for the pro-poor inequity in our results may be that the NCMS has a high reimbursement rate on inpatient utilization. A large proportion of inpatient expenses can be reimbursed, indicating that the insured face a lower price of inpatient services. In this case, the low-income groups will utilize more inpatient care because they are more sensitive to changes in prices than the high-income groups. In addition, as the aim of URRBMI is to increase the rural residents’ medical insurance benefits and to reduce the disparities between urban and rural areas, the central and local governments have arranged lots of resources to finance the URRBMI. Thus, URRBMI has a higher benefit level than NCMS, such as a higher reimbursement rate in inpatient care [7], that caused a greater pro-poor inequity.

It is also important to bear in mind that there is limitation in this paper. Since the implementation of URRBMI is not a ‘natural experiment’, it is hardly to avoid the problem of self-selection in this process. Therefore, the results of this paper are statistical analysis rather than ‘causal’ analysis. Although the PSM method can solve the self-selection problem to some extent by matching the treatment and control groups, it cannot control the unobservable characteristics (such as the willingness of local leaders). Besides, the PSM has several candidate matching methods, such as one-to-one, one-to-four, radius and kernel matching et al. If the PSM method was applied, we must use the matched data to calculate the concentration index of healthcare utilization among the treatment and control groups, respectively. Against this backdrop, only the one-to-one method can be applied. However, the results we get will not be accurate because large numbers of samples are deleted, and it is also difficult to test the robustness of the PSM matching effect only by the one-to-one matching. As a result, the ‘causal’ relationship cannot be attained in this paper. Meanwhile, there are few studies to analyze the inequity of healthcare utilization in URRBMI and to compare it with that in NCMS. It is reasonable to make a statistical analysis firstly, and the future study could further identify the ‘causal’ effect between the inequity of healthcare utilization and URRBMI.

This paper shows that inequity still exists in rural areas after the integration of urban-rural medical insurance schemes, and there is a certain gap between the actual and the expected goal of URRBMI. Specifically, compared to NCMS, the pro-rich inequity in outpatient care and the pro-poor inequity in inpatient care are more serious in URRBMI. Thus, comprehensive measures to reduce the inequity should be taken: first, covering more outpatient diseases in URRBMI, especially chronic diseases; second, setting a reasonable reimbursement ratio in inpatient care to avoid the moral hazard in URRBMI; and third, for the vulnerable groups, special policies such as reducing the deductible and covering them in catastrophic medical insurance could be considered.