NHA provides a framework to collect, compile, and analyze such data on all types of health spending in a country. As, institutionalization of NHA provide a strong evidence base for decision making in order to creating new resources, reallocating existing resources, improving efficiency of current spending and improving the equity in health financing. International reports show that developing countries such as Turkey, Philippines and Malaysia regularly use NHA framework to enable the government to identify health system issues and rearrange the policies accordingly. NHA also can help to successful implementation, evaluation, and management of health reform . Meanwhile, one of policy implications of NHA is how the indicators are varied across different provinces within a country, which aspires equity in health financing as the main concern worldwide , and inequity in health expenditures is one of the factors affecting the health of households. Therefore, this study aimed to investigate the inequality in the indices of the health care system financing agents from 2008 to 2016, based on population and the number of service providers.
Overall, we found that there is inequality in the resources allocated by financing agents studied in Iran. Moreover, the private sector particular the subset of OOP had the highest inequality among main financing agents. In case of public expenditures, we also delineated that highest inequality in resources distribution is related to SSIO. Surprisingly, the inequality measured by the number of service providers in each province was less than the inequality per the population base. The results were discussed in detail as follows:
According to the results, the distribution of THE was relatively unequal or moderately unequal, and its distribution process was more or less incremental in terms of the population, which inequality was higher than inequality in terms of the number of health care providers. More precisely, inequality in the distribution of resources in terms of population is greater than equality based on the number of health service providers. One of the main reasons seems to be this issue that allocating funds to the provinces by the main agents are relied on the structure of service provision. However, several other studies demonstrated that health allocation patterns based on the geographical conditions, population, disease burden, and the need in each region are better than the health allocation based on the number of health care providers. The results of a study on the allocation of resources to the health system in Iran show that the basis for allocating more resources is based on the defined service delivery structures and that consequently, demographic and epidemiological indices in this model are deemphasized, which is consistent with the results of this study [31, 32]. As a result, it is suggested that policymakers should pay more attention to the variables associated with demographic, epidemiological, and geographical conditions in the allocation of health system resources.
The results also show that inequality in the distribution of private health expenditures was higher than inequality in the distribution of public health expenditures, and its trend showed a sharper increase. Hence, the pattern of inequality was similar in both bases of GC (i.e., population and the number of health service providers) in terms of the main agents of financing, including MSUs, HIO, and SSIO. This issue can be due to at least three reasons. Firstly, the distribution of disease burden varies from one region to another region, and this is more important, especially for chronic and non-contagious diseases, which have higher expenditures. Therefore, various studies conducted in Iran indicate that inequality in risky behaviors, access to health services, and health outcomes such as mortality and morbidity, are evident in urban, rural areas and different provinces [33,34,35,36]. Secondly, as the main incentive of the private sector in delivering health services is the attained profit, regions with more facilities, higher development level, and stronger infrastructures provide more potential opportunities for private sector development. Thus, these sectors focus on further investment in these provinces. As a result, regarding the higher tariffs of the private sector and the lack of appropriate insurance coverage in the private sector, this could increase OOP spending compared to other areas.
Evidence suggests that the services provided by the private sector depend on the mechanism and type of services covered, e.g., whether they are specialized or general, or therapeutic and preventive. Furthermore, the method of payment can affect the access of people to need-based services. Even in most cases, due to the incentives for profitability, financial access is limited, especially for the underprivileged and less developed regions , which requires targeted policy and planning, focusing on strategic purchasing of health services by governments to ensure quality and affordability. Thirdly, there are some inequalities in the distribution of health facilities and human resources that can lead to some shortcomings in access to these services in some areas. Consequently, people go to other provinces to receive services, and this increases OOP spending in the destination provinces. Some studies conducted in Iran delineated inequality in the distribution of some health resources and facilities among the country’s provinces [38, 39]. It appears that HTP interventions have not been effective in the balanced distribution of HR in different provinces and cities of the country.
Considering the years before and after the HTP implementation, the results of our study showed that following the beginning of the plan in early 2014, the government allocated significant resources from the targeted subsidies and part of the increase in the value-added tax to the health sector. Nevertheless, it seems that due to adding these new resources, the inequality in the distribution of public health decreased compared to the year before its implementation. However, inequality in the distribution of private sector resources increased after the implementation of this plan. In the later years of HTP implementation, due to the unmet financial resources by government for this plan, a relative increase in the inequality in public and private expenditures was observed, which was also consistent with other studies [21, 40]. This increase seems to be due to interventions incorporated in HTP were mainly focused on health care providers affiliated with MSUs, and other public sectors such as SSIO, medical centers affiliated with armed forces private sector were excluded. We also concluded that the both distribution of resources based on the population base and the number of health services providers by MSUs has less inequality than basic health insurers (i.e. HIO and SSIO).
Among the main agents of the provision of basic health insurance, HIO had lower inequality in the distribution of resources compared to the SSIO. The probable cause of this difference seems to be that the SSIO, in addition to indirect treatment, provides health care services through direct treatment focused on its customers. Due to the unequal population with health insurance coverage, the distribution of direct treatment centers in provinces of Iran is unequal, and most centers providing direct health care are located in the center of industrial provinces. Therefore, this misallocation may be a reason for inequality in the resource distribution of this insurance organization compared to that of HIO in provinces. Therefore, health insurance policy integration as well as the use of strategic purchasing in basic health insurance, based on the demographic needs of each region, can improve the equity in the distribution of health insurance resources at the provincial level.
The results of the disparity index from the OOP health expenditures showed that during the studied years, the disparity rate from the target index of at least 30% of the OOP according to the fourth and fifth NDPs did not have a regular trend. In conclusion, the disparity of the OOP was decreased after the first year of the HTP implementation as compared with the previous years. This relative increase in the second and third years showed that in the subsequent years, due to the lack of resource allocation to continue the plan and instability of government funding, it led to further disparity and, consequently, distancing from the target of the fifth NDP. Furthermore, the results obtained by Homaie Rad et al. (2017) on the urban family physician program indicated that the implementation of this program not only did not change the OOP compared to the previous years but also increased inequality in the OOP payments . This is due to the incomplete implementation of the family physician program and its related components as well as severe financial constraints in the aftermath of economic instability. It should be noted that necessarily applying economic reforms cannot improve the equity in health financing, such as what was concluded in a study concluded in Iran indicating targeted subsidies law could not improve the equity in health financing .
Study strength and limitations
This study is one of the first studies investigating the inequality in the distribution of health resources in terms of financial resource agents for almost a decade at the provincial level in Iran. Although this study was based on the NHA indicators, some indicators such as donors support, non-profit institutions serving households, banks, and other insurance organizations, including the armed forces and private companies, were not included. However, these indicators consist of approximately 15% of THE [25, 43]. Thus, the indicators with a greater share of funding, including SSIO, HIO, MSUs, and OOP spent by households, were included in our study. Another limitation of the present study is the lack of access to data on the number of service providers in 2016; therefore, the GC was calculated based on the number of service providers for health financing agents from 2008 to 2015.