Assessing the inequalities in healthcare resources in China after medical reforms: a study from 2010 to 2019

Introduction

Health equality aims to provide everyone with identical opportunities, care, and services. Equitable access to healthcare treatments and consultations symbolizes a country’s medical standard. The ability of a country or region to provide adequate healthcare resources for its residents has long been a focal point of concern, particularly in developing countries such as India, Vietnam, and Thailand (1-4). Existing research has highlighted issues such as the shortage of healthcare professionals and emergency facilities (2,3). Historically, China also faced challenges with insufficient healthcare resources to meet the demands of its population. However, as the country has undergone economic development, there have been continuous efforts to increase healthcare resources and improve the equality of distribution in healthcare services (5,6). The Chinese government increased the healthcare budget’s share of gross domestic product (GDP) from 4.1% in 2008 to 6.8% in 2018, aiming to reduce healthcare availability inequality (7). Notably, in 2009, a significant medical reform policy was introduced to enhance healthcare service levels and address disparities in healthcare resource distribution. According to a study, the number of healthcare institutions per 10,000 people rose from 6.78 in 2008 to 7.16 in 2013. Similarly, the number of health technical personnel per 10,000 people increased from 41.48 in 2008 to 52.92 in 2013 (7).

In addition to addressing healthcare resource inequality, we emphasize the importance of equity in this study. According to the World Health Organization, health equity means the absence of unfair, avoidable, or remediable differences among populations, regardless of social, economic, demographic, or geographic factors (8). This study focused on individuals who must travel long distances to receive treatment. This research investigates the impact of geographical factors on healthcare equity and examines whether there is inequity in healthcare accessibility between areas with varying population densities. In countries with large territorial expanses like Canada and China, an equal distribution based solely on population does not ensure equitable access to healthcare. In Canada, the distribution of healthcare professionals is uneven, with urban areas having a higher concentration of doctors, nurses, and specialists compared to rural regions. Almost one-fifth of Canadians live in rural communities, but they are served by only 8% of the physicians practising in Canada (9). Regions characterized by vast land and low population density may display equitable distributions per capita, yet accessibility to healthcare services is compromised by considerable distances to healthcare facilities. China may face similar issues, but there is a notable lack of related research. Our study aims to analyze whether the accessibility of healthcare resources is equitable under varying geographical conditions.

In 2009, the Chinese government introduced significant healthcare reform measures (10). Existing research indicates improvements in the equity of healthcare resource distribution following these reforms. However, disparities in equality persist between developed and developing regions (11). The government enacted a series of new policies to address this enduring issue. The ‘Notice of the General Office of the State Council on Issuing the Outline for the Planning of the National Medical and Health Service System (2015–2020)’ was promulgated in 2015, with the ‘Comprehensive Reform of Public Hospitals’ being unveiled by the National Health Commission of the People’s Republic of China in 2017 (12). These initiatives were deliberately targeted at elevating the standard of medical care in public hospitals and revamping medical insurance and payment frameworks. The overarching goal of these reforms was to guarantee equitable access to medical services for all segments of the population and to ensure that the provision of medical supplies meets the healthcare demands of the public. Due to the ongoing nature of healthcare reforms, research must encompass long-term data to identify changes resulting from successive reforms. Consequently, we examined data over a 10-year period to clearly illustrate trends in healthcare resource distribution disparity. The primary aim is to analyze the trajectory and transformation of equality in healthcare resource distribution during the healthcare reform era.

Several statistical methods have been developed to assess the equality of healthcare resource distribution. The Gini coefficient and Theil index are this domain’s most applied methods (13-15). Research indicates that the Theil index has shown the equality of China’s healthcare resource distribution, with its values progressively approaching the baseline, which signifies an equitable distribution regarding healthcare institutions, medical personnel such as doctors and nurses, and other relevant indicators. The Theil index is particularly advantageous because it not only assesses overall equality at the national level but also allows for the decomposition of inequality to understand the contribution of disparities within and between regions. This feature is crucial for identifying areas with acute inequality issues (6,13,16). Therefore, in this study, we adopted the Theil index as the statistical method to investigate inequality in healthcare resource distribution, discern the underlying causes and provide substantiated recommendations for policy intervention.

The Theil index is commonly used to evaluate the distributional equality of healthcare resources, focusing on the proportion of the population as a factor in its computation. This method, however, has limitations because it fails to consider geographical dimensions such as land area. The original formula for evaluating healthcare resource distribution primarily assesses equality based on population. To enhance this evaluation, we have incorporated a geographical area factor into the Theil Index. This modification enables the new formula to reflect equality and equity in the distribution of healthcare resources across the country. To this end, this study proposes an amendment to the traditional Theil index formula, incorporating land area as an additional factor to reflect the realities of healthcare resource allocation equity.

Methods

Data sources and setting

This study utilized data from the open-access database of the China Statistical Yearbook. The database includes information on healthcare resources, covering hardware resources such as investment amounts, the number of medical institutions, the number of hospital beds, and human resources, including the number of doctors and nurses. We extracted data from the China Health Statistical Yearbook (2010–2019), which covers 31 provinces, autonomous regions, and municipalities. In addition, areas in China were divided into four segments—northeastern, eastern, western, and central—considered Category 1. Moreover, regions of China were divided into urban and suburban areas according to Category 2. The quality of healthcare resources was evaluated based on these two segments. The data used in this study were obtained from publicly available sources. Although this study utilized publicly available data, it was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki (as revised in 2013).

Based on the economic situation, geographical location, and descriptions in the China Health Statistical Yearbook, the 31 provinces, autonomous regions, and municipalities of mainland China were separated into four groups (Table 1): the northeastern, eastern, central, and western regions. The northeastern region includes Heilongjiang, Jilin, and Liaoning (3 provinces). The eastern region included Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, and Hainan (10 provinces and municipalities). The central region includes Shanxi, Anhui, Jiangxi, Henan, Hubei, and Hunan (6 provinces). The western region included Inner Mongolia, Chongqing, Guangxi, Sichuan, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang (12 provinces, autonomous regions, and municipalities). The institutions included urban hospitals (hospitals and community health service centers) and suburban hospitals (township hospitals, village clinics, and outpatient clinics). Certified doctors and nurses were also included. Medical investments came from government financing.

Statistical analysis

Theil index is considered as one of the most comment used method to assess the equality of social issues (17,18), because it presents the distinction among groups and shows the contribution of equality from within and between groups.

Although the Theil index assesses the quality of health resources, it can be used to evaluate inequality contributions from within regions or between groups (19). The Theil index method considers the population factor but not the land factor. In this study, population and land were viewed as factors. Therefore, the Theil index formula was modified by adding the land factor to assess the inequality and inequity of healthcare resources.

The five indicators chosen were the amount of investment and the number of institutions, doctors, nurses, and beds in health institutions. The Theil index assesses the equality level of the distribution of healthcare resources. T is a relative indicator; no universal assessment standard for inequality levels is available (14). The T value ranges between 0 and 1, with a smaller T value indicating a more equitable condition. Specifically, the closer the value is to the x-axis, the more equal the situation (17,18). T was calculated as follows:

T=∑i=1nPilogPiYi[1]

Pi: Proportion of every province’s population accounting for China’s overall population.

Yi: Proportion of health resources owned by every province accounting for the total number of health resources nationwide.

The Theil index can be decomposed into two components to describe inequality “within” and “between” subgroups. The formulae are as follows (17,18):

Tw=∑g=1kPgTg[2]

Tb∑g=1kPglogPgYg[3]

T=Tw+Tb[4]

Tw represents the fairness of health resource allocation in a targeted region, Tb represents the degree of equality between the different regions, and Pg and Yg have the same meanings as Pi and Yi.

T′=∑i=1nAilogAiYi[5]

In the above formula, Yi represents the health resource, Pi represents the population of each unit, and Ai represents the square of Unit I. This study intends to introduce the land factor into the Theil index and further assess the inequity situation. The original Theil index formula considers the distribution of healthcare resources in a population. First, we changed the factor of population Pi to Ai, which provides a new Theil index Eq. [5] with a land factor (Ai) to evaluate the distribution of healthcare resources on the land.

T″=T−T′=∑i=1nPilogPiYi−∑i=1nAilogAiYi[6]

Furthermore, subtracting Eq. [5] from Eq. [1] gives the T″ of Eq. [6]. If the results are greater than zero, the contribution of the population to inequality is greater. In contrast, if the results are less than zero, the contribution of land to inequity is greater.

T‴=T+T′=12(∑i=1nPilogPiYi+∑i=1nAilogAiYi)[7]

Second, the addition of Eqs. [1] and [5] gives T‴. Correcting the formula yields values between 0 and 1. The results showed disparities in China concerning both population and land. For the two formulae, the explanations of the results are similar to those of the original Theil index. Regardless of whether the results are greater than 0 or less than 0, the closer the line is to the x-axis, the greater the disparities of the healthcare resources.

Results

The Theil index results for the national situation

Table 2 and Figure 1 display the Theil index for the allocation of national health resources across five indicators. From 2010 to 2019, the indices for government investment, healthcare institutions, and beds were consistently below 0.03, indicating achieved equity in financial input and healthcare infrastructure, with the bed indicator showing the lowest values among them. These three indices remained stable over the observed period. In contrast, the indices for doctors and nurses, which initially ranged from 0.145 to 0.095 between 2010 and 2015, exhibited a marked decline to 0.103 by 2012, followed by a rise to approximately 0.126. After 2014, these indices stabilized at approximately 0.097, maintaining a value roughly double that of the other three indicators.

Figure 1 Theil index of healthcare resource allocation from 2010 to 2019. T, the value of Theil index.

The Theil index results for Category 1

Figure 2 shows that the northeast region, excluding government investment, has the lowest Theil index for the distribution of medical resources among the five regions. For the number of medical institutions, the blue line representing the northeast region, although experiencing fluctuations over the 10-year period, remains significantly lower than other regions (Table 3 shows it was 0.0072 in 2019). Particularly regarding human resource distribution, the northeast region has remained stable and close to the x-axis over the 10 years, with Theil indices consistently below 0.020 (Table 3).

Figure 2 Theil index of healthcare resource allocation by areas and years (Category 1). Tg, the value of Theil Index in different regions.

For the central and western regions, government investment and the number of beds show a level of equality similar to that of the northeast. Government investment in the central region is the lowest, while the western region is slightly higher than the central and northeast regions. However, the Theil indices in both regions are less than 0.0080 (Table 3). Regarding the number of medical institutions, the western region demonstrates better equality in the distribution of medical resources compared to the central region. Still, the Theil index in the central region has decreased over the decade, reaching 0.017 in 2019. Regarding human resources, the central region displays significantly better equality than the western region, with its yellow line closer to the northeast and a decreasing trend over the decade, reaching 0.020 for doctors and 0.019 for nurses in 2019 (Table 3). Although the western region has also shown a decreasing trend in the inequality of human resource distribution over the decade, its Theil indices in 2019 remain noticeably higher than those of the central region (0.12 for doctors and 0.089 for nurses).

Being a developed area, the eastern region shows the highest inequality distribution indices among the five regions for all four indicators except the number of beds. However, the values for all four indicators show a decreasing trend. The Theil index for the number of medical institutions decreased to 0.033 in 2019, still about twice that of the central region (Table 3). Regarding human resource distribution, doctors in the eastern region decreased to a level similar to that of the western region in 2019, reaching 0.012. However, the inequality index for nurses remains significantly higher than that of the second highest, the western region, at 0.12 in 2019. Table 3 shows that the inequality in all five regions primarily stems from within-group disparities, with an intra-group contribution rate of around 80%.

The Theil index results for Category 2

Analysis of the data in Table 4 and Figure 3, which categorizes China into urban and rural sectors (Category 2), reveals that from 2010 to 2019, disparities in healthcare resource allocation were predominantly attributed to between-group differences, particularly in institutional factors. By 2019, intergroup disparities contributed 93% of the inequality. For the bed factor, there was a notable shift from within-group to between-group contributions over the decade: in 2010, 92% of inequality was due to within-group factors, yet by 2019, 59% was attributed to between-group factors. In contrast, for doctors and nurses, there was a discernible transition from between-group to within-group contributions, with the proportion of within-group contributions increasing significantly by the end of the period (93% for doctors and 83% for nurses).

Figure 3 Theil index of the proportion of differences in the contribution by Category 2 and years.

The Theil index results for the modified formula

As shown in Table 5 and Figure 4, the results derived from applying Eq. [5] confirm the trends observed using the Theil index equation that considers only geographic area. From 2010 to 2019, the distribution of hardware resources such as investments, systems, and beds remained relatively stable, ranging between 0.21 and 0.28, with the Theil index for investment resources being the lowest. The distribution of human resources in 2010 was similar to that of hardware resources. Still, over the subsequent nine years, the Theil index for human resources fluctuated, significantly surpassing the distribution index for hardware resources by 2019 (physicians: 0.37, nurses: 0.39). Furthermore, comparing the results in Figures 1,4 reveals that the equality of medical resource distribution is very high in terms of population. However, when considering only geographic areas, the fairness of the distribution of medical resources still requires improvement.

Figure 4 The trend of the modified Theil index (T′).

Using Eq. [6], as depicted in Table 6 and Figure 5, the analysis yielded consistently negative values below the x-axis, indicating stable trends across all factors. The bed indicator was the farthest from the x-axis, followed by the institution, investment, doctor, and nurse indicators, with their respective values ranging from −0.34 to −0.15. Notably, in 2017 and 2018, the doctor and nurse lines nearly converged.

Figure 5 The trend of the modified Theil index (T″).

In contrast, results from Eq. [7] (Table 7 and Figure 6) showed that the investment, bed, and institutional factors remained stable throughout the study period. The investment indicator was closest to the x-axis, with the bed indicator positioned between the investment and institution lines, ranging between 0.11 and 0.15. The trends for doctors and nurses paralleled each other, remaining stable from 2010 to 2014, with the nurse indicator marginally closer to the x-axis at approximately 0.18 compared to the doctor indicator at approximately 0.19. However, both exhibited upward fluctuations from 2014 to 2017, culminating in a slight increase to 0.24 by 2019. During this latter period, the trends for doctors and nurses were closely aligned.

Figure 6 The trend of the modified Theil index (T‴).

Discussion

This study demonstrates that government investment in healthcare and the distribution of treatment facilities and hospital beds remains remarkably steady and closely aligned with the x-axis. This indicates an equal availability of healthcare resources. The equality in these three distribution aspects signifies that the ongoing healthcare reforms have effectively improved the allocation of hardware resources in the medical sector, achieving a fundamental level of equality.

In contrast to the relatively stable and equitable distribution of hardware resources, the distribution of human resources, after experiencing fluctuations, has stabilized at a level 0.1 higher than that of hardware resources. Although a level of 0.1 is generally considered relatively fair in equity studies, there remains room for improvement in the fairness of human resource distribution compared to the hardware resource level. The availability of healthcare resources in China has achieved a commendable level of equality nationwide, a finding that aligns with previous research (6). Despite the general downward trend, the doctor and nurse indicators exhibited variations indicative of increasing equality. These variations stemmed from changes in the statistical methods of the Chinese Statistical Office post-2011, a response to the evolving healthcare landscape.

The equality in the distribution of human resources mentioned above experienced a significant rise and then a decline from 2012 to 2014. This fluctuation is likely due to the formalization of regulations governing the qualifications of medical personnel in China. In the early stages of China’s development, when medical resources were scarce, doctors who had not received formal medical school training but had undergone short-term training to perform basic medical care, as well as traditional Chinese medicine practitioners from generational families without Western medical licenses, were all counted as doctors in national statistics. However, as medical standards improved and healthcare systems were refined, the government introduced certification for traditional Chinese medicine practitioners and, since 1999, required all doctors to hold a professional license to practice. Consequently, national statistics began counting only those with a professional doctor’s qualification. This policy and statistical methodology change led to a decrease in the equality of doctor distribution in 2013. Nevertheless, as doctors who wished to continue their practice obtained their professional qualifications, there was an increase in the number of licensed doctors in 2014, leading to improved equality. This stabilization in the following five years reflects the overall enhancement in the equality of doctor distribution.

Within the context of regional disparities (Category 1), the northeast region demonstrates significantly greater equality compared to other regions. As a traditionally industrially developed area, the northeast adjusted its industrial structure in response to national environmental protection policies. Simultaneously, the region experienced a significant population decline due to migration to the rapidly developing coastal regions. The traditional Theil index reflects the equality of medical resource distribution under the population index, which may explain why the northeast region exhibits the most equal distribution of medical resources.

The above economically developed coastal region, the eastern region, however, shows relatively weaker equality in the distribution of medical resources among the four regions. This may be attributed to its rapid economic development, which has attracted a large influx of talent, thus outpacing the development of medical resource distribution to meet the population’s needs. A study on healthcare resources in the eastern regions also mentions the potential for unequal distribution in developed areas (20).

The central and western regions, being slower in economic development, have seen significant improvements in medical resource availability due to increased government investment highlighted in healthcare reforms. The increased emphasis on investing in these regions is evident in the substantial enhancements in the number of institutions and hospital beds, achieving high levels of equality. Additionally, the talent attraction policies within healthcare reforms have also proven effective, resulting in notably higher equality in the distribution of human resources in the central region. Published studies have also shown improvements in the quantity of healthcare resources in the western regions of China (13,16,20,21). Additionally, within-group contributions dominated the observed disparities in healthcare resource allocation, implying that future governmental strategies should address intragroup variances. Other scholarly work corroborates this study’s findings (13).

In the second category of analysis, the distribution of healthcare infrastructure resources exhibited lower Theil index values, with contributions to this inequity primarily arising from intergroup disparities. Urban centres typically boast more health institutions than rural areas, suggesting that targeted government investment could mitigate the urban-rural divide. For human resource indicators, such as doctors and nurses, there was a notable increase in the proportion of contributions from within-group disparities. Conversely, the within-group contributions for institutions and beds indicated a declining trend, consistent with findings from another study (16).

In discussions of healthcare resource equality, resource availability has traditionally been the focal point for healthcare availability. However, in countries with large geographical areas, extensive land challenges equitable healthcare service distribution due to the potential for longer distances between individuals and medical institutions. Most existing studies have concentrated on the number of healthcare facilities and workforce ratios per capita, which may suffice for countries with smaller land areas.

This study integrates land as a pivotal factor in assessing healthcare resource allocation inequality in China, a dimension not fully addressed in previous analyses (16,22). When considering both population and land area, we found that the distribution of medical resources is not entirely satisfactory. Medical resources, particularly human resources, are concentrated in a few densely populated areas. In contrast, vast but sparsely populated regions lack sufficient medical resources to ensure timely and adequate treatment for local residents. China continuously advances and deepens healthcare reforms, including hospital and medical insurance system reforms. These reforms aim to implement hierarchical diagnosis and treatment, alleviate the pressure on large hospitals, and allow residents to access timely medical care locally. However, the overly centralized distribution of medical resources hampers effective management and allocation. It is essential to decentralize and distribute high-quality medical resources to meet the needs of patients for accessible, timely, and effective medical care.

Canada also faces challenges accessing healthcare in remote regions due to its vast geographical area. To address these issues, the Canadian Institute for Health Information (CIHI) supports developing policies to improve healthcare conditions in these areas. These policies include increasing healthcare investment, encouraging healthcare professionals to practice in these regions, and strengthening telemedicine infrastructure (23). A book provides a comprehensive analysis that while social determinants of health are crucial, the political determinants often underpin these social factors and must be addressed to achieve true health equity (24). Therefore, implementing well-structured and progressively advancing policies will play a crucial role in addressing and mitigating healthcare inequities.

Acknowledging the suboptimal equality outcomes upon incorporating the land factor into the Theil index, it remains impractical for the government to indiscriminately construct additional health facilities in remote, sparsely populated areas, as this could lead to resource misallocation. However, establishing mobile medical service centres in sparsely populated regions could be a viable solution. Since patient mobility is limited, mobile hospitals could bring healthcare services closer to them, thus reducing the difficulty of accessing care and improving equity to some extent. Additionally, expanding the scope of practice for healthcare professionals in these areas could help address the issues of workforce shortages and instability. Increasing the number of general practitioners would also enhance healthcare accessibility in such regions.

Moreover, improving the medical skills of local doctors could allow patients to receive necessary care locally. It would also be beneficial if high-level physicians from developed areas could regularly rotate to remote and rural areas to conduct medical activities. This would enable patients to access the same quality of healthcare services as those in developed regions, thereby reducing healthcare access inequities.

This research highlights the significance of travel distance to healthcare access as a profound inequality factor. We modified the Theil index by incorporating land area as a key factor in assessing the equity of medical resource distribution. It investigates the extent to which land area influences the equity of medical resource allocation and explores whether policy reforms should address the challenges of geographic regions in providing healthcare services.

Conclusions

Using the Theil index, which considers only population, the equality of medical resource distribution in China from 2010 to 2019 shows satisfactory results for hardware and human resources, although the Theil index for human resources is slightly higher. This indicates that China’s ongoing healthcare reforms have effectively narrowed the disparities in medical resource allocation. Despite varying economic development levels across different regions in China, the distribution of medical resources has reached a relatively fair level. An analysis of medical resource equity was conducted by modifying the formula to incorporate land area. The results reveal that remote areas still face challenges accessing medical care compared to densely populated areas. Future research and policy development should focus more on addressing the healthcare needs of small populations in remote regions.

Acknowledgments

None.

Footnote

Peer Review File: Available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-24-81/prf

Funding: None.

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-24-81/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki (as revised in 2013).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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