Equity and efficiency of public hospitals’ health resource allocation in Guangdong Province, China

As the main body of China’s medical service system, public hospitals serve as the main force in the implementation of health strategies in China. During the past two years of prevention and control of the COVID-19 pandemic, the percentage of patients treated in public hospitals nationwide exceeded 98%, undertaking the most urgent, difficult, and dangerous tasks and demonstrating the essential role of public hospitals in safeguarding people’s lives, health, and social stability [1]. As health resources are the basis for the delivery of health care services, the well-balanced configuration and efficient utilization of public hospitals’ health resources is a prerequisite for the improvement in health output and services in China. The development of health care in China over the past 70 years also shows that unity of equity and efficiency is an essential requirement for the sustainable development of health services [2, 3]. The evolution of medical and health services in China can be divided into three stages. In the first stage, from the establishment of the People’s Republic of China to the introduction of reform and opening up (1949–1978), the government shouldered the greatest responsibility for healthcare to ensure accessible and affordable healthcare for residents in urban and rural areas in the context of the planned economy management model [4]. During this period, the state invested no more than 3% of its GDP in the health field, and yet it was able to meet the basic health care needs of the entire population [2, 5]. Nevertheless, patterns of administration in the planned economic system discouraged the active participation of medical institutions and staff. Common problems such as poor service quality, low operational efficiency, and intense financial pressure imposed on the government hindered the rapid advancement of health services. The second period was from 1979 to 2009. Following the introduction of the market economy, the government reduced its financial investment in hospitals and increased the autonomy of public hospitals so they could operate on their own [2, 4]. Over this period, the medical service quality and operational efficiency of public hospitals improved as a result of increased market involvement. However, due to deficient input from the government and stimulated by policies, hospitals pursued excessive profitability, causing a rapid rise in medical expenses as well as the emergence of the problem of it being “expensive and difficult to see a doctor”. Although progress was made in some areas, the problems exposed were even more serious; on the whole, the health care reform was not successful [6]. Then, a new round of reform was introduced in 2009, which specified the public welfare aspect of healthcare and highlighted the unified pursuit of equity and efficiency. Concretely, the reform aimed to strengthen the government’s accountability for providing public sanitation and basic medical services in the first place and focus on the role of the market mechanism in the second place [7]. Public hospital reform was the core of this round of medical system reform, and China started pilot projects of public hospital reform in 2010 [4]. As one of the first pilot provinces, Guangdong Province, in accordance with national requirements, conducted trials of public hospital reform in Shenzhen (SZ), Zhuhai (ZH), and Dongguan (DG) [8]. As of 2017, public hospitals throughout 21 cities of Guangdong Province had been involved in the reform [9].

Guangdong Province (20°09′ ~ 25°31′ N, 109°45′ ~ 117°20′ E), located in the southernmost part of mainland China, covers a land area of 179,700 km². Guangdong Province is the largest economy in China and has the largest population; the GDP of Guangdong Province in 2021 was 12.44 trillion yuan, ranking first in the country for 33 consecutive years; the permanent population was 126.84 million, accounting for 8.98% of the country [10, 11]. The key health indicators in the province were at the forefront of the country in 2020, with an average life expectancy of 78.4 years, a maternal mortality rate and infant mortality rate of 10.18 per 100,000 and 2.13 per 1000, respectively [12]. How to utilize the fruits of economic development to satisfy the ever-increasing demands for better healthcare and to complete the crucial mission of constructing a healthy and powerful province has been a great challenge for Guangdong Province.

With the development of the social economy and the popularization of prevention-oriented health concepts, society has paid more attention to equity and efficiency in the health field than ever before, and increasing numbers of studies have explored the equity and efficiency of health resource allocation. The majority of studies have examined the equality and efficiency of the distribution of health resources in all medical and health institutions [13‐17], without discriminating between different types of health resources in varied healthcare institutions [18‐22]. Few studies have focused on health resources in public hospitals. With the introduction of policies to encourage and guide social capital into the health care field, investment in the medical sector has been increasing [23]. Although the number of private hospitals surpassed that of public hospitals in 2015 for the first time and has remained so since then [24‐26], there are substantial discrepancies in resource aggregation and operational efficiency between private and public hospitals [27]. In addition, grassroots healthcare institutions have indeed improved their hardware and equipment, personnel, and service capacity since the start of the new healthcare reform, but the difference has not been narrowed in comparison to public hospitals. All these facts suggest that it is necessary to differentiate the types of health resources in different medical institutions when measuring the equity and efficiency of health resource allocation for more precise conclusions. Moreover, for the most part, studies have analyzed the equity and efficiency of health resource distribution in parallel, neglecting to incorporate equity and efficiency into the same analytical framework.

Different approaches based on data envelopment analysis (DEA) have been widely used as tools to assess the efficiency of decision-making units (DMUs) in the health care sector in China and abroad. The use of these methods can be broadly categorized into three types. The first is the use of a traditional DEA model or an extended model based on DEA to measure the efficiency score of DMUs. The efficiency of several hospital health centers in Greece was investigated with an input-oriented CCR-DEA model, and excellent performance was found for the units additionally providing preventive medical services [28]. By means of the BCC-DEA model, the efficiency of intensive care units in Iran was estimated, and five hospitals were identified as efficient in technical, managerial and scale performance [29]. An output-oriented DEA model was employed to assess the efficiency of maternal and child health resource allocation in Hunan Province, China, and over 40% of regions were found to have poor performance [30]. Chitnis A and Mishra DK used the output-oriented CCR-DEA model and superefficiency DEA model to assess the performance efficiency of 25 Indian private hospitals and determined that the low use of resources was the main reason for the underperformance of hospitals [31]. Second, studies apply the two-stage DEA method, which combines the DEA method with the Tobit regression method, aiming at efficiency evaluation and exploration of influencing factors. An input-oriented DEA model was applied to calculate the efficiency values of 11 Palestinian public hospitals, after which the Tobit regression model was constructed to explore contextual factors. Efficiency scores increased by 4% over the period from 2010 to 2015, and the outpatient-inpatient ratio had a positive effect on hospitals’ efficiency [32]. The efficiency of public and private hospitals in Beijing was analyzed with an output-oriented DEA method, and the findings revealed that the scale efficiency of public hospitals in Beijing was higher than that of private hospitals from 2012 to 2017. Then, the panel Tobit regression implied that some hospital characteristics, such as service type, level and governance structure, influenced the efficiency of public hospitals, while the geographical location impacted the efficiency of private hospitals [33]. A two-stage DEA approach was adopted to examine the technical efficiency of healthcare systems in a sample of 49 lower-middle-income countries and concluded that GDP per capita, percentage of total government health expenditure, and population density probably made a positive contribution to health efficiency [34]. Third, the three-stage DEA approach is used, integrating the conventional DEA model with stochastic frontier analysis (SFA) to adjust for the effects of environmental variables and statistical noise on efficiency values. Resource utilization efficiency in obstetrics and gynecology units was studied with a three-stage DEA method, and the technical efficiency and scale efficiency values of units were 0.48 and 0.54, respectively [35]. By using the three-stage DEA method, the technical efficiency of Chinese regional public hospitals was measured, and the average efficiency was found to improve from 0.927 to 0.981 during the period 2011–2018 [36]. Li et al. integrated input-oriented DEA and SFA to estimate the operational efficiency of basic pension insurance and obtained values of 0.742, 0.689, and 0.505 for the eastern, central and western regions, respectively. Additionally, they found that GDP, urbanization rate, and the amount of government public expenditure positively affected operational efficiency, while the elderly dependency ratio had a significant negative impact on efficiency [37]. In summary, the first approach has no bias adjustment for efficiency scores; the second method is unable to account for the effect of statistical noise on efficiency values, despite its ability to explore the factors influencing efficiency values [38]. For the third method, the three-stage DEA method, random error and disturbance of environmental factors can be effectively removed to put all the DMUs in a homogeneous environment for comparison [38]. However, this method still has some drawbacks. For example, the model used in the first and third stages, which are conventional DEA methods, cannot solve the relaxation problem and sequencing problem of DMUs, which can be easily overcome through the use of the slack-based measure of the superefficiency DEA model (superefficient SBM model), an improved DEA model [39]. Therefore, future research should endeavor to capitalize on the advantages of these two models while performing efficiency analysis.

Concerning the selection of indicators, appropriate inputs and outputs are critical for a meaningful analysis [40]. Most researchers selected input indicators of hospital performance assessment in terms of labor and capital investment [13, 28‐30, 33, 36, 41‐49]. The number of healthcare institutions and beds were commonly chosen to represent capital investment [33, 42, 46‐49]. Regarding labor variables, health workers [13, 17, 42, 44‐47, 50], health technical workers [30, 33, 36, 42, 45, 48, 49], physicians [28‐30, 36, 41, 43‐45, 50], and nurses [17, 28, 30, 36, 41, 42, 44, 45] were often regarded as types of labor investment. In the selection of output indicators, there are two main categories of expected and undesirable outputs. For data availability issues, most studies opt for expected indicators when conducting analysis. The number of outpatient visits or outpatient and emergency visits [13, 28, 30, 36, 41, 42, 44‐49, 51], inpatient visits or discharged visits [28, 29, 36, 41‐44, 46‐48, 51] and revenue [17, 33] are usually regarded as expected outputs, and infection incidence or infectious patients and patient or population mortality [36, 50, 52] are regarded as undesirable outputs. Kohl S and Schoenfelder J et al. pointed out that it is of great importance to distinguish between absolute and relative data to prevent biased conclusions [40]. However, this has been ignored in some studies.

Based on a review and summary of the relevant literature, this study assesses the equality and efficiency of the distribution of public hospitals’ health resources in Guangdong Province with the use of the latest data, aiming to provide a thorough understanding of the postreform development of the health sector, analyze the problems that may exist, and offer appropriate countermeasures for the sustainable development of health services. In addition, this study attempts to make improvements in the following aspects. First, it puts equity and efficiency into one analytical framework following an independent analysis of efficiency and equity. Specifically, all the indicators used for equity analysis are given different weights through the entropy weight method to derive comprehensive indicators representing the total amount of health resources. We then calculate the HRDI of the comprehensive indicator reflecting the volume of health resources in each city in terms of geography and population. Next, two-dimensional matrix diagrams of the HRDI of the comprehensive indicator and efficiency, per capita government subsidies and efficiency are drawn to observe the coordination of the equity and efficiency in health resource allocation across regions. Second, for efficiency analysis, the study constructs an improved three-stage DEA method, which combines the traditional DEA method, SFA and the superefficient SBM model. For this approach, not only the effects of environmental factors and statistical noise on the efficiency but also the ranking of the effective units and slack movement are considered. Third, all data used for efficiency assessment are unified as absolute data, without confusion between absolute and relative values, to prevent biased outcomes.

During the five years from 2016 to 2020, the number of health resources and medical service capacity in public hospitals of Guangdong Province greatly improved. The study confirmed that beds, health technicians, and government financial subsidies showed an upward trend in total number, per thousand persons, and per square kilometer in Guangdong Province. In addition, the number of public hospitals decreased slightly, which is mainly due to the recent policies limiting the blind expansion of public hospitals in terms of quantity and scale to provide space for social capital to develop medical and health care and requiring public hospitals to pursue high-quality development of service and management [22].

This study analyzed the equity in the distribution of health resources, including public hospitals, beds, health technicians, and government financial subsidies, in Guangdong Province from 2016 to 2020. According to the Gini coefficients and Lorenz curves, the study reaches two conclusions. First, the distribution of public hospitals, beds, and health technicians by population is absolutely fair, while the distribution of government financial subsidies is unfair. This result is consistent with the finding of Li Q et al. [17]. The main reason why the government financial subsidies allocation is much less equitable than the allocation of the other three types of resources is that the amount of financial subsidies depends largely on the tax revenues of each city, which is deeply influenced by the level of local economic development. Additionally, a significant disparity in economic development between the Pearl River Delta, eastern region, western region, and mountainous region still exists [65]. Consequently, it is reasonable to suggest that the government improve the redistribution system and increase financial support for less-developed regions, covering the eastern region, western region, and mountainous region. Second, the fairness of health resources allocated by population is better than that allocated by geographic area, which is consistent with other studies on the equity of health resource distribution in Guangdong Province [66, 67]. There are two possible explanations for this result: first, some cities, such as SG, MZ, and HY, having a large geographical area, are backward in economic development and therefore face a lack of health resources; second, the health resource allocation standards set by the government are the number of health resources per thousand persons instead of the number of health resources per square kilometer [22]. However, it should not be ignored that the farther away residents are from the hospital, the more time and economic cost it takes to go to the hospital, and the less motivated residents will be to receive health services, which is not conducive to the construction of a healthy China. Thus, it is necessary for governments to take population and geographical factors into consideration when formulating health resource allocation plans [30, 51]. The results for T showed that the unfairness of health resource allocation in Guangdong Province mainly stemmed from intraregional differences. The Pearl River Delta has the largest variation in the internal distribution of health resources and contributes much more to the differences in the province than other regions. The same result was found in the study of Zhu C et al. [68]. Although the HRDI of the Pearl River Delta is far greater than that of the other three regions, the differences among cities in the Pearl River Delta are great, with the lowest values in JM, HZ, and ZQ. Taken together, these results suggest that the development of health services in the Pearl River Delta is extremely uneven, and improving the equity status of health resource allocation in the Pearl River Delta can effectively enhance the fairness of health resource allocation in the whole province. Therefore, it is highly recommended that the government attach great importance to the equity status of health resource distribution in the Pearl River Delta and ensure the basic medical and health needs of residents in underdeveloped and remote cities, including JM, HZ, and ZQ. It is equally important to promote the reasonable flow of medical experts, key personnel, and recent graduates of higher educational backgrounds from large cities to economically underdeveloped cities, with policy guidance and financial support, which could enable people living in rural, remote areas to have access to quality health resources and services.

After excluding the impact of external environmental and random factors, the efficiency scores and ranking of the cities changed. That is, environmental and random factors affect the real performance of hospitals. Therefore, it is reasonable and necessary to use the improved three-stage DEA method when measuring the efficiency of public hospitals for accurate results. The results for efficiency indicated that the mean efficiency score of public hospitals in Guangdong was 0.891, which was higher than that in Palestine (0.853) [32], Serbia (0.782) [45], Turkey (0.724) [69], Saudi Arabia (0.76) [50], Jordan (0.547) [70], and Iran (0.873) [71] and lower than that in Spain (1.016) [72], Wuhan, China (0.899) [73], and Taiwan, China (0.973) [74]. Only 38.1% of cities were found to be efficient in 2020. All these findings show that the results for the allocation of health resources in public hospitals in Guangdong Province were not satisfactory, and the health resources in most cities have not been fully utilized. On the other hand, cities found to be DEA-effective were mainly located in the Pearl River Delta, which indicates that it is of great significance to establish a mechanism for cooperation and exchange between the Pearl River Delta, eastern region, western region and mountainous region to encourage cities to learn from the advanced concepts and successful practices of cities at the forefront of efficiency in the Pearl River Delta, such as GZ, SZ, ZH, FS, DG, and ZS, to boost the efficiency in resource utilization. Although the government has been driving regional exchanges and cooperation [75], it seems that the effect is not obvious, the relevant system still needs to be improved, and related measures still need to be put in place.

For the distribution of the HRDI of the comprehensive indicator and efficiency, six out of nine cities in the Pearl River Delta were in the first quadrant, which means these cities have relatively sufficient health resources and high efficiency in resource utilization. However, the remaining three cities in the Pearl River Delta, HZ, JM, and ZQ, were in the third quadrant, indicating the simultaneous existence of a shortage of health resources and inefficient use of health resources. These results suggest that cities in the Pearl River Delta have polarized performance in the coordination of fairness and efficiency, which once again demonstrates that high priority should be given to the integrated development of health services in the Pearl River Delta to promote the sustainable development of healthcare in the region by strengthening regional health planning and focusing on less-developed cities, i.e., HZ, JM, and ZQ. The Pearl River Delta was in the first quadrant and the other three regions were in the third quadrant during these five years. In addition, cities in the third quadrant accounted for a large proportion of the total number of cities. Taken together, these indicate uneven development of health care between the four regions, and most cities in the eastern, western, and mountainous regions suffer the dual pressures of relatively insufficient health resources and inefficiency. Consequently, it is necessary to strengthen the cooperation and exchange between the Pearl River Delta, eastern, western and mountainous regions to promote the flow of health resources between regions, which is conducive to the improvement in hospital management and medical service in less-developed areas. In addition, cities in the third quadrant should learn from the health management and experience of cities including QY and MM in the second quadrant and emphasize improving efficiency in the case of limited health resources, enabling them to move from the third quadrant to the second quadrant and finally to the first quadrant. In this way, the dynamic coordination of equity and efficiency of health resource allocation can be realized.

Although we have attempted to use various methods and the improved three-stage DEA model to conduct a comprehensive assessment of the equity and efficiency of public hospitals’ health resource allocation, there are still some limitations to this study. First, the selection of indicators was based on previous studies, but like most studies, due to the availability of data, the output indicators did not include quality indicators, such as those related to patient health recovery, patient satisfaction, job satisfaction of medical staff, medication errors, etc. Second, although environmental factors were considered from five dimensions, i.e., economic development, population, education, insurance and policy, some alternative environmental variables that may also affect the efficiency scores should be incorporated in future studies. Third, when calculating the comprehensive index reflecting the overall level of health resources, the entropy weight method is first used to assign the weights of indicators. The entropy weight method is an objective method that can reduce the subjective influence of decision-makers and improve objectivity. However, future research can consider introducing subjective methods, such as Analytic Hierarchy Process and Delphi methods, to assign the weights of indicators, or combining the results of subjective and objective weighting methods.

This study provides an empirical study of the equity and efficiency of public hospitals’ health resource allocation in Guangdong Province based on the most recent available data from official publications. The study has enlightenment for management and significance guidance for policymakers in formulating effective policies to realize the unification of equity and efficiency of health resource allocation. Major findings in the study and recommendations are as follows. With the development of the social economy, the total amount of health resources and the capacity of medical services greatly improved from 2016 to 2020 in Guangdong Province. The equity of government financial subsidies distribution was the worst, and there were distinct regional differences in the geographical distribution of public hospitals’ health resources in Guangdong Province. Furthermore, the development of health services in the Pearl River Delta was extremely uneven, which is reflected in the substantial differences in health resources allocation and resources utilization efficiency among cities in the region. The uneven development of health care between the Pearl River Delta, eastern region, western region, and mountainous region was also observed. Most cities in the eastern, western, and mountainous regions of Guangdong Province faced the problem of relatively insufficient health resources and low efficiency. To improve the equity and efficiency of health resource allocation, this study offers several suggestions. First, high priority should be given to the integrated development of health services in the Pearl River Delta, with a focus on key cities including HZ, JM, and ZQ. Second, demographic and geographical factors should be taken into consideration when formulating health resource allocation planning. Third, the government income redistribution system needs to be further improved, with more distribution to underdeveloped areas and more preferential policies to attract experienced medical workers and health technicians with a higher education background to work in the eastern region, western region and mountainous region. Finally, the cooperation and exchange between the Pearl River Delta, eastern region, western region and mountainous region should be strengthened to promote the flow of health resources between regions, increase the total amount of health resources and improve the medical service capacity in eastern region, western region and mountainous region.