Equity and efficiency of primary health care resource allocation in mainland China

The primary health care (PHC) system is the key component of almost every health system in the world [1]. China had always attached considerable importance to PHC and established a good PHC system as a model before 1978, which was highly praised by the World Health Organization. Subsequently, a market-oriented reform was implemented in the health sector. The efficient three-tier health-care delivery system and the Cooperative Medical System nearly collapsed [2, 3]. Fortunately, the Chinese government launched a new round of health care reform with a primary goal of rebuilding an effective PHC system [4]. The government had invested an additional $127 billion to enhance the infrastructures of PHC institutions, particularly those in rural areas [5]. These measures aimed at ensuring the commonweal of PHC and providing for all as a public product.

The reform had five key tasks [6] in 2009, one of the tasks was to build a relatively complete PHC system in 3 years (2009–2011). The Deepening Health Care Reform on March 14, 2012 proposed that we should consolidate and improve the service capabilities of PHC institutions. One of the goal of this reform is that the PHC will be more equitable and accessible, and efficiency of PHC institutions will be significantly improved by 2015. Specifically, the number of beds per thousand people will be 1.2 and the number of health workers per thousand people will be 3.5 in PHC institutions by 2020 (<Outline of the national plan for medical and health service system (2015–2020) > issued by the General Office of the State Council on March 6, 2015). Since 2009, the situation of PHC system and the equity and efficiency of the PHCRA were hot topics. In fact, equity and efficiency are always important goals pursued by health policy makers and health system [7]. And, some scholars had been devoted to research the equity and efficiency of health resource allocation. However, most of the studies were aimed at a certain area or one aspect and were based on data from early national yearbooks [8‐10]. For instance, Zhang et al. [11] conducted a comparative study on inequality in the distribution of health resources and health services between hospitals and primary care institutions in China. Xu et al. [1] analyzed trends in the distribution of PHC professionals in Jiangsu Province of eastern China. In these studies, the methods that scholars mainly used to measure equity were Gini coefficient, Theil index, Concentration index, Lorenz curve and so on [12]. Lorenz curve could put a vivid reflection of the equity in resources allocation when combine with Gini coefficients, Theil index could reflect the contribution rate within the group and between groups when measuring the main factors causing the disparities [13]. Besides, Cheng et al. [4] used bootstrapping data envelopment analysis to assess the efficiency and productivity of rural township hospitals in China. Giuffrida researched productivity and efficiency changes in primary care based on a Malmquist index approach [14]. Indeed, DEA and MPI were extensively used to assess efficiency and productivity of decision-making units (DMUs) [15]. DEA is a method of performance evaluation that includes mathematical planning models to evaluate the relative effectiveness of the department or unit using multiple input and output indicators, and MPI is used in production analysis through the calculation of the ratio between the distance function to the productivity index [16]. Based on these successful practices of these methods in equity and efficiency measurement, this study adopted Lorenz curve, Gini coefficient and Theil index to measure equity, and DEA and MPI to measure efficiency and productivity. However, relatively few studies focused on nationwide PHCRA based on the latest data. And, those previous studies couldn’t represent the latest situation and if they only focused on some areas, some institutions or one aspect, they couldn’t represent the entire situation of China. Meanwhile, the nationwide study was easy to compare differences in provincial level and regions, then to develop corresponding plans to solve these problems.

The Deepening Health Care Reform from 2012 to 2015 had finished, the effects of this reform for PHCR need to be assessed in time. This study aimed to evaluate the equity, efficiency and productivity of PHCRA in this reform with the latest and nationwide data, analyse the causes of deficiencies, explore measures to solve the problems and provide references for policy makers in sustainable reform and other scholars.

After a long period of development, China has established the medical and health service system, including PHC institutions. This study comprehensively analyzed the equity and efficiency of PHCRA in recent years. The results corroborated that, except for the number of institutions per capita, the total number of institutions, beds and health workers and the number of per capita and per km² presented a steadily increasing trend. However, the speed of decrease in institutions per thousand capita slowed down, which was mainly due to the fact that the state, in recent years, had encouraged social capital to enter the medical market to improve the equity and efficiency of resource allocation through competition with public institutions. In terms of PHC institutions, nonpublic institutions occupied 46% in 2016. In 2016, the speed of growth in bed allocation slowed down. And, the differences in urban and rural areas showed that the number of beds per thousand people in urban regions was decreasing, which had limited the speed of increase in beds. If it does not improve, then achieving 1.2 beds per thousand capita in the PHC institutions will be difficult by 2020, which is the goal proposed by China. Compared with institutions and beds, the speed of growth in health workers improved. But, with respect to the number of health workers per thousand people, which in rural areas is more than four times as urban areas. So, in order to achieve the goal of 3.5 health workers per thousand capita by 2020, numerous health workers should be allocated to PHC institutions in urban areas gradually.

The Chinese government has issued a number of documents to optimize the allocation of health resources. However, most of these documents were based on population allocation. Correspondingly, the equity of resource allocation by population size was much better than that by geographical area. Many scholars have obtained the same conclusion [35, 36]. G of population size (0.07–0.19) was far less than G of geographical area (0.62–0.66). Indeed, when Zhang et al. [11] and Yang et al. [37] used G to measure equity of PHCRA by geographical area in China, the Gs were over 0.7 and between 0.6 and 0.7 respectively. Specifically, the equity of PHCRA by population size is health workers>beds>institutions. The equity of geography is institutions>beds> health workers. Zhang [11] and Yang [37] had also verified this result. The equity of T and G is the same as regards population size. Moreover, equity in the eastern, central and western regions were health workers>beds>institutions, and the differences in the intra-east mainly caused the inequity. The finding is the same as that of the study of Liu et al. and Gong et al. [13, 38]. By taking the number of institutions per thousand capita in 2016 as an example, seven provinces in eastern region (7/11) wre lower than their average, and the maximum value of Hubei was six times that of Shanghai. As for central and western regions, the proportions were 3/8, 6/12, and Shanxi was three times that of Anhui, Tibet was four times that of Yunnan respectively. The instance presented above could roughly explain the big differences in the intra-east. And, the differences contributed by the intra-east and west decreased; but, those of the central region increased. This finding means that the eastern region, with its economic and geographical advantages, is starting to improve its poor PHCRA [13]. The equity of western region had considerably improved because of inclined policies and aids [21]. However, the central region presented a relatively reduced development due to shortage of priority and positivity. When HRDI was used to assess the comprehensive equity, we found the following trend: eastern region>central region>western region. This reason may be the inadequate financial capacity and similar health resource allocation standards that cannot be followed [13]. The severe inequity in geographical area is indisputable, but existing policy documents are still based on population and administrative divisions to allocate health resources. However, a reasonable method is that the demographic and geographical distributions and all influencing factors should be considered when making health allocation plans [39]. Therefore, the central government should convert implementations of supply side oriented resource allocation to demand side oriented resource allocation and continue to increase inputs to central and western regions [40], narrow the regional disparities through financial transfer coordination [11], strengthen supervision and ensure that government investments can reach less developed and remote areas in a timely manner. Besides, more resources should be put into PHC institutions in urban areas gradually, because of increasing demand for services brought about by urbanization.

The results of the analysis on efficiency and productivity verified that PHC institutions had experienced significant technical inefficiency from 2012 to 2016. Although the government had attached importance to the PHC services, less than 20% of provinces achieved technical efficiency every year. The scores of SE (0.62–0.73) and PTE (0.64–0.68) were relatively bigger than those of TE (0.38–0.47). This finding means that these provinces only attained less than 50% of efficiency, and PTE, SE have a lot of room for improvement. Compared with similar studies, the mean of TE in this study is lower than that in the Nouna health district is 0.862 [41] and 0.833 in the Spanish region of Extremadura [42], 0.620 in the Weifang Prefecture [43] and 0.515 in the Xiaogan Prefecture of China [4]. Further analysis of the mean of TE, PTE and SE in the eastern, central and western regions showed that west>east>middle. The same result had been found in the study of Ding et al. [21]. This finding seemed to be an interesting phenomenon. The eastern region had economic and technical advantages and it’s amount of resources was larger than the others. Thus, their efficiency should be high. However, the scale of institutions in the east is too large, and the PHC institutions in east are mostly decreasing back to scale. Meanwhile, a much larger number of input redundancies have not been fully utilized. The technical level in the west region is limited, but their inputs are relatively appropriate and more fully utilized. As one of the output indicators, annual hospitalization rate can explain the differences, which is 4.063% in the western region and 1.934% in the eastern region. And, a study conducted by Zhang et al. [11] pointed out that richer people were more likely to go to high level hospitals for outpatient care, while poorer people were more likely to go to PHC institutions for inpatient care. Indeed, the economic development level of west is worse than east, geographical area is larger, traffic is inconvenient, so western people are more likely to go to PHC institutions. To some extent, the inputs and outputs in the western region were valuable to refer. Moreover, the low efficiency in the central region is reflected in the redundant inputs and inadequate outputs that simultaneously exist. Indeed, comparing with west and east, the central region did not benefit from the preferential regional policies and had become the most vulnerable region [44]. Specifically, Shanghai, Hainan (east), Qinghai and Ningxia (west) had no adjustment in their inputs, outputs and scale with their current technical level. Beijing, Zhejiang (east), Hubei (central), Chongqing, Sichuan and Xinjiang (west) only need to shrink scale, whereas others should improve TE and adjust scale.

Low TE had changed positively from 2012 to 2015. The productivity of institutions had risen again in 2016 because TE decline was counteracted by technological progress. Li et al. [16] asserted that technological progress was helpful to the short-term development of PHC services. However, to achieve sustainable development, the improvements of TE should be paid considerable attention. As for TE, because it decomposes into PTE and SE, so we should try our best to improve PTE and SE. Therefore, modifying manager and employee relationships, correcting leadership, marking personnel’s comments and suggestions, promoting and encouraging innovation and creating a favorable working environment are factors that can be effective in improving TE [32]. Finally, the medical pattern will be optimal which is small diseases in PHC institutions, severe diseases in hospitals, rehabilitation back to the PHC institutions with hierarchical treatment through referral system. Indeed, the study of Yip et al. [45] had proven that the PHC institutions could improve their overall efficiency and productivity by providing medical care, disease prevention, health promotion and education, rehabilitation and birth control [1]. However, the redundant inputs of 2016 are evidently larger than those of other years. These redundancies implied that PHC services did not meet the needs of the participating subjects (PHC institutions, primary doctors and patients). Specifically, services delivered by PHC institutions were deemed poor quality, leading to patients’ distrust [11]. Consequently, patients bypassed PHC institutions and received treatment in high-level health-care facilities [46]. In addition, additional resources were concentrated on hospitals and the residents’ income had been increasing because of market power, promoting patients to seek high-quality services from hospitals [47]. Meanwhile, the implementation of zero-profit policy of medicine and the National Essential Medicines Scheme had resulted in the reduction of drug income in institutions and the corresponding reduction of staffs’ performance salary. At this time, government subsidies were difficult to be timely in place, resulting in the overall work enthusiasm frustrated [4]. In fact, the real reasons for the decline in TE are complex, but the analysis here only discovers one aspect, thus more studies are needed to do this complex analysis.

This study provided an empirical research for the equity, efficiency and productivity of PHCRA based on authoritative data. The results corroborated that the equity of PHCRA had improved year by year and that the equity of population allocation was far better than the geographical area in China. After comprehensive consideration of population and geographical area factor, we confirmed that the eastern region had the largest resource density and best equity and the western region had contrary results. The results of the efficiency analysis affirmed that the TE and productivity of the institutions in each province were generally low. Further analysis of the invalid provinces elucidated that their scales were too large and had redundancies. The improvement of productivity relied solely on technological progress rather than on the improvement of internal management level and institutional innovation. The inputs of several resources had certainly caused the improvement of equity, but the improvement of TE had not kept up with the pace. In the future, internal management should be strengthen by setting performance goals, improving incentives and updating personnel quality. The existing resources should be fully and rationally applied, and the allocation of health resources in China should be revitalized through the flow of resources among the institutions.