Sections “Efficiency of the healthcare system of china”, “Meta frontier, group frontier, and TGR in the healthcare system of China”, and “Total factor productivity of the healthcare system of China” present the results of efficiency, regional technological gap ratio, and total factor productivity change in the healthcare system across Chinese provinces for the study period 19,197-2022.
Efficiency of the healthcare system of china
Table 2 and Figure A1 present the efficiency of the healthcare system of China estimated through DEA-SBM for the study period of 1997–2022. It illustrates the efficiency trends across different periods and elaborates on the efficiency level of the healthcare system of China. In general, higher scores signify enhanced efficiency in the provision of healthcare services. Conversely, lower scores indicate deficiencies or opportunities for improvement. From 1997 to 2022, the mean efficiency score was 0.7672. It provides a comprehensive summary of the performance of the healthcare system over these years and identifies potential for improvement of 23.28. A consistent upward trajectory is observed in efficiency scores over time, signifying improvements in the efficiency of the healthcare system. The efficiency scores fluctuate from 1997 to 2009 but remain relatively constant within a certain range. Notable growth in efficiency is evident starting from 2010, as evidenced by consistently raised scores compared to preceding years. A marginal decrease in efficiency scores has been observed in recent years, specifically between 2020 and 2022; however, the overarching trajectory continues to be favorable. A moderate level of efficiency has been observed in the healthcare system throughout the entire period (1997–2022), as indicated by the average efficiency score of 0.7672. Significant enhancements in the provision of healthcare services have been indicated by the maximum efficiency scores observed in recent years, specifically from 2010 to 2016. The healthcare system experienced possible challenges or inefficiencies in management during the late 1990s and early 2000s, as evidenced by the lowest efficiency scores recorded during that period. The observed upward trajectory in efficiency scores implies that the Chinese healthcare system’s performance may have been influenced positively by reforms or interventions that have been implemented over time. The marginal decrease in efficiency scores observed between 2020 and 2022 may serve as an indication of emerging obstacles or domains necessitating focus to maintain or enhance the efficiency of the healthcare system63.
The healthcare reform in China had the objective of attaining Universal Health Coverage (UHC) by enhancing the accessibility, quality, and affordability of healthcare services for the public. The key initiatives were the expansion of insurance coverage, augmentation of government health expenditure, reformation of public hospitals, and the promotion of primary care. There was a notable rise in efficiency scores between 2009 and 2010, as depicted in Fig. A1, which can likely be ascribed to several reasons associated with these reforms. Firstly, the significant government investment in healthcare likely resulted in improved resource availability and more effective utilization. Increased insurance coverage facilitated greater accessibility to healthcare services, thereby mitigating the burden of out-of-pocket payments and financial obstacles for patients. Efforts aimed at improving the efficiency and standard of public hospitals have resulted in improved healthcare outcomes and more optimal utilization of resources. In addition, enhancing primary care services contributed to the efficient management of prevalent health conditions, alleviating the strain on tertiary institutions and enhancing the overall effectiveness of the healthcare system. The previous research studies discussed the benefits of these health measures in Chinese and global healthcare systems64,65,66.
A comprehensive analysis of the efficiency levels within healthcare systems across different provinces in China is presented in Table 3 and Fig. A2. Efficiency scores are assigned to each province as indications of the effectiveness and productivity of healthcare service delivery. The scores enable a comparative evaluation of healthcare system performance at a regional level. The observed variation in efficiency scores among the provinces underscores notable inequalities in the performance of healthcare systems. Significantly high efficiency scores are observed in provinces such as Guangdong, Zhejiang, and Shandong, suggesting that their healthcare systems are operating with effectiveness and efficiency. In contrast, it is seen that provinces such as Inner Mongolia, Tibet, and Hainan exhibit comparatively lower efficiency scores, indicating the presence of possible obstacles or inefficiencies within their healthcare systems. A comprehensive analysis of provinces exhibiting remarkably high-efficiency scores, namely Shanghai, Zhejiang, and Guangdong, provides significant insights into the underlying variables that contribute to their notable achievements. The greater performance of these provinces can be attributed to their well-structured healthcare infrastructure, effective healthcare management techniques, high-quality healthcare services, or a combination of these factors67.
On the other hand, provinces exhibiting lower efficiency scores may require additional scrutiny to ascertain potential areas for enhancement. Inadequate healthcare infrastructure, limited access to healthcare services, inefficiencies in healthcare delivery, and socioeconomic variables may be potential contributors to lower efficiency scores. Ensuring equitable access to quality healthcare services for all individuals across China demands the imperative task of addressing regional variations in healthcare system efficiency. Policymakers can employ the data presented to effectively allocate resources, direct investments, and execute focused initiatives to enhance the efficiency of healthcare systems in regions exhibiting lower ratings. By adopting this approach, individuals can strive towards attaining a more equitable and efficient provision of healthcare services on a national scale68.
Table 4 and Figs. A2 & A3 present a comprehensive analysis of the efficiency levels witnessed in the healthcare systems of four different regions in China, namely Central, Eastern, Northeastern, and Western. Every region consists of multiple provinces, and each province’s healthcare system is granted efficiency scores. The above-mentioned scores function as metrics that assess the efficiency and output of healthcare service provision in each respective geographical region. Commencing with the Eastern area, provinces such as Shanghai, Zhejiang, and Shandong exhibit conspicuously high-efficiency scores, signifying the presence of accurately structured and proficient healthcare systems. The Eastern area exhibits a commendable performance in healthcare delivery, as evidenced by its average efficiency score of 0.86917. In contrast, it is seen that provinces located in the Western and Northeastern areas tend to demonstrate comparatively lower efficiency scores, with average scores of 0.6983 and 0.7236, respectively. These regions’ healthcare systems may face issues or inefficiency.
The central provinces, namely Henan, Hubei, and Jiangsu, exhibit notable levels of efficiency, but marginally lower compared to the Eastern area. The Central provinces have an average efficiency score of 0.757, which suggests a moderate level of efficiency in delivering healthcare services. On the other hand, it is seen that provinces located in the Western and Northeastern regions exhibit comparatively lower levels of efficiency, as evidenced by their overall average ratings, in contrast to the Central and Eastern regions. This highlights the requirement for focused interventions and allocation of resources to tackle inefficiencies and enhance the performance of healthcare systems in these locations. In general, the variations in efficiency levels across different regions highlight the significance of customized approaches and cooperative endeavors in improving healthcare provision on a national scale. The policymakers can effectively allocate funding and execute focused interventions to enhance the efficiency of healthcare systems in various regions of China. China may strive to achieve a more equitable and effective healthcare delivery by addressing regional differences and exchanging best practices. This would ensure that all residents have equal access to high-quality healthcare services throughout the country69 (Fig. 2).
The average regional efficiency level of the healthcare system in China.
Meta frontier, group frontier, and TGR in the healthcare system of China
Table 5 provides a comprehensive overview of three key indicators, Meta Frontier (MF), Group Frontier (GF), and Technology Gap Ratio (TGR), within the healthcare system of China over the period from 1997 to 2022. MF is the same efficiency score presented in Table 2 and labelled the M&H efficiency. These measures offer valuable insights into the disparities in efficiency and technology among various regions of China’s healthcare sector. The Meta Frontier values are indicative of the efficiency benchmarks established by the National healthcare system, signifying the utmost level of efficiency attainable within the sector. On the other hand, the Group Frontier values represent the degrees of efficiency achieved by the collective healthcare system in one specific Chinese region. Although Meta Frontier values generally exceed Group Frontier values, both metrics exhibit a constant rising trajectory over time, suggesting broad enhancements in efficiency across the Chinese healthcare industry. The Technology Gap Ratio (TGR) is a significant metric used to assess the disparity in production technology among different regions in China. This statement clarifies the degree to which various regions exhibit disparities in technical progress within their healthcare systems. A smaller technology gap across regions is indicated by a lower Technology Gap Ratio (TGR), whereas a higher TGR signifies a greater discrepancy in manufacturing technology. By tracking TGR values over the study period, policymakers and stakeholders can pinpoint areas that may need extra assistance or financial resources to close the technological disparity and ensure fair and equal access to advanced healthcare services across the country. The TGR after 2010 enhanced dramatically showing a rapid growth in production technology in the healthcare systems of China. It indicates that technology gaps have been reduced during 2010–2022.
Table 6 provides a detailed analysis of the Meta Frontier (MF), Group Frontier (GF), and Technology Gap Ratio (TGR) scores in different areas and provinces of China’s healthcare system. The provinces are classified into four regions: Central, Eastern, Northeastern, and Western. These regions are accompanied by their corresponding scores for MF, GF, and TGR. The aforementioned scores offer significant insights into the levels of efficiency and digital inequities that exist across healthcare systems across various areas. There are noticeable differences in the scores among regions, indicating different levels of efficiency and technical progress. The Eastern provinces typically demonstrate higher MF and GF scores, suggesting the presence of more efficient healthcare systems in comparison to the Western and Northeastern provinces. It is noteworthy that certain provinces, particularly those in the Eastern region, have greater TGR scores, which suggests a narrower disparity between the Group Frontier and Meta Frontier scores. This implies that these provinces are in closer proximity to attaining the efficiency standards established by the most successful healthcare systems nationally.
The scores of the Technology Gap Ratio (TGR) provide insights into variations in production technology among different provinces. Greater Technology Gap Ratio (TGR) scores are indicative of narrower disparities in technology between the Group Frontier and Meta Frontier scores. This implies that specific provinces are in closer proximity to attaining the efficiency criteria established by the most successful healthcare systems nationally. This highlights the significance of implementing focused interventions to address existing inequities and provide fair and equal access to modern healthcare technologies. Examining specific provinces within each region uncovers different degrees of effectiveness and disparities in technology. Provinces that exhibit higher MF and GF scores typically demonstrate more efficient healthcare systems and narrower technology disparities. Conversely, provinces with lower scores may require strategic investments and policy initiatives to enhance their healthcare infrastructure and address any lingering technical inequalities. In addition, the computation of average values for each region offers a comprehensive perspective on the overall levels of efficiency and changes in the technology gap. Regions characterized by higher average MF and GF scores generally exhibit superior performance in the healthcare system as a whole and possess narrower technological gaps. This observation implies the presence of places that possess relative strength and possibility for enhancement.
Figure 3 indicates the TGR of all 4 regions. It indicates that the TGR of Eastern Chinese provinces is 0.9909, which is higher among all 4 regions. It illustrates that eastern China has the most advanced technologies employed in the health care system. Western regions witnessed a TGR value of 0.8109, ranked second in all four regions, and shows that after the eastern region, the western provinces keep more technologically advanced health care systems. Moreover, central (0.7942) and northeastern (0.7236) regions are ranked third and fourth, respectively. Elaborating on the TGR of different provinces study found that Beijing, Guangdong, Shanghai, Tianjin, and Zhejiang are the provinces with the latest healthcare technologies across all 31 mainland Chinese provinces for the study period. On the other hand, Heilongjiang (0.6878) and Jilin (0.5914) were found to have the least advanced healthcare technologies.
Technology gap ratio of healthcare systems in 4 different regions of China.
Ensuring fair access to sophisticated healthcare services nationally in China’s healthcare system requires the reduction of technological heterogeneity across various regions. Figure 3 presents the Technology Gap Ratio (TGR) values, which provide valuable information about the differences in production technology among the four regions: Eastern, Western, Central, and Northeastern. Based on the data provided, it can be observed that the Eastern region demonstrates the greatest TGR value of 0.9909 when compared to the other three regions. This observation suggests that the healthcare systems in the Eastern Chinese provinces are equipped with the most sophisticated technologies. To decrease the diversity of technology in this region, it is crucial to adopt methods that focus on spreading modern technologies to other regions and promoting cooperation and the exchange of knowledge across healthcare facilities.
Among the four regions, the Western regions exhibit a TGR value of 0.8109, placing them in second place. These findings indicate that the Western provinces have healthcare systems that are more technologically advanced compared to the central and northeastern regions. To address the existing technological gaps in Western regions, it is imperative to allocate resources toward infrastructure development, training initiatives, and research and development endeavors. These expenditures are crucial to ensuring that healthcare facilities are equipped with state-of-the-art technologies and can proficiently integrate them into patient care practices. Conversely, the Central and Northeastern regions exhibit lower TGR values of 0.7942 and 0.7236, respectively, suggesting that their healthcare systems utilize relatively least modern technologies. To tackle this issue, specific measures such as enhancing skills and knowledge, implementing technology transfer initiatives, and providing incentives for innovation can be employed to improve technological capabilities in these regions70,71.
In providing additional details regarding the TGR of various provinces, the research highlights Beijing, Guangdong, Shanghai, Tianjin, and Zhejiang as the provinces exhibiting the most advanced healthcare technology among all 31 provinces in mainland China throughout the study. In contrast, it has been observed that provinces such as Heilongjiang and Jilin exhibit the lowest levels of healthcare technology advancement, as indicated by their respective TGR values of 0.6878 and 0.5914. To mitigate technological inequities among provinces, it is imperative to prioritize the improvement of infrastructure, the cultivation of research and development activities, and the facilitation of collaboration between healthcare institutions and technology suppliers. The mitigation of technological disparities among various areas and provinces within China’s healthcare system demands a holistic strategy encompassing focused investments, knowledge dissemination, and capacity enhancement endeavors. China can reduce these technological gaps to provide fair and equal access to sophisticated healthcare services and enhance overall health outcomes for its population72.
Total factor productivity of the healthcare system of China
Table 7 presents a thorough examination of the Malmquist Index (MI), Efficiency Change (EC), and Technology Change (TC) in the healthcare system of China, covering the period from 1997 to 2022. The mean index (MI), which measures the overall change in productivity, exhibits an average value of 1.0033, indicating 0.33% growth in TFPC over the study period. The MI is further decomposed to efficiency change and technology change. This suggests a marginal growth in production within the system. The Efficiency Change (EC) exhibits an average value of 1.0123, indicating a 1.23 percent enhancement in the efficiency of the healthcare system. However, the average Technology Change (TC) is at 0.986, suggesting a decline of 1.4 percent in technical progress within the healthcare industry. These indicators provide a comprehensive understanding of the system’s performance. MI evaluates the combined effect of efficiency and technological changes, EC measures resource usage efficiency, and TC measures technological advancement. These results indicate that efficiency change is the main determinant of total factor productivity growth in the healthcare system of China. Policymakers and stakeholders can utilize these findings to identify areas that require improvement and develop specific initiatives to strengthen the efficiency and technical progress of China’s healthcare system73.
China must prioritize the enhancement of technology innovation within its healthcare industry to boost productivity growth. This objective can be accomplished by allocating resources towards research and development, cultivating an environment conducive to the advancement of medical technologies, encouraging the integration of digital health solutions, and enhancing the cooperation between healthcare providers and technology firms. China can achieve substantial enhancements in productivity and ultimately provide superior healthcare services to its population by prioritizing the advancement of technology. Policymakers and stakeholders can employ these data to identify areas in need of enhancement and devise targeted measures to boost the efficiency and technological advancement of China’s healthcare system74.
Table 8 and Fig. 4 display the mean values of the Malmquist Index (MI), Efficiency Change (EC), and Technology Change (TC) among the healthcare systems of 31 mainland provinces in China. The MI values across different provinces reveal a combination of positive and negative trends in productivity growth. Some provinces have seen improvement, while others have experienced slight losses. Efficiency Change (EC) and Technology Change (TC) provide valuable information about the effectiveness of resource usage and the progress of technology in each province. Results indicate that MI of Guizhou, Anhui, Yunnan, Jiangxi, Chongqing, Beijing, Guangxi, Ningxia, Qinghai, Fujian, Tibet, Gansu, Sichuan, Hainan, Shanghai, Inner Mongolia, and Tianjin witnessed growth as their corresponding score is greater than 1. On the other hand, the MI values of Henan, Guangdong, Hunan, Jiangsu, Zhejiang, Xinjiang, Shaanxi, Shandong, Hubei, Hebei, Shanxi, Jilin, Liaoning, and Heilongjiang are less than 1; indicating a decline in the productivity in these provinces over the study period. Results further elaborate that growth is mostly attributed to the EC as technology change values are less than 1. The study found that the EC of Shandong, Shanxi, Guangdong, Jilin, Liaoning, and Heilongjiang is less than one. These provinces need to enhance their efficiency in the healthcare system. All other provinces witnessed growth in EC. On the other hand, Guizhou, Anhui, Ningxia, Yunnan, Beijing, Tibet, Qinghai, Fujian, Chongqing, and Shanghai witnessed growth in TC. It shows that only these provinces enhance their technological growth in the healthcare system.
Variation in MI, EC, and TC of the healthcare system in Chinese provinces.
The growth in MI is influenced by Efficiency Change, while the majority of Technology Change values are below 1. It is crucial to improve the effectiveness of healthcare systems in different provinces. Provinces exhibiting EC scores below 1, such as Shandong, Shanxi, and other regions, should prioritize the enhancement of efficiency. In contrast, provinces such as Guizhou, Anhui, and others have had an increase in TC, which suggests the achievement of successful technical progress. To further augment MI, provinces should prioritize tactics that are customized to their requirements. In provinces characterized by suboptimal efficiency, the adoption of strategies such as process streamlining, resource allocation optimization, and the implementation of best practices might yield advantageous outcomes. Conversely, provinces that have lower technical progress might allocate resources towards research and development, encourage partnerships with technology companies, and facilitate the implementation of cutting-edge healthcare solutions. Provinces can effectively increase their MI and contribute to overall improvements in healthcare delivery and outcomes by carefully tackling both Efficiency Change and Technology Change75.
Table 9 and Figs. 5 and 6 depict the regional Malmquist Index (MI), Efficiency Change (EC), and Technology Change (TC) within the healthcare system of China. The 31 provinces are categorized into four regions: Central, Eastern, Northeastern, and Western. Every region consists of multiple provinces, and average values for MI, EC, and TC are derived within each region. In the Central region, provinces such as Anhui and Jiangxi demonstrate elevated MI values, which signify a comprehensive increase in production resulting from the combined influence of efficiency and technological progress. The Central region has an average MI of 1.0018, indicating a 0.18 percent marginal enhancement in productivity growth. The Efficiency Change (EC) in this region is significantly high, with an average value of 1.0198, which suggests efficient utilization of healthcare resources. However, the Technology Change (TC) exhibits a comparatively lower value of 0.9683, indicating the potential for enhancement in technological progress.
Total factor productivity change in the regional healthcare systems of China.
MI, EC, and TC of healthcare systems in 4 different regions of China.
The Eastern region exhibits a combination of outcomes, as provinces such as Beijing and Shanghai display higher MI values, indicating an increase in productivity influenced by both EC and TC. The mean MI value for the Eastern area is 0.9955, suggesting a consistent level of productivity. Although EC typically has a positive value of 1.007, TC has a significantly lower value of 0.9886, suggesting a requirement for more substantial technological progress. Provinces such as Jilin and Liaoning in the Northeastern area demonstrate lower MI values, suggesting a decrease in productivity. The Northeastern region has an average MI of 0.9137, indicating difficulties in achieving productivity growth. Both the EC and TC values exhibit relatively low levels, suggesting inefficiency in the utilization of resources and a lack of significant technological progress. Provinces such as Chongqing and Guizhou in the Western area exhibit higher MI values, suggesting a strong productivity increase influenced by both EC and TC. The mean MI for the Western area is 1.033, indicating substantial enhancements in production. Both the EC and TC values exhibit a notable raise, suggesting effective utilization of resources and substantial progress in technology.
To optimize MI in each region, provinces should prioritize the implementation of customized solutions. The Central and Eastern areas have the potential to enhance their resource utilization by prioritizing the advancement of technology. It is imperative for the Northeastern provinces to effectively tackle inefficiencies in resource consumption and allocate resources towards technical developments. In the meantime, it is recommended that Western provinces persist in utilizing their effective resource allocation and allocate more resources towards technological developments to maintain and augment productivity growth within their healthcare systems76.
To improve the Malmquist Index (MI) in the Central area, it is necessary to adopt a comprehensive strategy that combines technical advancements and efficiency enhancements in healthcare systems. First and foremost, it is imperative to cultivate partnerships among healthcare facilities, research centers, and technology businesses. This collaboration can expedite the advancement and acceptance of cutting-edge healthcare solutions customized to the specific requirements of the region. Moreover, allocating resources towards telemedicine services might enhance healthcare accessibility in remote regions, thereby optimizing the efficiency of healthcare provision. Additionally, the integration of data analytics and artificial intelligence technologies has the potential to enhance the allocation of resources, enhance patient outcomes, and reduce administrative procedures, so fostering overall productivity expansion. Promoting technological innovation and efficiency enhancement in healthcare systems is crucial for enhancing the MI in the Eastern area. The promotion of digital health technologies, such as electronic health records and telehealth platforms, is a crucial approach. These proposed solutions have the potential to not only enhance operational efficiency but also improve patient care and availability of services. The provision of incentives and resources to healthcare technology entrepreneurs has the potential to foster innovation within the region. In addition, it is imperative to allocate resources towards enhancing healthcare infrastructure to facilitate the integration of cutting-edge technologies and enhance the effectiveness of service provision.
The Northeastern region encounters distinct obstacles in augmenting Motivational Interviewing (MI) using technology progress and increasing efficiency in healthcare systems. It is essential to invest in information technology infrastructure, such as electronic health records and telemedicine capabilities, to modernize healthcare systems. Implementing training and educational initiatives for healthcare personnel to improve their proficiency in digital literacy and technology utilization can also facilitate advancement. Furthermore, promoting cooperation between healthcare providers and research institutions helps expedite the creation and application of cutting-edge technology specifically designed to meet the healthcare requirements of different regions. Expanding healthcare technology availability and promoting innovation are crucial methods for improving MI in the Western area. The facilitation of successful utilization of healthcare technology can be achieved by enhancing access to technology through infrastructure development and providing training for healthcare workers. The establishment of innovation hubs and technology incubators with a specific focus on healthcare has the potential to foster the creation of locally pertinent solutions. In addition, promoting collaborations between the public and private sectors can utilize resources and knowledge from both parties to promote technical progress in healthcare provision, ultimately leading to enhancements in overall efficiency as indicated by the Malmquist Index. Numerous research studies highlight the importance of technology advancement and efficiency enhancement to promote the healthcare system across the globe77,78.
Kruskal Wallis test
The results of sections “Efficiency of the healthcare system of china”, “Meta frontier, group frontier, and TGR in the healthcare system of China”, and “Total factor productivity of the healthcare system of China” reveal that the Efficiency, MI, and TGR of the healthcare system across the four distinct regions of China exhibit heterogeneity and are at different levels for different regions. Kruskal–Wallis test evaluates the statistically significant differences among the four regions of China concerning the average values of efficiency, MI, and TGR. The results of the Kruskal–Wallis test are illustrated in Table 10 and Figs. A4, A5 and A6. The significance level of all 3 hypotheses is less than 0.05. Therefore, we reject these hypotheses that state that the distribution of efficiency, MI, and TGR of the healthcare system is the same across the categories of 4 Chinese Regions. These results illustrate that efficiency, productivity growth, and production technology of healthcare systems of eastern, central, western, and northeastern China are heterogeneous.
The findings underscore prominent differences in the efficiency, rate of productivity growth, and utilization of production technology across the healthcare systems of eastern, central, western, and northeastern China. The observed diversity indicates that various regions within the country are encountering varying degrees of efficiency in how resources are utilized and technological improvements are embraced within their healthcare systems. To mitigate this heterogeneity and foster a more consistent advancement throughout various places, several techniques can be contemplated. The implementation of standardized practices and protocols across different regions has the potential to enhance operational efficiency and optimize resource allocation. Furthermore, it is imperative to allocate equal funding to healthcare infrastructure to guarantee that all regions have equitable access to essential resources and technology. To address the disparity, it is imperative to implement training and capacity-building initiatives targeting healthcare workers in regions characterized by poorer efficiency and technological advancement. The promotion of progress can be further enhanced through the facilitation of knowledge sharing and collaboration within regions, as well as the development of focused policy interventions that are customized to address the unique needs of each region. Through the implementation of these initiatives, policymakers and stakeholders can strive to decrease disparities and promote a fairer and more effective healthcare system in all regions of China. Research studies proved that the healthcare system of a country could be enhanced through resource utilization efficiency and technological advancement79,80.
link