Disease burden of ageing, sex and regional disparities and health resources allocation: a longitudinal analysis of 31 provinces in Mainland China

Chen, Shu; Si, Yafei; Hanewald, Katja; Li, Bingqin; Bateman, Hazel; Dai, Xiaochen; Wu, Chenkai; Tang, Shenglan

doi:10.1136/bmjopen-2022-064641

Cited by 3 publications

(3 citation statements)

References 38 publications

(119 reference statements)

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“…Fourth, health resource allocation is analysed in combination with geography and operations research methods. This mainly includes geographical detector models and geographically weighted regression methods,14 as well as fixed effects regression models 15. The allocation of health resources and regional disparities within the Chengdu-Chongqing economic circle are topics that require further investigation.…”

Section: Introductionmentioning

confidence: 99%

“…This mainly includes geographical detector models and geographically weighted regression methods, 14 as well as fixed effects regression models. 15 The allocation of health resources and regional disparities within the Chengdu-Chongqing economic circle are topics that require further investigation. Comprehensive evaluation of health resources in the Chengdu-Chongqing economic circle is targeted to benefit the leading advantages of the areas with good health resource allocation and supplement the deficiencies of the areas with weak health resource allocation.…”

Section: Introductionmentioning

confidence: 99%

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Regional differences in health resource allocation: a longitudinal study in the Chengdu-Chongqing economic circle, China

Zhou

2024

BMJ Open

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ObjectiveTo analyse regional differences in health resource allocation in the Chengdu-Chongqing economic circle.DesignA longitudinal analysis that collected data on health resource allocation from 2017 to 2021.SettingThe number of beds, health technicians, licensed (assistant) physicians, registered nurses and financial allocations per 1000 population in the 42 regions of Chengdu-Chongqing economic circle were used for the analysis.MethodsThe entropy weight technique for order preference by similarity to an ideal solution (TOPSIS) method and the rank sum ratio (RSR) method were used to evaluate the health resource allocation.ResultsThe number of licensed (assistant) physicians per 1000 population in the Chengdu-Chongqing economic circle (3.01) was lower than the average in China (3.04) in 2021. According to the entropy weight–TOPSIS method, Yuzhong in Chongqing had the largest C-value and the highest ranking. Jiangbei in Chongqing and Chengdu and Ya’an in Sichuan Province had higher C-values and were ranked in the top 10. Jiangjin, Hechuan, Tongnan and Zhongxian in Chongqing and Guang’an in Sichuan Province had lower C-values and were all ranked after the 30th place. According to the RSR method, the 42 regions were divided into three grades of good, medium and poor. The health resource allocations of Yuzhong, Jiangbei, Nanchuan, Jiulongpo and Shapingba in Chongqing and Chengdu and Ya’an in Sichuan Province were of good grade, those of Tongnan, Jiangjin, Yubei and Dazu in Chongqing and Guang’an and Dazhou in Sichuan Province were of poor grade, and the rest of the regions were of medium grade.ConclusionThe regional differences in health resource allocation in the Chengdu-Chongqing economic circle were more obvious, the health resource allocation in Chongqing was more polarised and the health resource allocation in Sichuan Province was more balanced, but the advantaged regions were not prominent enough.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Regional differences in health resource allocation: a longitudinal study in the Chengdu-Chongqing economic circle, China

Zhou

2024

BMJ Open

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“…China only became an upper middle-income country in 2010. The poorer provinces have even more severe need for old age services due to out migration of the younger population, but the older people have much lower affordability than those in the wealthier provinces (Chen et al, 2022;Si et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

The Entrepreneurial Welfare Mix: The Case of Community-Based Old Age Services in China

Fang,

2023

Social Policy and Society

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Developing an old-age service system that can meet the fast-growing needs of the aging population is challenging. It is increasingly recognised that community-level services should be pivotal in providing services to older people. In this article, the authors use the Chinese experience and argue that because the state is not clear how such a system should look like, all actors behave like entrepreneurs who strategise, take risks and search for a viable “business model”. The research draws upon in-depth interviews and focus groups in six cities in China collected in 2015-2016 and follow-up interviews in one community in three cities in 2021. The findings show that the service system has evolved into a dynamic entrepreneurial welfare mix that actively embraces the market. This research contributes to the theoretical development of the welfare mix. The authors also raised possible issues with such a direction of change in the conclusion.

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The impact of the scale and hierarchical structure of health human resources on the level of medical services-based on China’s four major economic regions

Chen,

Yang,

Zhu

et al. 2024

Int J Equity Health

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Background Ensuring that the scale and hierarchical structure of health human resources are rational, and that medical services are efficient and fair, is an important task of practical significance. On this basis, examining the impact of health human resources on the level of medical services presents a new and formidable challenge. This study aims to delve into how the scale and hierarchical structure of health human resources in China’s four major economic regions affect the fairness and efficiency of medical services, and to identify optimization strategies. Methods This study utilizes provincial panel data from China’s four major economic regions spanning the years 2009 to 2021. Initially, it provides a statistical description of the current state of health human resources and the level of medical services. Subsequently, it employs a fixed-effects model to analyze the impact of the scale and hierarchical structure of health human resources, as well as their interactive effects, on the fairness and efficiency of medical services, and discusses the interactive mechanisms between medical service fairness and medical service efficiency. Furthermore, after conducting a comprehensive evaluation of the level of medical services using the entropy weight method, it explores the regional heterogeneity and temporal dynamics in the influence of the scale and hierarchical structure of health human resources on the level of medical services. Finally, the study examines the scientific validity and rationality of the research findings through various robustness checks, including the substitution of research variables and models. Results The study found that the scale of health human resources has a promoting effect on the equity of medical services (β ≤ 0.643, p ≤ 0.01), but exhibits an inhibitory effect on the efficiency of medical services (β ≥ -0.079, p ≤ 0.1); the hierarchical structure of health human resources shows a positive impact on both the equity and efficiency of medical services (βequity ≤ 0.160, p ≤ 0.01; βefficiency ≤ 0.341, p ≤ 0.05); at the same time, the results indicate that the interactive effect of the scale and hierarchical structure of health human resources promotes equity in medical services (β = 0.067, p ≤ 0.01), but restricts the efficiency of medical services (β ≥ -0.039, p ≤ 0.01); the mechanism by which health human resources affect the level of medical services in China’s western and northeastern regions is more pronounced than in the central and eastern regions; after the implementation of the “Healthy China 2030” Planning Outline, the role of health human resources in the level of medical services has been strengthened; in the robustness tests, the model remains robust after replacing the core explanatory variables, with R2 maintained between 0.869 and 0.972, and the dynamic GMM model test shows a significant second-order lag in the level of medical services (βequity ≤ 0.149, p ≤ 0.01; βefficiency ≤ 0.461, p ≤ 0.01); the channel test results prove that managerial personnel and other technical personnel are key pathways in regulating the impact of medical staff on the level of medical services. Conclusion This study provides an in-depth analysis of the impact of health human resources on the level of medical services, revealing that both the scale and hierarchical structure of health human resources significantly affect the equity and efficiency of medical services. Furthermore, the influence of health human resources on the level of medical services exhibits regional heterogeneity and temporal characteristics. Robustness tests ensure the scientific validity and robustness of the research conclusions. This provides effective references for optimizing the allocation of health human resources and improving the level of medical services.

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Disease burden of ageing, sex and regional disparities and health resources allocation: a longitudinal analysis of 31 provinces in Mainland China

Cited by 3 publications

References 38 publications

Regional differences in health resource allocation: a longitudinal study in the Chengdu-Chongqing economic circle, China

Regional differences in health resource allocation: a longitudinal study in the Chengdu-Chongqing economic circle, China

The Entrepreneurial Welfare Mix: The Case of Community-Based Old Age Services in China

The impact of the scale and hierarchical structure of health human resources on the level of medical services-based on China’s four major economic regions

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