Temporal-Spatial Evolution and Trend Prediction of the Supply Efficiency of Primary Medical Health Service—An Empirical Study Based on Central and Western Regions of China

Wu, Fang; Gu, Ming-Yao; Zhu, Chenming; Qu, Yingna

doi:10.3390/ijerph20031664

Cited by 3 publications

(1 citation statement)

References 52 publications

(63 reference statements)

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“…The larger the bandwidth, the smaller the variance of the kernel density estimate. In this study, we adopted a smoother Gaussian kernel and used kernel density estimation to explain the dynamic evolution of the HQMR distribution in EMAs from four perspectives [40]: (1) distribution position; (2) shape; (3) ductility; and (4) polarisation of the curve.…”

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confidence: 99%

Regional differences, dynamic evolution, and influencing factors of high-quality medical resources in China’s ethnic minority areas

Hao,

Liang,

Chen

et al. 2023

Preprint

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Background: In China, as people’s standard of living improves and the medical service system becomes more sophisticated, the demand for higher-quality and improved healthcare services is steadily rising. Inequality in health resource allocation (HRA) is more pronounced in ethnic minority areas (EMAs) than in developed regions. However, little research exists on high-quality medical resources (HQMRs) in China’s EMAs. Hence, we examined the spatiotemporal dynamic evolution of HQMRs in China’s EMAs from 2007 to 2021 and identified the main factors affecting their respective HQMR levels. Methods: We selected tertiary hospitals to represent the quality of healthcare resources. We employed descriptive statistical techniques to analyze changes in the distribution of HQMRs from 2007 to 2021. We used the Dagum Gini coefficient and kernel density approach to analyse the dynamic evolution of HQMRs in China’s EMAs. We utilised the least squares dummy variable coefficient (LSDVC) to identify key factors affecting HQMR. Results: The number of HQMRs in each EMA has risen annually. The average number of tertiary hospitals increased from 175 in 2007 to 488 in 2021. The results of the Dagum Gini coefficient revealed that the differences in the HQMR level in China’s EMAs have slowly declined, and intra-regional disparities have now become the primary determining factor influencing overall variations. The kernel density plot indicated that the HQMR level improved significantly during the study period, but bifurcation became increasingly severe. Using the LSDVC for analysis, we found that gross domestic product (GDP) per capita, the size of the resident population, and the number of students enrolled in general higher education exhibited a significant negative correlation with HQMR levels, while GDP and urbanisation rate had a significant promoting effect. Conclusions: The HQMR level in EMAs has risen rapidly but remains inadequate. The differences in HQMR between regions have continued to narrow, but serious bifurcation has occurred. Policymakers should consider economic growth, education, and population size rather than simply increasing the number of HQMRs everywhere.

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confidence: 99%

Regional differences, dynamic evolution, and influencing factors of high-quality medical resources in China’s ethnic minority areas

Hao,

Liang,

Chen

et al. 2023

Preprint

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Measurement and characteristics of the temporal-spatial evolution of China’s healthcare services efficiency

Ye,

Tao

2023

Arch Public Health

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Background Healthcare services efficiency (HSE) is directly related to the healthcare demands of the general public and also plays an essential role in the country’s coordinated economic and social development. Methods In this study, the stochastic frontier approach (SFA)-Malmquist model was applied to measure the HSE of 31 Chinese provinces based on panel data from 2010–2020. Then, kernel density estimation, Markov chain, and exploratory spatial data analysis were adopted to study the temporal-spatial dynamic evolution characteristics of the HSE. Results The study found that China’s HSE showed an average value of approximately 0.841, indicating room for improvement. The HSE varied significantly across regions, presenting an “East > Central > West” distribution layout. The TFP of healthcare services in China grew by 1.6% per year, driven mainly by technological progress of 1.8% per year. The trend of the HSE shifting to a high level in China was significant, but its evolution exhibited stability of maintaining the original state, and it was harder to achieve leapfrog transfer. The temporal-spatial evolution of the HSE was also significantly affected by geospatial factors, with a clear spatial spillover effect and spatial agglomeration characteristics. Provinces with high-level HSE exhibited positive spatial spillover effects, while provinces with low-level HSE had negative spatial spillover effects. Thus, the “club convergence” phenomenon of “high efficiency concentration, low efficiency agglomeration, high levels of radiation, and low levels of suppression” was formed in the spatial distribution. Conclusions The results indicate that countermeasures should be taken to improve the HSE in China. Theoretical support for the improvement of HSE is provided in this paper.

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Research on Driving Factors of Forest Ecological Security: Evidence from 12 Provincial Administrative Regions in Western China

Guo

Zhu

et al. 2023

Sustainability

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Forests are associated with countrywide ecological security, and there are significant differences in the forests of different regions. Based on the DPSIR model, 25 indicators were selected from five dimensions to determine the index system, and the entropy-weighted TOPSIS method and gray correlation were applied to determine the index of western China’s forests. The spatial distribution map was used to observe the spatial changes of forests. The results show that first, Inner Mongolia (0.466) has the best forest ecological security status and Ningxia (0.124) has the worst forest resource status. Second, the first and most frequent correlation is the area of planted forests (I1). The last and most frequent correlation is sulfur dioxide emission (P2). Thirdly, Inner Mongolia and Szechwan belong to the high ecological safety–high economic level, Yunnan, Guangxi, and Tibet belong to the high ecological safety–low economic level, and Gansu and Guizhou belong to the low ecological safety–low economic level. The rest of the regions are classified in the low ecological security–high economic level. Fourth, the forest ecological security in western China has gradually become better, with the security index increasing from 0.417 to 0.469, with an average annual increase of 12.47%.

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Temporal-Spatial Evolution and Trend Prediction of the Supply Efficiency of Primary Medical Health Service—An Empirical Study Based on Central and Western Regions of China

Cited by 3 publications

References 52 publications

Regional differences, dynamic evolution, and influencing factors of high-quality medical resources in China’s ethnic minority areas

Regional differences, dynamic evolution, and influencing factors of high-quality medical resources in China’s ethnic minority areas

Measurement and characteristics of the temporal-spatial evolution of China’s healthcare services efficiency

Research on Driving Factors of Forest Ecological Security: Evidence from 12 Provincial Administrative Regions in Western China

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