Regional disparities and influencing factors of high quality medical resources distribution in China

Abstract

Background With the gradual increase of residents’ income and the continuous improvement of medical security system, people’s demand for pursuing higher quality and better medical and health services has been released. However, so far little research has been published on China's high quality medical resources (HQMR). This study aims to understand the spatiotemporal variation trend of HQMR from 2006 to 2020, analyze regional disparity of HQMR in 2020, and further explore the main factors influencing the distribution of HQMR in China. Methods The study selected Class III level A hospitals (the highest level medical institutions in China) to represent HQMR. Descriptive statistical methods were used to address the changes in the distribution of HQMR from 2006 to 2020. Lorentz curve, Gini coefficient (G), Theil index (T) and High-quality health resource density index (HHRDI) were used to calculate the degree of inequity. The geographical detector method was used to reveal the key factors influencing the distribution of HQMR. Results The total amount of HQMR in China had increased year by year, from 647 Class III level A hospitals in 2006 to 1580 in 2020. In 2020, G for HQMR by population was 0.166, while by geographic area was 0.614. T was consistent with the results for G, and intra-regional contribution rates were higher than inter-regional contribution rates. HHRDI showed that Beijing, Shanghai, and Tianjin had the highest allocated amounts of HQMR. The results of the geographical detector showed that total health costs, government health expenditure, size of resident populations, GDP, number of medical colleges had a significant impact on the spatial distribution of HQMR and the q values were 0.813, 0.781, 0.719, 0.661, 0.492 respectively. There was an interaction between the influencing factors. Conclusions China's total HQMR is growing rapidly but is relatively inadequate. The distribution of HQMR by population is better than by geography, and the distribution by geography is less equitable. Population size and geographical area both need to be taken into account when formulating policies, rather than simply increasing the number of HQMR.

Ethnic disparities and temporal trends in health resource allocation: a retrospective decadal analysis in Sichuan, a multi-ethnic Province of Southwest China (2009–2019)

“…5 ). GDP per capita, a key economic development indicator, is widely recognized as a significant influence on health resources, as evidenced by numerous previous studies [ 25 , 28 – 31 ]. Although non-minority counties generally have higher GDP per capita than ethnic minority counties, the more substantial growth rate of Bed p1000 in Yi and other ethnic minority counties compared to non-minority counties attests to the effectiveness of preferential policies in increasing bed availability in these ethnic minority counties (Fig.…”

“…The Theil index (TI) was utilized as a metric to assess the disparities in health resource distribution across various categories by previous researches [ 5 – 7 , 20 , 24 , 25 ]. To enable a comprehensive analysis of overall equity, the TI was segregated into two components: intra-category and inter-category.…”

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

“…Although we identified abundant literature on the equity of HRA, most studies among these focused on the spatiotemporal regional differences of equity for basic medical resources at the national level [16,19], the changing trend of medical resources in urban agglomerations [28], and the influencing factors of medical resource allocation in a single province [25]. Few studies have examined the regional differences and influencing factors of HQMRs.…”

Telenursing needs and influencing factors in patients with type 2 diabetes mellitus: A cross‐sectional study

“…In reality, telenursing is the telematics‐based remote implementation of in‐person care services (Al‐Badri et al, 2022), which by its very nature still depends on actual nursing resources (Anderson et al, 2022). However, the distribution of high‐quality medical and health resources is unbalanced between urban and rural areas, and between eastern and western China (Wan et al, 2021; Yuan et al, 2023). Consequently, Glasgow et al (2000) established a pyramid model of resource support for chronic disease management based on the theory of social‐environmental support and developed a chronic illness resources survey (CIRS), used to evaluate multiple resource utilisation for chronic disease patients in disease management, which laid the foundation for research regarding chronic disease resources.…”