Weimin Gao

Background: As economic growth drives higher demand for health services, equitable health resource allocation becomes crucial to meet diverse healthcare needs. Since China’s reform and opening-up, increased government healthcare investment has not fully resolved regional disparities. Existing studies, often relying on methods other than the concentration index, fail to comprehensively analyze the link between resource inequities and economic factors. This study uses the concentration index and its decomposition to assess regional disparities and identify determinants of inequity, offering practical recommendations for optimizing resource distribution in China and similar developing nations.Methods: This study analyzed China’s healthcare resource allocation (institutions, beds, and workforce) from 2009 to 2021 using the concentration index to measure equity across socio-economic regions and its decomposition method to identify contributing factors to inequality.Results: From 2009 to 2021, the numbers of institutions per 1,000 people (IPK), beds per 1,000 people (BPK), doctors per 1,000 people (DPK), technicians per 1,000 people (TPK), and nurses per 1,000 people(NPK) in China increased. The concentration index (CI) for IPK remained negative, while BPK’s CI turned negative after 2013. CIs for DPK, TPK, and NPK stayed positive. The CI for IPK’s absolute value rose, while others decreased. Factors like population size (PS), population density(PD), geographical Location(GL), maternal mortality rate(MMR), rate of born-baby weighting less than 2.5 kg (RBWL25), and perinatal mortality rate (PMR) influenced unequal healthcare resource distribution, with PS and RBWL25 favoring developed areas, and PD, GL, and MMR favoring less developed regions. Additionally, urbanization level (UL), Out-of-Pocket (OPP), per capita health expenditures(PCHE), per capita gross domestic product(PCGDP), disposable income of urban residents(DIUR), government health expenditures (GHE), and number of insured(NI) positively impacted resource allocation to developed provinces, with varying effects.Conclusion: This study analyzes 2009–2021 panel data, revealing growth trends and regional disparities in China’s healthcare resource equity, focusing on institutions, beds, and workforce. Need variables (PS, PD, and RBWL25) reduced bed/doctor disparities, while MMR/PMR worsened maternal/nurse inequities. Non-need economic factors concentrated resources in affluent areas despite redistribution efforts. The findings highlight ongoing challenges in equitable distribution and offer crucial policy insights for China and other developing nations.

Purpose: This study aimed to clarify patterns of Berry’s acculturation strategy and further identify the factors influencing physician trust among internal migrants.Methods: This study used a sample of 1,200 respondents of Shanghai’s migrant population through an online survey (Wenjuanxing platform) from January 2021 to December 2021. K-means cluster analysis and multivariate logistic regression models were used to identify acculturation strategy patterns of internal migrants and the factors influencing their physician trust in China.Results: Among the 1,117 valid respondents, 85.5% were aged 18–39 years, 51.8% (579) were male, 74.8% (836) were married, and 62.9% (703) had completed university or junior college education, 62.1% (690) were covered by urban employee medical insurance, and 46.3% (517) had an annual income of 110,000–250,000 yuan. Through K-means clustering analysis, four clusters of acculturation strategy patterns were obtained: integration, assimilation, separation, and marginalization. When controlling for all significant socioeconomic and other covariates, compared to physician trust of the respondents adopting the separation acculturation strategy groups, the OR values of physician trust of the respondents adopting the integration and assimilation acculturation strategy groups were 1.979 (p < 0.01) and 1.585 (p < 0.01), respectively.Conclusion: Berry’s framework delineates four acculturation strategy patterns applicable to internal migrants in Chinese megacities, and the effects of these distinct patterns on trust in physicians have been demonstrated. This research provides valuable insights into the dynamics of doctor-patient relationships among internal migrants in China’s megacities. Therefore, it is advisable for the Chinese government to launch a combined effort from multiple stakeholders to adopt targeted interventions designed for specific demographic groups to foster greater trust in physicians among internal migrants.

Background: Healthcare resources are necessary for individuals to maintain their health. The Chinese government has implemented policies to optimize the allocation of healthcare resources and achieve the goal of equality in healthcare for the Chinese people since the implementation of the new medical reform in 2009. Given that no study has investigated regional differences from the perspective of healthcare resource agglomeration, this study aimed to investigate China’s healthcare agglomeration from 2009 to 2017 in China and identify its determinants to provide theoretical evidence for the government to develop and implement scientific and rational healthcare policies.Methods: The study was conducted using 2009–2017 data to analyze health-resource agglomeration on institutions, beds, and workforce in China. An agglomeration index was applied to evaluate the degree of regional differences in healthcare resource allocation, and spatial econometric models were constructed to identify determinants of the spatial agglomeration of healthcare resources.Results: From 2009 to 2017, all the agglomeration indexes of healthcare exhibited a downward trend except for the number of institutions in China. Population density (PD), government health expenditures (GHE), urban resident’s disposable income (URDI), geographical location (GL), and urbanization level (UL) all had positive significant effects on the agglomeration of beds, whereas both per capita health expenditures (PCHE), number of college students (NCS), and maternal mortality rate (MMR) had significant negative effects on the agglomeration of institutions, beds, and the workforce. In addition, population density (PD) and per capita gross domestic product (PCGDP) in one province had negative spatial spillover effects on the agglomeration of beds and the workforce in neighboring provinces. However, MMR had a positive spatial spillover effect on the agglomeration of beds and the workforce in those regions.Conclusion: The agglomeration of healthcare resources was observed to remain at an ideal level in China from 2009 to 2017. According to the significant determinants, some corresponding targeted measures for the Chinese government and other developing countries should be fully developed to balance regional disparities in the agglomeration of healthcare resources across administrative regions.

Objective: The study aimed to measure time trends of inequalities of the geographical distribution of health facilities and workforce in Shanghai from 2010 to 2016 and used a spatial autocorrelation analysis method to precisely detect the priority areas for optimizing health resource reallocation in metropolises like Shanghai in developing countries.Methods: The study used secondary data from the Shanghai Health Statistical Yearbook and the Shanghai Statistical Yearbook from 2011 to 2017. Five indicators on health resources, namely, health institutions, beds, technicians, doctors, and nurses, were employed to quantitatively measure the healthcare resource in Shanghai. The Theil index and the Gini coefficient were applied to assess the global inequalities in the geographic distribution of these resources in Shanghai. Global and local spatial autocorrelation was performed using global Moran's index and local Moran's index to illustrate the spatial changing patterns and identify the priority areas for two types of healthcare resource allocation.Results: Shanghai's healthcare resources showed decreasing trends of inequalities at large from 2010 to 2016. However, there still existed an unchanged over-concentration distribution in healthcare facilities and workforce density among districts in Shanghai, especially for doctors at the municipal level and facility allocation at the rural level. Through spatial autocorrelation analysis, it was found that there exhibited a significant spatial autocorrelation in the density distribution of all resources, and some identified priority areas were detected for resource re-allocation policy planning.Conclusion: The study identified the existence of inequality in some healthcare resource allocations in Shanghai from 2010 to 2016. Hence, more detailed area-specific healthcare resource planning and distribution policies are required to balance the health workforce distribution at the municipal level and institution distribution at the rural level, and particular geographical areas (low–low and low–high cluster areas) should be focused on and fully considered across all the policies and regional cooperation to ensure health equality for municipal cities like Shanghai in developing countries.