Comparing Regional Distribution Equity among Doctors in China before and after the 2009 Medical Reform Policy: A Data Analysis from 2002 to 2017

Digital economy and the medical and health service supply in China

The impact of the digital economy on the healthcare sector is becoming increasingly profound. This article focuses on the relationship between the development of China's digital economy and medical and health services supply. Based on panel data from 30 provinces in China from 2012 to 2021, the CRITIC weight method was applied to measure the supply capacity of medical and health services and the level of digital economy development, and the kernel density estimation method and Dagum Gini coefficient method was used to characterize the evolutionary trends and regional differences. Additionally, a two-way fixed-effects model is adopted to investigate the impact of digital economy development on medical and health services supply. The results show that both the supply capacity of healthcare services and the level of digital economy development have been increasing continuously in terms of evolutionary trends. From the perspective of regional differences, compared to the supply level of healthcare services, the regional differences in digital economy development are more significant. The intra-regional differences in medical and health services supply are greater than the inter-regional differences, while the development of the digital economy exhibits the opposite trend. The findings of this paper provide supports for China to enhance the development level of digital economy and improve supply of medical and health service.

Are Doctors Equally Distributed Throughout the World?

Background

As the vital and scarce resource of the health system, physicians are responsible for treating patients and saving lives and the equitable distribution of physicians among the whole population is a prerequisite to achieving health for all. We aimed to investigate inequality in physician distribution in the world using the Gini coefficient.

Methods

This descriptive-analytical study was conducted in 2021. The number of physicians and the population of countries were obtained from the WHO and United Nations (UN) databases. The Gini coefficient was calculated in three different modes and the distribution of physicians among countries in various Human Development Index (HDI) groups was determined using the physician ratio per 10,000 population.

Results

There were generally more than 13 million doctors in the world. About 43% of the world's physicians were available to 20% of the world's population in very high HDI countries, and 12% of the population had access to about 1% of physicians in low HDI countries. An average of 19.5 physicians are distributed per 10,000 population worldwide. The Gini coefficient between the four groups of HDI countries was 0.55, and that of all countries in the world was 0.640.

Conclusion

There was a shortage and inequality in the distribution of physicians worldwide. Governments should eliminate inequality in the distribution of the medical workforce, in particular physicians, by redoubling their efforts and accurate planning.

Inequality in benefit distribution of reducing the outpatient cost-sharing: evidence from the outpatient pooling scheme in China

Objective

The implementation of the outpatient pooling scheme in China has substantially elevated the compensation levels for outpatient expenses. This study aims to assess whether socioeconomically disadvantaged enrollees benefit proportionally compared to their non-disadvantaged counterparts.

Method

A cohort comprising 14,581 Urban and Rural Resident Basic Medical Insurance (URRBMI) enrollees and 830 Urban Employee Basic Medical Insurance (UEBMI) enrollees was derived from the China Health and Retirement Longitudinal Study 2018. Outpatient pooling scheme benefits were evaluated based on two metrics: the probability of obtaining benefits and the magnitude of benefits (reimbursement amounts and ratios). Two-part models were employed to adjust outpatient benefits for healthcare needs. Inequality in benefit distribution was assessed using the concentration curve and concentration index (CI).

Results

Following adjustments for healthcare needs, the CI for the probability of receiving outpatient benefits for URRBMI and UEBMI enrollees were - 0.0760 and - 0.0514, respectively, indicating an evident pro-poor pattern under the outpatient pooling scheme. However, the CIs of reimbursement amounts (0.0708) and ratio (0.0761) for URRBMI recipients were positive, signifying a discernible pro-rich inequality in the degree of benefits. Conversely, socioeconomically disadvantaged UEBMI enrollees received higher reimbursement amounts and ratios.

Conclusion

Despite a higher likelihood of socioeconomically disadvantaged groups receiving outpatient benefits, a pro-rich inequality persists in the degree of benefits under the outpatient pooling scheme in China. Comprehensive strategies, including expanding outpatient financial benefits, adopting distinct reimbursement standards, and enhancing the accessibility of outpatient care, need to be implemented to achieve equity in benefits distribution.

Dynamic distribution, regional differences and convergence of health workforce allocation in township health centers in China

This study evaluated the dynamic distribution, regional differences, and convergence of health workforce allocation in Township Health Centers in China during 2011-2020 using data obtained from the China Health Statistics Yearbook (2012-2021). The Gini coefficient and kernel density estimation were chosen to examine the dynamic distribution and regional differences in health workforce allocation in Township Health Centers in China and their components. σ convergence and β convergence were used to investigate the change trend of health workforce allocation in Township Health Centers. The results show that between 2011 and 2020, the number of licensed doctors and registered nurses per thousand population in Township Health Centers both increased largely and regional disparities still exist. In 2020, the largest differences in the density of licensed doctors and registered nurses were found in the eastern and central regions, respectively, and the intensity of trans-variation contributed the most to the overall disparities. The allocation of licensed doctors and registered nurses both exhibited σ convergence, absolute and conditional β convergence, indicating that the regional differences in health workforce in THCs among provinces will decrease. The growth of healthcare workforce was positively impacted by the urbanization rate, growth rate of government health expenditures and growth domestic product per capita, but negatively impacted by population density in rural areas and fiscal self-sufficiency.

Effect of doctor allocation policies on the equitable distribution of doctors in Thailand

BACKGROUND

Equitable geographic distribution of doctors is crucial for the provision of an accessible and efficient health service system. This study aimed to assess the effects of doctor allocation by the Thai Ministry of Public Health (MoPH) in relation to equity distribution.

METHODS

This descriptive study compared secondary data on the number of doctors, gross provincial products (GPP), and populations of 76 Thai provinces for the years 2017 and 2021. The ratio of doctors to 1000 population was used to measure the spatial distribution of doctors by province. Lorenz curves and the Gini coefficient were used to determine the equity of doctor distribution.

RESULTS

The results showed that the Gini coefficient decreased from 0.191 in 2017 to 0.03 in 2021 indicating that the equitable distribution of doctors improved after the MoPH commenced allocating newly graduated doctors according to health utilization in 2017. Compared to 2017, the percentage changes in the number of doctors were higher in provinces with lower doctor densities and in provinces with higher GPPs.

CONCLUSION

The equitable distribution of doctors in Thailand was affected by two main causes: the allocation of newly graduated doctors by the MoPH and the turnover rate of existing doctors.

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

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.

Equity assessment of the distribution of mental health beds in China: based on longitudinal data from 2011 to 2020

BACKGROUND

Mental health problems have become a public health problem that needs to be solved in China. However, medical resources for mental healthcare remain insufficient and unevenly distributed. The Chinese central government has taken many measures to address this issue over the last decade. This study aimed to evaluate the changes in equity in mental health bed allocation from 2011 to 2020.

METHODS

The data of this study came from the China Health Statistical Yearbook (2012-2021) and the China National Administrative Division Information Platform. The annual growth rate was used to evaluate the time trends of mental health beds. The Lorenz curve, Gini coefficient and Theil index were used to assess equity in the demographic and geographical dimensions. The distribution of mental health beds was visualized on a map using geographic information system (GIS) software.

RESULTS

The total number of mental health beds in China increased steadily from 2011 to 2020. At the national level, the Gini coefficient and Theil index all exhibited downward trends over time. The mental health bed allocation in terms of the demographic dimension was relatively equitable, with Gini values all less than 0.3; however, the Gini coefficients by geographical area were all more than 0.6, indicating inequity. Intraregional contribution rates were higher than interregional contribution rates, which were all above 60%.

CONCLUSION

The overall distribution equity of mental health beds improved from 2011 to 2020. The equity of mental health beds in terms of population size is superior to that in terms of geographical area. Intraregional differences are the main source of inequity. In particular, differences within the western region need to be given attention. Thus, the findings from this study emphasize that the demographic and geographical distributions and all influencing factors should be considered when the government makes mental health resource allocation policies.

Spatial distribution, regional differences, and dynamic evolution of the medical and health services supply in China

The imbalance of medical and health services supply (MHSS) is a significant public health concern as regional economic development disparities widen in China. Based on the provincial panel data of medical and health services, this paper constructed an evaluation index system and used the two-stage nested entropy method to measure the MHSS level of 31 provinces in China from 2005 to 2020. Then we used the standard deviation ellipse, Dagum Gini coefficient, β convergence model, kernel density estimation and Markov chain to investigate the spatial distribution, regional differences, and dynamic evolution of MHSS. According to the results of these analysis, the conclusions are drawn as follows: (1) In general, the MHSS level in China showed a significant up-ward trend from 2005 to 2020. However, the MHSS level among different provinces showed a non-equilibrium characteristic. (2) Regional comparison shows that the eastern region had the highest level, and the central region had the lowest level. The eastern and central regions presented polarization, while the western region showed unremarkable gradient effect. (3) During the period, the overall regional differences, intra-regional differences, and inter-regional differences of MHSS level all showed convergence. (4) The economic development, urbanization rate, fiscal self-sufficiency rate, and foreign direct investment had significant impacts on the convergence. (5) The provinces with high levels had the positive spillover effect. The findings of this paper provide theoretical supports for optimizing the allocation of health resources and improving the equity of MHSS.

Measuring the Inequalities in the Distribution of Public Healthcare Resources by the HRDI (Health Resources Density Index): Data Analysis from 2010 to 2019

Background: In China, a developing country, the imbalance of development exists in different fields, and the inequalities in the distribution of healthcare services have garnered increasing attention. This study aimed to assess the healthcare services allocation and compare the latest distribution ratios of the essential healthcare indicators with the national requirement values announced by the government to research the level of healthcare development in China. Methods: Data were extracted from the Chinese Statistical Yearbook (2010–2019). The Healthcare Resource Density Index (HRDI) was used to evaluate equity in the demographic and geographical dimensions. The requirement values related to the ratio of doctors, nurses, and institution beds per thousand people were drawn from government documents. The data of healthcare serviceability indicators were compared with those requirements to check the situation of each province’s medical development. Results: From 2010 to 2018, there was a sustainable upward trend in government investment, however, a noticeable drop in the investment in northeast areas was seen. Although the HRDI of the institutions, beds, doctors, and nurses experienced some small fluctuations over the years, the developing areas in the middle-west areas had almost approached the level of developed east areas. There were only four provinces that met the requirements of the government in all three indicators (the ratio of institution beds, doctors, and nurses per thousand people). Conclusion: The equality of the distribution of healthcare services in China was unfair between the eastern and middle-western areas. The government launched the developing requirements and paid additional attention to narrowing the imbalance among different economic level regions to meet the needs of the local people. Although many provinces did not meet the requirements for medical resources in 2019, the distribution of healthcare services was approached relatively equitably countrywide.

A critical review of definitions of rural areas in Indonesia and implications for health workforce policy and research

Background

Choosing the appropriate definition of rural area is critical to ensuring health resources are carefully targeted to support the communities needing them most. This study aimed at reviewing various definitions and demonstrating how the application of different rural area definitions implies geographic doctor distribution to inform the development of a more fit-for-purpose rural area definition for health workforce research and policies.

Methods

We reviewed policy documents and literature to identify the rural area definitions in Indonesian health research and policies. First, we used the health policy triangle to critically summarize the contexts, contents, actors and process of developing the rural area definitions. Then, we compared each definition’s strengths and weaknesses according to the norms of appropriate rural area definitions (i.e. explicit, meaningful, replicable, quantifiable and objective, derived from high-quality data and not frequently changed; had on-the-ground validity and clear boundaries). Finally, we validated the application of each definition to describe geographic distribution of doctors by estimating doctor-to-population ratios and the Theil-L decomposition indices using each definition as the unit of analysis.

Results

Three definitions were identified, all applied at different levels of geographic areas: “urban/rural” villages (Central Bureau of Statistics [CBS] definition), “remote/non-remote” health facilities (Ministry of Health [MoH] definition) and “less/more developed” districts (presidential/regulated definition). The CBS and presidential definitions are objective and derived from nationwide standardized calculations on high-quality data, whereas the MoH definition is more subjective, as it allows local government to self-nominate the facilities to be classified as remote. The CBS and presidential definition criteria considered key population determinants for doctor availability, such as population density and economic capacity, as well as geographic accessibility. Analysis of national doctor data showed that remote, less developed and rural areas (according to the respective definitions) had lower doctor-to-population ratios than their counterparts. In all definitions, the Theil-L-within ranged from 76 to 98%, indicating that inequality of doctor density between these districts was attributed mainly to within-group rather than between-group differences. Between 2011 and 2018, Theil-L-within decreased when calculated using the MoH and presidential definitions, but increased when the CBS definition was used.

Conclusion

Comparing the content of off-the-shelf rural area definitions critically and how the distribution of health resource differs when analysed using different definitions is invaluable to inform the development of fit-for-purpose rural area definitions for future health policy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12961-022-00847-w.

Knowledge, Attitudes, and Social Responsiveness Toward Corona Virus Disease 2019 (COVID-19) Among Chinese Medical Students-Thoughts on Medical Education

Purpose: To assess knowledge, attitudes, and social responsiveness toward COVID-19 among Chinese medical students. Methods: Self-administered questionnaires were used to collect data from 889 medical students in three well-known Chinese medical universities. The questionnaire was comprised of three domains which consisted of demographic characteristic collection, seven items for knowledge, and eight items for attitudes and social responsiveness toward COVID-19. Data from different universities were lumped together and were divided into different groups to compare the differences, including (1) students at the clinical learning stage (Group A) or those at the basic-medicine stage (Group B) and (2) students who have graduated and worked (Group C) or those newly enrolled (Group D). Results: Medical students at group B had a weaker knowledge toward COVID-19 than did students at group A, especially in the question of clinical manifestations (p < 0.001). The percentage of totally correct answers of COVID-19 knowledge in group C was higher than that in Group D (p < 0.001). There were significant differences between groups C and D in the attitudes and social responsiveness toward COVID-19. Surprisingly, we found that the idea of newly enrolled medical students could be easily affected by interventions. Conclusions: In light of this information, medical education should pay attention not only to the cultivation of professional knowledge and clinical skills but also to the positive interventions to better the comprehensive qualities including communicative abilities and empathy.

An equity evaluation in stroke inpatients in regard to medical costs in China: a nationwide study

Background

Stroke has always been a severe disease and imposed heavy financial burden on the health system. Equity in patients in regard to healthcare utilization and medical costs are recognized as a significant factor influencing medical quality and health system responsiveness. The aim of this study is to understand the equity in stroke patients concerning medical costs and healthcare utilization, as well as identify potential factors contributing to geographic variation in stroke patients’ healthcare utilization and costs.

Methods

Covering 31 provinces in mainland China, our main data were a 5% random sample of stroke claims from Urban Employees Basic Medical Insurance (UEBMI) and Urban Residents Basic Medical Insurance (URBMI) from 2013 to 2016. The Theil index was employed to evaluate the equity in stroke patients in regard to healthcare utilization and medical costs, and the random-effect panel model was used to explore the impact of province-level factors (health resource factors, enabling factors, and economic factors) on medical costs and health care utilization.

Results

Stroke patients’ healthcare utilization and medical costs showed significant differences both within and between regions. The UEBMI scheme had an overall lower Theil index value than the URBMI scheme. The intra-region Theil index value was higher than the inter-region Theil index, with the Theil index highest within eastern China, China’s richest and most developed region. Health resource factors and enabling factors (represented by reimbursement rate and education attainment years) were identified significantly associated with medical costs (P < 0.05), but have no impact on average length of stay.

Conclusions

China’s fragmented urban health insurance schemes require further reform to ensure better equity in healthcare utilization and medical costs for stroke patients. Improving education attainment, offering equal access to healthcare, allocating health resources reasonably and balancing health services prices in different regions also count.

Regional Disparities of Rehabilitation Resources for Persons with Disabilities in China: Data from 2014 to 2019

Although the United Nations’ Convention on the Rights of Persons with Disabilities enshrines the right to health for all persons with disabilities (PDs), PDs face health disparities in terms of access to rehabilitation resources, which is important for service supply. This study aimed to explore the trends and distribution of rehabilitation resources for PDs in China from 2014 to 2019, explore the main factors that influence equity, and provide suggestions for policymakers. Data were obtained from the annual China Statistical Bulletin on the Development of Disabled Persons and the database of the China Disabled Persons’ Federation. Six types of rehabilitation resources were chosen to measure the trends in allocation and equity. Data on disparities were analyzed based on western, central, and eastern regions. The Health Resource Density Index and Theil Index were calculated to determine the degree and density of unfairness. The findings show a steady increasing trend in the amount of rehabilitation resources in China from 2014 to 2019. The density and equity of allocation of rehabilitation resources have improved greatly in recent years. Regional disparities were principally caused by differences within the regions. Suggestions including expanding investment in rehabilitation resources and developing rehabilitation systems were put forward.