Trend of Gini coefficient of healthcare resources in China from 1998 to 2016

Abstract

Background: Healthcare disparities in China are attracting attention not only in the country but also worldwide. However, few studies have evaluated the changes in equality of healthcare resource distribution among provinces in China. This study was conducted to provide healthcare resource allocation advice to government medical management institutions. We aimed to (I) analyze changes in healthcare disparities in China from 1998 to 2016 through data visualization and (II) determine what factors are related to the changes. Methods: We evaluated healthcare disparities in China by collecting statistical data on healthcare in China from 1998 to 2016 and calculating the Gini coefficient of healthcare resource distribution among the provinces, and comparatively observed the trend of Gini coefficient. Data used in this study were taken from the China Statistical Yearbook (1999-2017).Results: From 2008 to 2016, the Gini coefficient for doctors and nurses dropped by 0.048 (39.4%) and 0.058 (40.9%), respectively. The increase rate of number of nurses is the highest (109.0%), and at the same time, the distribution of nurses is also the most significant. On the other hand, since 2002, the Gini coefficient of healthcare institutions has fluctuated between 0.150 and 0.200. few changes were found in number of medical institutions.Conclusions: Since 2004, the distribution of health human resource has been improving due to the abundance of healthcare resources in China; however, the distribution of healthcare institutions has not been improving. We consider that the enrichment of medical resources has a positive impact on the distribution of human resources, but not on the distribution of physical and financial resources. This situation is considered to be one of the results of several health issues in China, such as the existence of super hospitals with thousands of beds in the inland areas, which interferes with the establishment of China's hierarchical medical system.

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

“…Overall, the allocation of health workforce in THCs is relatively fair and the Gini coefficient for both doctors density and nurses density have decreased. This is consistent with previous studies [ 8 , 63 , 64 ]. The reason for this is that some low-level areas, especially those that previously experienced a shortage of licensed doctors and registered nurses, have increased their allocation level, while areas with higher levels of allocation kept their number of health technicians stable, narrowing the gap between regions.…”

“…Despite these notable advancements, China's healthcare system continues to grapple with significant challenges, one of which pertains to the uneven allocation of healthcare resources [ [8] , [9] , [10] , [11] ]. Even within the same city, like Shanghai, which represents the highest level of urbanization in China, there still existed regional difference [ 12 ].…”

Distribution of Primary Healthcare Centers Between 2017 and 2021 Across Saudi Arabia

“…A Chinese study, for example, used data from the Chinese Statistical Yearbook (1999-2017) from 2008 to 2016, the Gini coefficients for healthcare institutions fluctuated between 0.150 and 0.200, fell by 0.048 (39.5%) and 0.058 (40.9%), respectively. At the same time that the number of nurses is growing at the fastest pace (109.0%), the distribution of nurses is also of the utmost importance [ 10 ]. In another study conducted in 18 states of Sudan using state-level data on health resources and health outcomes from the Sudan Health Statistical Report of 2016, the Gini coefficient values vary from 0.32 for hospitals and 0.36 for healthcare centers [ 11 ].…”

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

“…Based on published studies, China had an imbalance distribution of health services among other areas and had gaps between urban and suburban areas [ 12 ]. A Chinese study showed that inequalities existed between urban and suburban areas due to an imbalance of economic levels and differences in land size and population [ 13 , 14 ]. Many studies have focused on equality research and used the Gini or Theil Indexes, popular methods in this field [ 15 , 16 ].…”