Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China

ObjectiveThe 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. MethodsThe 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. ResultsShanghai'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. ConclusionThe 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.

Automated summary

This study aimed to measure the trends of inequalities in the geographical distribution of health facilities and workforce in Shanghai from 2010 to 2016 and used spatial autocorrelation analysis to identify priority areas for optimizing health resource allocation. By analyzing secondary data, the study quantitatively measured healthcare resources in Shanghai and found decreasing trends of inequalities. However, there still existed over-concentration in certain areas. Through spatial autocorrelation analysis, priority areas for resource reallocation were identified. The study highlights the need for detailed area-specific healthcare resource planning and distribution policies to ensure balance in the distribution of health workforce and facilities.