Assessing spatial access to public and private hospitals in Sichuan, China: The influence of the private sector on the healthcare geography in China

In 2009, the Chinese government launched a new round of healthcare reform, which encourages development of private hospitals. Meanwhile, many public hospitals in China also became increasingly profit-oriented. These trends have led to concerns about social justice and regional disparity. However, there is a lack of empirical scientific analysis to support the debate. We started to fill this gap by conducting a regional-level analysis of spatial variation in spatial access to hospitals in the Sichuan Province. Such variation is an important indication of (in) equity in healthcare resource allocation. Using data of 2012, we intended to provide a snapshot of the situation that was a few years later since the new policies had set out. We employed two methods to quantify the spatial access: the nearest-neighbor method and the enhanced two-step floating catchment area (E2SFCA) method. We recognized two sub-regions of Sichuan: the rural West Sichuan and the well-developed East Sichuan. We classified the hospitals using both ownership and level. We applied the analysis to the resulting groups of hospitals and their combinations in the two sub-regions. The two sub-regions have a high contrast in the spatial access to hospitals, in terms of both quantity and spatial pattern. Public hospitals still dominated the service in the province, especially in the West Sichuan, which had been solely relying on public hospitals. Private hospitals only occurred in the East Sichuan, and at the primary level, they had surpassed public hospitals in terms of spatial accessibility. However, the governmental health expenditures seemed to be disconnected with the actual situation of the spatial access to hospitals. The government should continue carrying on its responsibility in allocating healthcare resources, be cautious about marketizing public hospitals, and encourage private hospitals to expand into rural areas. Methodologically, the results from the two methods are concurring but not identical. The E2SFCA method calculates population-adjusted density of hospitals, which measures deviation from the expected pattern, and therefore is more meaningful in assessing associations of the spatial access to hospitals with other factors (e.g., population density and investment).