Effectiveness of hierarchical medical system and economic growth: based on China’s urban vs. rural health perspectives - Zhao, Yongze; Qiao, Qingyu; Xu, Xian; Bian, Ying (Frontiers in Public Health, 2024)
Background The hierarchical medical system is an important measure to promote equitable healthcare and sustain economic development. As the population’s consumption level rises, the demand for healthcare services also increases. Based on urban and rural perspectives in China, this study aims to investigate the effectiveness of the hierarchical medical system and its relationship with economic development in China. Materials and methods The study analyses panel data collected from Chinese government authorities, covering the period from 2009 to 2022. According to China’s regional development policy, China is divided into the following regions: Eastern, Middle, Western, and Northeastern. Urban and rural component factors were downscaled using principal component analysis (PCA). The factor score formula combined with Urban–rural disparity rate (ΔD) were utilized to construct models for evaluating the effectiveness of the hierarchical medical system from an urban–rural perspective. A Vector Autoregression model is then constructed to analyze the dynamic relationship between the effects of the hierarchical medical system and economic growth, and to predict potential future changes. Results Three principal factors were extracted. The contributions of the three principal factors were 38.132, 27.662, and 23.028%. In 2021, the hierarchical medical systems worked well in Henan (F = 47245.887), Shandong (F = 45999.640), and Guangdong (F = 42856.163). The Northeast (ΔDmax = 18.77%) and Eastern region (ΔDmax = 26.04%) had smaller disparities than the Middle (ΔDmax = 49.25%) and Western region (ΔDmax = 56.70%). Vector autoregression model reveals a long-term cointegration relationship between economic development and the healthcare burden for both urban and rural residents (βurban = 3.09, βrural = 3.66), as well as the number of individuals receiving health education (β = −0.3492). Both the Granger causality test and impulse response analysis validate the existence of a substantial time lag between the impact of the hierarchical medical system and economic growth. Conclusion Residents in urban areas are more affected by economic factors, while those in rural areas are more influenced by time considerations. The urban rural disparity in the hierarchical medical system is associated with the level of economic development of the region. When formulating policies for economically relevant hierarchical medical systems, it is important to consider the impact of longer lags.