The coupling coordination between digital village construction and rural healthcare service efficiency in China: dynamic evolution, spatial difference and driving factors

TL;DR

This study examines how digital village development and rural healthcare efficiency in China are coordinated, finding regional imbalances and factors influencing their relationship.

Contribution

The paper introduces a dynamic analysis of coupling coordination and spatial disparities between digital village construction and rural healthcare efficiency in China.

Findings

The national coordination level improved from 0.589 to 0.665 between 2015 and 2022.

Regional disparities within areas increased, while differences between regions decreased.

Economic and government support positively influence coordination, while urbanization and health human capital negatively affect it.

Abstract

Promoting coordination between digital village construction and rural healthcare service efficiency is central to advancing rural social progress and implementing the Healthy China strategy, and has drawn growing attention in public administration and health economics.

Using panel data from 29 provinces across China spanning 2015–2022, the study employed the coupling coordination degree model to assess the level of coupling coordination degree (CCD) between digital village construction and the effectiveness of rural healthcare services. The Dagum’s Gini coefficient was applied to analyze regional disparities, while kernel density estimation and spatial Markov chain were utilized to examine reveal their spatio-temporal dynamic evolution patterns. Employed quantile regression to analyze the primary factors influencing the CCD.

The national coordination level has steadily improved from 0.589 to 0.665, but some provinces have yet to reach the coordination stage. The national Gini coefficient has risen from 0.148 to 0.158, with within-regional disparities continuing to increase, while inter-regional disparities have gradually narrowed. Kernel density analysis showed that the right tail of the eastern region continued to widen, with benchmark provinces emerging within the region, while the central and western regions showed a trend towards evolution of double peak and multi-peak, respectively, with increased differentiation within the region. Spatial Markov chain results indicate that stable synergistic relationships exist between high-level regions or low-level regions; medium-to-high-level regions exhibit a certain degree of siphoning effect on surrounding medium-to-low-level regions. Economic, government support, and health needs are positive factors driving the CCD development, while health human capital and urbanization rate are negative factors.

The coordinated development of digital village construction and rural healthcare service efficiency has achieved positive results, but issues such as regional development imbalances, intensified within regional differentiation trends, development lock-in, and resource siphoning still require attention. The CCD is influenced to varying degrees by social, economic, and demographic factors. In the future, efforts should be made in two areas: regional balance and interregional coordination, and strengthening government support to promote the effective allocation of resources and the coordinated advancement of digital healthcare.

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