Ketao Lin, Feng Xie, Qiao Quan, Yongshan Chen, Jie Ye
Against the backdrop of the digital economy and the 'Healthy China' initiative, clarifying the mechanisms through which digital technologies influence public health can help improve public health governance. Drawing on panel data from 30 Chinese provinces covering the period 2012-2024, this paper employs the Critic-entropy weighting method and a dual machine learning model to address the shortcomings of existing research in causal identification, mechanism decomposition and boundary analysis. The results indicate that digital technologies significantly improve public health; per capita healthcare expenditure plays a partial mediating role; the empowerment effect exhibits a regional gradient, being strongest in the central regions, followed by the western regions, and relatively weaker in the eastern regions; and the number of outpatient visits exerts a positive moderating effect. These findings provide empirical guidance for the differentiated advancement of digital health initiatives in China.