The spatial spillover effects of digital transformation on healthcare services quality.

OBJECTIVE

Economic growth and improved material living standards have raised people's expectations for healthcare service quality. The digitalization level of healthcare organizations can significantly impact meeting these expectations.

METHODS

This study uses Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to calculate the digital transformation and healthcare service quality composite index. Digital transformation and healthcare service quality spatiotemporal evolution are studied using kernel density estimation, spatial Moran's I index and trend surface analysis. Second, the spatial Durbin model explores how digitalization directly impacts healthcare quality. Finally, digital transformation's spatial spillover impacts on healthcare service quality are examined using partial differential decomposition.

RESULTS

The digital transformation gap is expanding as areas develop differently. Notwithstanding west-east expansion of digital transformation across China, the centre region demonstrates greatest expansion compared with northern or southern regions. Beijing-Tianjin-Hebei, the eastern coastline region, Sichuan-Chongqing and Guangdong are high-level, whereas the northeast, northwest and Yunnan-Guizhou are low. Healthcare quality has improved annually, although regional gaps have grown. The centre was found to have a greater healthcare gap than the east and west. North exceeds south, with the north-south gap growing in 2021 over 2012. Digital transformation improves local healthcare but degrades neighbouring care.

CONCLUSION

Situated within a digital framework, this research examines how digital transformation might improve the quality of healthcare services and the spatial spillover effects. The results indicate that digital transformation may markedly improve the quality of medical services and have spatial spillover effects. Limitations identified in this study include constraints in research methodologies and modest sample size. Consequently, future studies may refine the provincial sample to the level of prefecture-level cities, employing moderation and mediation effect models to more precisely evaluate the impact mechanism of digital transformation on the quality of medical services.