AUTHOR=Zheng Qi , Jin Yun , Xu Xinying TITLE=Artificial intelligence and job performance of healthcare providers in China JOURNAL=Frontiers in Public Health VOLUME=12 YEAR=2024 URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2024.1398330 DOI=10.3389/fpubh.2024.1398330 ISSN=2296-2565 ABSTRACT=Introduction

This study explores the influence of artificial intelligence (A.I.) applications on the job performance of healthcare providers, based on data from standardised-trained residents in the First People’s Hospital of Yunnan Province in China.

Methods

The ordinary least squares model is employed to examine the relationship between A.I. applications and job performance. To address potential endogeneity and missing variables, we utilise the propensity score matching method and alternative regression models.

Results

The findings indicate that the job performance of standardised-trained residents positively correlates with A.I. applications. This relationship remains robust after addressing endogenous and missing variables. Further discussion reveals that patients’ support mediates the relationship between A.I. and job performance. Under identical conditions, the job performance of female residents empowered by A.I. is found to be significantly better than that of their male counterparts. Conversely, no heterogeneity is observed regarding the impact of A.I. on the job performance of medical practitioners and clinical medical technicians.

Discussion

This study underscores the positive role of A.I. applications in enhancing the job performance of standardised-trained residents. The results highlight the mediating role of patient support and suggest gender-based differences in the efficacy of A.I. empowerment.