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ORIGINAL RESEARCH article

Front. Public Health
Sec. Digital Public Health
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1398330

Artificial Intelligence and Job Performance of Healthcare Providers in China

Provisionally accepted
Qi Zheng Qi Zheng 1Yun Jin Yun Jin 2*Xinying Xu Xinying Xu 3
  • 1 Capital University of Economics and Business, Beijing, Beijing Municipality, China
  • 2 The First People’s Hospital of Yunnan Province, Kunming, China
  • 3 University of International Business and Economics, Beijing, Beijing Municipality, China

The final, formatted version of the article will be published soon.

    Based on the data from standardised-trained residents in the First People’s Hospital of Yunnan Province in China, this study explores the influence of artificial intelligence (A.I.) applications on the job performance of healthcare providers, employing the ordinary least squares model. The study finds that the standardised-trained residents’ job performance positively correlates with A.I. applications. After handling the problems of endogenous and missing variables based on the propensity score matching method, as well as variable and alternation of regression model the results are still robust. In further discussion, patients’ support was found to mediate the relationship between A.I. and job performance, and under the same conditions, the job performance of female residents empowered by A.I. was found to be significantly better than that of their male counterparts. Contrarily, no heterogeneity was observed with regard to how A.I. impacts the job performance of medical practitioners and clinical medical technicians.

    Keywords: artificial intelligence, job performance, healthcare providers, patients' support, China instrumental variable method

    Received: 09 Mar 2024; Accepted: 05 Jul 2024.

    Copyright: © 2024 Zheng, Jin and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yun Jin, The First People’s Hospital of Yunnan Province, Kunming, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.