This paper is in the following e-collection/theme issue:

Artificial Intelligence (2129) Generative Language Models Including ChatGPT (708) Adoption and Change Management of eHealth Systems (894) Ethical, Legal, and Social Issues in AI (102) Digital Health, Telehealth and e-Innovation in Clinical Settings (556)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70789, first published .
Adoption of Large Language Model AI Tools in Everyday Tasks: Multisite Cross-Sectional Qualitative Study of Chinese Hospital Administrators

Adoption of Large Language Model AI Tools in Everyday Tasks: Multisite Cross-Sectional Qualitative Study of Chinese Hospital Administrators

Adoption of Large Language Model AI Tools in Everyday Tasks: Multisite Cross-Sectional Qualitative Study of Chinese Hospital Administrators

Authors of this article:

Jun Chen1 Author Orcid Image ;   Yu Liu2 Author Orcid Image ;   Peng Liu1 Author Orcid Image ;   Yiming Zhao1 Author Orcid Image ;   Yan Zuo3, 4, 5 Author Orcid Image ;   Hui Duan6 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Jun Chen   1 , MSMHA ;   Yu Liu   2 , MD ;   Peng Liu   1 , MD ;   Yiming Zhao   1 , MMed ;   Yan Zuo   3, 4, 5 , MSN ;   Hui Duan   6 , PhD

1 Medical Services Management Department, Peking University People's Hospital, Beijing, China

2 Department of Obstetrics and Gynecology, Peking University Shenzhen Hospital, Shenzhen, China

3 Department of Gynecology and Obstetrics Nursing, West China Second University Hospital, Sichuan University, Chengdu, China

4 West China School of Nursing, Sichuan University, Chengdu, China

5 Key laboratory of Birth Defects and Related Disease of Women and Children (Sichuan University), Ministry of Education, Chengdu, China

6 School of Public Administration and Policy, Renmin University of China, Beijing, China

Corresponding Author:

  • Hui Duan, PhD
  • School of Public Administration and Policy
  • Renmin University of China
  • #59 Zhongguancun Street, Haidian District
  • Beijing 100872
  • China
  • Phone: 86 1062511122
  • Email: rucduanhui@ruc.edu.cn