npj Health Systems · Published 2026-06-08 · DOI 10.1038/s44401-026-00101-3
Wei Zhang, Saibing Qi, Yu Hu, Xiaolin Zhai, Wangsong Zhai, Sichang Liu, Zhenwei Li, Wei Su, Simiao Liu, Wu Liu, Jie Liu, Jiejing Yin, Mengyi Xie, Ang Zheng, Lanying Zhang, Ai He, Ruifen Zhang, Weilin Liu, Kan Ding, Lianzhong Wu, Yongsheng Meng, Qi Li, Baima Yangjin, Ting Li, Chao Liu, Da Gao, Heng He, Fei Long, Xiaoyan Ge, Xiao-Xiao Sun, Haizhao Ma, Tiansheng Su, Shuhao Du, Mengyun Chen, Yahui Feng, Zhen Song, Jinyu Wang, Robert Peter Gale, Xiaowen Gong, Qiujin Shen, Junren Chen
Abstract Using artificial intelligence (AI) to prescribe drugs has advanced slowly. Whether a “doctor-in-the-loop” design would increase acceptance of drug-prescribing AI is unknown, as are settings where physicians envision AI-driven drug prescription most likely to be implemented. We surveyed a stratified sample of 2708 physicians throughout China to interrogate their opinions on drug-prescribing AI. Most respondents (78%) are receptive to using drug-prescribing AI and anticipate doing so within 5 years. Respondents suggested initial settings for AI-driven drug prescribing include situations where there are standard guidelines (74%), where the decision is whether to continue a current prescription in someone (55%), and where prescribing decisions rely on high-complexity clinical data (44%). Many (66%) indicated a preference for conditional to fully autonomous drug-prescribing AI. Clustering analysis identified 2 psychological profile-types, “optimists” and “pragmatists”, who have different standards for model efficacy, expediency, explainability, and governance/stewardship for drug-prescribing AI. A high level of using medical AI is the strongest predictor for being an optimist (OR = 2.98 [2.53, 3.51]; P < 0.0001). In conclusion, our data point to the wide acceptability of conditional autonomous drug-prescribing AI among Chinese physicians. Moreover, disparity in optimism about drug-prescribing AI is caused by disparity in prior exposure to medical AI.
Abstract from DOAJ. Public domain (CC0 1.0).
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Zhang, W., Qi, S., Hu, Y., et al. (2026). Receptiveness of physicians towards artificial intelligence-driven drug prescription: a nationwide survey. npj Health Systems. https://doi.org/10.1038/s44401-026-00101-3