Receptiveness of physicians towards artificial intelligence-driven drug prescription: a nationwide survey.
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Zhang Wei, Qi Saibing, Hu Yu, Zhai Xiaolin, Zhai Wangsong, Liu Sichang, Li Zhenwei, Su Wei, Liu Simiao, Liu Wu, Liu Jie, Yin Jiejing, Xie Mengyi, Zheng Ang, Zhang Lanying, He Ai, Zhang Ruifen, Liu Weilin, Ding Kan, Wu Lianzhong, Meng Yongsheng, Li Qi, Yangjin Baima, Li Ting, Liu Chao, Gao Da, He Heng, Long Fei, Ge Xiaoyan, Sun Xiao-Xiao, Ma Haizhao, Su Tiansheng, Du Shuhao, Chen Mengyun, Feng Yahui, Song Zhen, Wang Jinyu, Gale Robert Peter, Gong Xiaowen, Shen Qiujin, Chen Junren
Аннотация
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.