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PRIMARY-AI: outcomes-based standards to safeguard primary care in the AI era - Nature Medicine

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By Dian Zeng, Lorainne Tudor Car, Kamlesh Khunti, Yuanli Liu, Till Bärnighausen, Niels H. Chavannes, Pearse A. Keane, Holger Kunz, Lan Xue, Yih Chung Tham, Lorenzo Righetto Verified, Donald J. Boudreau, Qionghai Dai, Weiping Jia, Yang Liu Verified, Dinggang Shen, Jia Liu, Weixing Shen, John S. Ji, Zhong Lin Wang, Zhiyi Wang, Haibo Wang, Shenglan Tang, Chenyang Pei, Zehua Jiang, Zihao Zou, Yiming Qin, Huating Li, Yasha Wang, Dinesh Visva Gunasekeran, Sabrina Wong, Dong Xu, Ryan J. Urbanowicz, Liliana Laranjo, Ana Neves, Nan Liu, Neil M. Bressler, Rifat Atun, David C. Klonoff, Nigam H. Shah, Josip Car, Rupa Sarker, Phuoc Van Le
| Nature Verified
Artificial intelligence (AI) is being deployed at scale in primary care — from diagnostic support and risk stratification to triage and clinical documentation — without any agreed-upon outcomes-based framework for determining whether it strengthens or undermines continuity, coordination, comprehensiveness and people-centered care1. This is dangerous for the billions of people whose first contact with health systems is primary care.
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