Jackson Brian R, Sendak Mark P, Solomonides Anthony, Balu Suresh, Sittig Dean F
Department of Pathology, University of Utah, Salt Lake City, UT 84112, United States.
Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States.
J Am Med Inform Assoc. 2025 Feb 1;32(2):404-407. doi: 10.1093/jamia/ocae296.
To assess the potential to adapt an existing technology regulatory model, namely the Clinical Laboratory Improvement Amendments (CLIA), for clinical artificial intelligence (AI).
We identify overlap in the quality management requirements for laboratory testing and clinical AI.
We propose modifications to the CLIA model that could make it suitable for oversight of clinical AI.
In national discussions of clinical AI, there has been surprisingly little consideration of this longstanding model for local technology oversight. While CLIA was specifically designed for laboratory testing, most of its principles are applicable to other technologies in patient care.
A CLIA-like approach to regulating clinical AI would be complementary to the more centralized schemes currently under consideration, and it would ensure institutional and professional accountability for the longitudinal quality management of clinical AI.
评估调整现有技术监管模式（即临床实验室改进修正案（CLIA））以用于临床人工智能（AI）的潜力。
我们确定了实验室检测和临床AI质量管理要求中的重叠部分。
我们提议对CLIA模型进行修改，使其适用于临床AI的监管。
在关于临床AI的全国性讨论中，令人惊讶的是，对于这种长期存在的本地技术监管模式几乎没有考虑。虽然CLIA是专门为实验室检测设计的，但其大多数原则适用于患者护理中的其他技术。
采用类似CLIA的方法来监管临床AI将补充目前正在考虑的更为集中的方案，并将确保临床AI纵向质量管理的机构和专业责任。
