Saenz Agustina D, Harned Zach, Banerjee Oishi, Abràmoff Michael D, Rajpurkar Pranav
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
NPJ Digit Med. 2023 Oct 6;6(1):185. doi: 10.1038/s41746-023-00929-1.
Autonomous AI systems in medicine promise improved outcomes but raise concerns about liability, regulation, and costs. With the advent of large-language models, which can understand and generate medical text, the urgency for addressing these concerns increases as they create opportunities for more sophisticated autonomous AI systems. This perspective explores the liability implications for physicians, hospitals, and creators of AI technology, as well as the evolving regulatory landscape and payment models. Physicians may be favored in malpractice cases if they follow rigorously validated AI recommendations. However, AI developers may face liability for failing to adhere to industry-standard best practices during development and implementation. The evolving regulatory landscape, led by the FDA, seeks to ensure transparency, evaluation, and real-world monitoring of AI systems, while payment models such as MPFS, NTAP, and commercial payers adapt to accommodate them. The widespread adoption of autonomous AI systems can potentially streamline workflows and allow doctors to concentrate on the human aspects of healthcare.
医学中的自主人工智能系统有望改善治疗效果，但引发了对责任、监管和成本的担忧。随着能够理解和生成医学文本的大语言模型的出现，解决这些担忧的紧迫性增加，因为它们为更复杂的自主人工智能系统创造了机会。本文探讨了对医生、医院和人工智能技术创造者的责任影响，以及不断演变的监管环境和支付模式。如果医生严格遵循经过充分验证的人工智能建议，在医疗事故案件中可能会受到青睐。然而，人工智能开发者可能因在开发和实施过程中未遵守行业标准的最佳实践而面临责任。由美国食品药品监督管理局（FDA）引领的不断演变的监管环境，旨在确保人工智能系统的透明度、评估和实际监测，而诸如医疗保险医师费率表（MPFS）、基于价值的支付调整计划（NTAP）和商业付款方等支付模式也在进行调整以适应它们。自主人工智能系统的广泛应用有可能简化工作流程，并使医生能够专注于医疗保健的人文方面。
