[Focus: artificial intelligence in medicine-Legal aspects of using large language models in clinical practice].

Innere Medizin (Heidelberg, Germany) Pub Date : 2025-04-01 Epub Date: 2025-03-14 DOI:10.1007/s00108-025-01861-0
Eva Weicken, Mirja Mittermaier, Thomas Hoeren, Juliana Kliesch, Thomas Wiegand, Martin Witzenrath, Miriam Ballhausen, Christian Karagiannidis, Leif Erik Sander, Matthias I Gröschel
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引用次数: 0

Abstract

Background: The use of artificial intelligence (AI) and natural language processing (NLP) methods in medicine, particularly large language models (LLMs), offers opportunities to advance the healthcare system and patient care in Germany. LLMs have recently gained importance, but their practical application in hospitals and practices has so far been limited. Research and implementation are hampered by a complex legal situation. It is essential to research LLMs in clinical studies in Germany and to develop guidelines for users.

Objective: How can foundations for the data protection-compliant use of LLMs, particularly cloud-based LLMs, be established in the German healthcare system? The aim of this work is to present the data protection aspects of using cloud-based LLMs in clinical research and patient care in Germany and the European Union (EU); to this end, key statements of a legal opinion on this matter are considered. Insofar as the requirements for use are regulated by state laws (vs. federal laws), the legal situation in Berlin is used as a basis.

Materials and methods: As part of a research project, a legal opinion was commissioned to clarify the data protection aspects of the use of LLMs with cloud-based solutions at the Charité - University Hospital Berlin, Germany. Specific questions regarding the processing of personal data were examined.

Results: The legal framework varies depending on the type of data processing and the relevant federal state (Bundesland). For anonymous data, data protection requirements need not apply. Where personal data is processed, it should be pseudonymized if possible. In the research context, patient consent is usually required to process their personal data, and data processing agreements must be concluded with the providers. Recommendations originating from LLMs must always be reviewed by medical doctors.

Conclusions: The use of cloud-based LLMs is possible as long as data protection requirements are observed. The legal framework is complex and requires transparency from providers. Future developments could increase the potential of AI and particularly LLMs in everyday clinical practice; however, clear legal and ethical guidelines are necessary.

[聚焦:医学人工智能--在临床实践中使用大型语言模型的法律问题]。
背景:在医学中使用人工智能(AI)和自然语言处理(NLP)方法,特别是大型语言模型(llm),为推进德国的医疗保健系统和患者护理提供了机会。法学硕士最近变得越来越重要,但到目前为止,他们在医院和实践中的实际应用还很有限。复杂的法律情况阻碍了研究和实施。研究法学硕士在德国的临床研究,并为用户制定指南是至关重要的。目的:如何在德国医疗保健系统中建立符合数据保护的llm使用基础,特别是基于云的llm ?这项工作的目的是介绍在德国和欧盟(EU)的临床研究和患者护理中使用基于云的法学硕士的数据保护方面;为此目的,审议了关于这个问题的法律意见的主要陈述。只要使用要求是由州法律(相对于联邦法律)规定的,就以柏林的法律情况为基础。材料和方法:作为一个研究项目的一部分,在德国柏林慈善大学医院委托了一份法律意见,以澄清将法学硕士与基于云的解决方案结合使用的数据保护方面的问题。研究了有关处理个人资料的具体问题。结果:法律框架因数据处理类型和相关联邦州(Bundesland)而异。对于匿名数据,不需要适用数据保护要求。在处理个人资料时,应尽可能使用假名。在研究环境中,通常需要患者同意才能处理他们的个人数据,并且必须与提供者签订数据处理协议。法学硕士提出的建议必须始终由医生审查。结论:只要遵守数据保护要求,使用基于云的llm是可能的。法律框架很复杂,要求供应商提供透明度。未来的发展可能会增加人工智能,特别是法学硕士在日常临床实践中的潜力;然而,明确的法律和道德准则是必要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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