在医院调研LLM临床应用需求，识别落地难题
Participatory Assessment of Large Language Model Applications in an Academic Medical Center
- 联合30位医护、患者代表共同识别潜在应用场景
- 评估了11个科室的使用可行性及合规风险
- 为医疗AI部署提供可落地的参与式框架
尽管大语言模型在医疗应用中展现出良好潜力，但其在医疗领域的部署面临伦理、监管和技术等独特挑战。本研究采用系统性参与式方法，调查瑞士洛桑大学医院这一学术医疗中心对大语言模型临床应用的需求与期望。通过与来自11个科室的临床人员、护理人员及患者代表共30位利益相关者协作，识别出潜在的LLM应用场景，并综合考虑监管框架、数据保护法规、偏见、幻觉及部署限制等因素，评估这些场景的当前可行性。研究提出了一种参与式方法框架，用于识别机构在引入先进医疗技术时的需求，并对大语言模型在医疗应用中的技术成熟度进行了现实分析，指出了实现伦理合规和监管合规前需克服的关键问题。
原文摘要 · Abstract (English)
Although Large Language Models (LLMs) have shown promising performance in healthcare-related applications, their deployment in the medical domain poses unique challenges of ethical, regulatory, and technical nature. In this study, we employ a systematic participatory approach to investigate the needs and expectations regarding clinical applications of LLMs at Lausanne University Hospital, an academic medical center in Switzerland. Having identified potential LLM use-cases in collaboration with thirty stakeholders, including clinical staff across 11 departments as well nursing and patient representatives, we assess the current feasibility of these use-cases taking into account the regulatory frameworks, data protection regulation, bias, hallucinations, and deployment constraints. This study provides a framework for a participatory approach to identifying institutional needs with respect to introducing advanced technologies into healthcare practice, and a realistic analysis of the technology readiness level of LLMs for medical applications, highlighting the issues that would need to be overcome LLMs in healthcare to be ethical, and regulatory compliant.
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