Independent Consultant, Health Care Technology & Policy, Bethesda, MD, USA.
Discipline of Surgery, University of Adelaide, AdelaideSA, Australia.
Int J Technol Assess Health Care. 2024 Nov 5;40(1):e48. doi: 10.1017/S0266462324000382.
The Health Technology Assessment International (HTAi) 2023 Annual Meeting included a novel "fishbowl" session intended to 1) probe the role of HTA in the emergence of generative pretrained transformer (GPT) large language models (LLMs) into health care and 2) demonstrate the semistructured, interactive fishbowl process applied to an emerging "hot topic" by diverse international participants.
The fishbowl process is a format for conducting medium-to-large group discussions. Participants are separated into an inner group and an outer group on the periphery. The inner group responds to a set of questions, whereas the outer group listens actively. During the session, participants voluntarily enter and leave the inner group. The questions for this fishbowl were: What are current and potential future applications of GPT LLMs in health care? How can HTA assess intended and unintended impacts of GPT LLM applications in health care? How might GPT be used to improve HTA methodology?
Participants offered approximately sixty responses across the three questions. Among the prominent themes were: improving operational efficiency, terminology and language, training and education, evidence synthesis, detecting and minimizing biases, stakeholder engagement, and recognizing and accounting for ethical, legal, and social implications.
The interactive fishbowl format enabled the sharing of real-time input on how GPT LLMs and related disruptive technologies will influence what technologies will be assessed, how they will be assessed, and how they might be used to improve HTA. It offers novel perspectives from the HTA community and aligns with certain aspects of ongoing HTA and evidence framework development.
卫生技术评估国际（HTAi）2023 年年会包含了一个新颖的“鱼缸”环节，旨在：1）探究 HTA 在生成式预训练转换器（GPT）大型语言模型（LLM）进入医疗保健领域中的作用，以及 2）展示通过多样化的国际参与者应用于新兴“热点话题”的半结构化、互动式鱼缸流程。
鱼缸流程是一种进行中型到大型群体讨论的格式。参与者被分为内圈和外圈两个小组。内圈回答一组问题，而外圈则积极倾听。在会议期间，参与者可以自愿加入或离开内圈。本次鱼缸讨论的问题是：GPT LLM 在医疗保健中的当前和潜在未来应用有哪些？HTA 如何评估 GPT LLM 应用在医疗保健中的预期和非预期影响？GPT 如何用于改进 HTA 方法？
参与者针对这三个问题提供了大约六十个回复。其中突出的主题包括：提高运营效率、术语和语言、培训和教育、证据综合、检测和最小化偏差、利益相关者参与，以及认识和考虑道德、法律和社会影响。
互动鱼缸式的形式使人们能够实时分享关于 GPT LLM 和相关颠覆性技术将如何影响需要评估的技术、如何评估它们以及如何利用它们来改进 HTA 的信息。它提供了 HTA 社区的新颖视角，并与正在进行的 HTA 和证据框架开发的某些方面相吻合。
