Is health technology assessment ready for generative pretrained transformer large language models? Report of a fishbowl inquiry.
| Autor: | Goodman C; Independent Consultant, Health Care Technology & Policy, Bethesda, MD, USA., Treloar E; Discipline of Surgery, University of Adelaide, AdelaideSA, Australia. |
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| Jazyk: | angličtina |
| Zdroj: | International journal of technology assessment in health care [Int J Technol Assess Health Care] 2024 Nov 05; Vol. 40 (1), pp. e48. Date of Electronic Publication: 2024 Nov 05. |
| DOI: | 10.1017/S0266462324000382 |
| Abstrakt: | Objectives: 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. Methods: 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? Results: 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. Conclusions: 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. |
| Databáze: | MEDLINE |
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