Wang Zhiyuan, Yan Runze, Francis Sherilyn, Diaz Carmen, Flickinger Tabor, Lin Yufen, Hu Xiao, Barnes Laura E, LeBaron Virginia
School of Engineering and Applied Science, University of Virginia, Charlottesville, VA USA.
Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA USA.
Npj Health Syst. 2025;2(1):22. doi: 10.1038/s44401-025-00024-5. Epub 2025 Jun 18.
Large language models (LLMs) are transforming healthcare by advancing clinical decision support, patient care, and administrative efficiency. However, effectively and sustainably integrating LLMs into healthcare systems requires addressing participatory gaps that may hinder alignment with stakeholders' practical and ethical needs. This paper explores how participatory methods can be applied throughout the development lifecycle of LLM-enhanced health systems (LLMHS), arguing that: (1) participatory approaches are critical for engaging stakeholders in LLMHS development, and (2) LLM techniques can create novel participatory opportunities that reinforce stakeholder engagement while driving technical innovation in LLMHS. This dual perspective highlights the potential of LLMHS to align technical sophistication with real-world healthcare demands, paving the way for next-generation health systems.
大型语言模型（LLMs）正在通过推进临床决策支持、患者护理和管理效率来改变医疗保健行业。然而，要有效地、可持续地将大型语言模型整合到医疗系统中，就需要解决可能阻碍与利益相关者的实际和道德需求保持一致的参与差距。本文探讨了如何在大型语言模型增强型医疗系统（LLMHS）的开发生命周期中应用参与式方法，并认为：（1）参与式方法对于让利益相关者参与LLMHS开发至关重要；（2）大型语言模型技术可以创造新的参与机会，在推动LLMHS技术创新的同时加强利益相关者的参与。这种双重观点凸显了LLMHS将技术复杂性与现实世界医疗需求相结合的潜力，为下一代医疗系统铺平了道路。
