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全科医生希望大语言模型如何应用于基层医疗,他们的担忧是什么?一项横断面调查。

How do GPs Want Large Language Models to be Applied in Primary Care, and What Are Their Concerns? A Cross-Sectional Survey.

作者信息

Armitage Richard C

机构信息

Academic Unit of Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham, UK.

出版信息

J Eval Clin Pract. 2025 Jun;31(4):e70129. doi: 10.1111/jep.70129.


DOI:10.1111/jep.70129
PMID:40369934
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12079004/
Abstract

INTRODUCTION: Although the potential utility of large language models (LLMs) in medicine and healthcare is substantial, no assessment has been made to date of how GPs want LLMs to be applied in primary care, or of which issues GPs are most concerned about regarding the implementation of LLMs into their clinical practice. This study's objective was to generate preliminary evidence that answers these questions, which are relevant because GPs themselves will ultimately harness the power of LLMs in primary care. METHODS: Non-probability sampling was utilised: GPs practicing in the UK and who were members of one of two Facebook groups (one containing a community of UK primary care staff, the other containing a community of GMC-registered doctors in the UK) were invited to complete an online survey, which ran from 06 to 13 November 2024. RESULTS: The survey received 113 responses, 107 of which were from GPs practicing in the UK. When LLM accuracy and safety were assumed to be guaranteed, broad enthusiasm for LLMs carrying out various nonclinical and clinical tasks in primary care was reported. The single nonclinical task and clinical task that respondents were most supportive of were the LLM listening to the consultation and writing notes in real-time for the GP to review, edit, and save (44.0%), and the LLM identifying outstanding clinical tasks and actioning them (51.0%), respectively. Respondents were concerned with a range of issues regarding LLMs being embedded into clinical systems, with patient safety being the most commonly reported single issue of concern (36.2%). DISCUSSION: This study has generated preliminary evidence that is of potential utility to those developing LLMs for use in primary care. Further research is required to expand this evidence base to further inform the development of these technologies, and to ensure they are acceptable to the GPs who will use them.

摘要

引言:尽管大语言模型(LLMs)在医学和医疗保健领域具有巨大的潜在效用,但迄今为止,尚未对全科医生(GPs)希望大语言模型在初级保健中如何应用,或全科医生在将大语言模型应用于临床实践时最关心哪些问题进行评估。本研究的目的是生成初步证据来回答这些问题,这些问题具有相关性,因为全科医生自身最终将在初级保健中利用大语言模型的力量。 方法:采用非概率抽样:邀请在英国执业且是两个脸书群组之一的成员的全科医生(其中一个群组包含英国初级保健人员社区,另一个群组包含英国医学委员会注册医生社区)完成一项在线调查,该调查于2024年11月6日至13日进行。 结果:该调查共收到113份回复,其中107份来自在英国执业的全科医生。当假定大语言模型的准确性和安全性得到保证时,报告显示全科医生对大语言模型在初级保健中执行各种非临床和临床任务表现出广泛的热情。受访者最支持的单一非临床任务和临床任务分别是大语言模型实时听取会诊并为全科医生撰写笔记以供审查、编辑和保存(44.0%),以及大语言模型识别未完成的临床任务并采取行动(51.0%)。受访者对将大语言模型嵌入临床系统存在一系列担忧,患者安全是最常报告的单一担忧问题(36.2%)。 讨论:本研究生成了初步证据,对那些开发用于初级保健的大语言模型的人具有潜在效用。需要进一步研究以扩大这一证据基础,为这些技术的进一步发展提供更多信息,并确保它们为将使用它们的全科医生所接受。

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本文引用的文献

[1]
Implications of Large Language Models for Clinical Practice: Ethical Analysis Through the Principlism Framework.

J Eval Clin Pract. 2025-2

[2]
Using fine-tuned large language models to parse clinical notes in musculoskeletal pain disorders.

Lancet Digit Health. 2023-10-26

[3]
Generative artificial intelligence in primary care: an online survey of UK general practitioners.

BMJ Health Care Inform. 2024-9-17

[4]
The potential for large language models to transform cardiovascular medicine.

Lancet Digit Health. 2024-10

[5]
Ethical and regulatory challenges of large language models in medicine.

Lancet Digit Health. 2024-6

[6]
Performance of GPT-4 in Membership of the Royal College of Paediatrics and Child Health-style examination questions.

BMJ Paediatr Open. 2024-3-20

[7]
Performance of generative pre-trained Transformer-4 (GPT-4) in RCOG diploma-style questions.

Postgrad Med J. 2024-8-16

[8]
The performance of large language models in intercollegiate Membership of the Royal College of Surgeons examination.

Ann R Coll Surg Engl. 2024-11

[9]
Potential applications and implications of large language models in primary care.

Fam Med Community Health. 2024-1-30

[10]
Performance of Generative Pre-trained Transformer-4 (GPT-4) in Membership of the Royal College of General Practitioners (MRCGP)-style examination questions.

Postgrad Med J. 2024-3-18

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