Use, knowledge and perception of large language models in clinical practice: a cross-sectional mixed-methods survey among clinicians in Switzerland.

Abstract

Objectives: Large language model (LLM)-based tools offer potential for clinical practice but raise concerns regarding output accuracy, patient safety and data security. We aimed to assess Swiss clinicians' use, knowledge and perception of LLMs and identify associated factors.

Methods: An anonymous online survey was distributed via 34 medical societies in Switzerland. The primary outcome was frequent use of LLMs (at least weekly use). The secondary outcome was higher knowledge regarding LLMs (score above the median in an 11-item test). Qualitative analysis explored clinicians' perceptions of LLM-related opportunities and risks.

Results: Among 685 participants (response rate 29.0%), 225 (32.8%) reported frequent use of LLMs, 25 (3.6%) reported having used a specific medical LLM and 42 (6%) reported the availability of workplace LLM guidelines. The median knowledge test score was 6 points (IQR 4-8 points). Multivariable analysis showed that younger age, male sex and research activity were significantly associated with frequent use and higher knowledge. Qualitative analysis identified administrative support, analytical assistance and access to information as key opportunities. The main risks identified were declining clinical skills, poor output quality and legal or ethical concerns.

Discussion: The study highlights a notable adoption of LLMs among Swiss clinicians, particularly among younger, male and research-active individuals. However, the limited availability of workplace guidelines raises concerns about safe and effective use.

Conclusion: The gap between widespread LLM use and the scarcity of workplace guidelines underscores the need for accessible educational resources and clinical guidelines to mitigate potential risks and promote informed use.