A large language model digital patient system enhances ophthalmology history taking skills
Clinical trainees face limited opportunities to practice medical history-taking skills due to scarce case diversity and access to real patients. To address this, we developed a large language model-based digital patient (LLMDP) system that transforms de‑identified electronic health records into voice‑enabled virtual patients capable of free‑text dialog and adaptive feedback, based on our previously established open-source retrieval-augmented framework. In a single‑center randomized controlled trial (ClinicalTrials.gov: NCT06229379; N = 84), students trained with LLMDP achieved a 10.50-point increase in medical history-taking assessment scores (95% CI: 4.66-16.33, p < 0.001) compared to those using traditional methods. LLMDP-trained students also demonstrated greater empathy. Participants reported high satisfaction with LLMDP, emphasizing its role in reducing training costs and boosting confidence for real patient interactions. These findings provide evidence that LLM-driven digital patients enhance medical history-taking skills and offer a scalable, low-risk pathway for integrating generative AI into ophthalmology education.
Authors
- Ching‐Kit Tsui (ORCID: https://orcid.org/0000-0002-5636-962X)
- Yunxi Lai (ORCID: https://orcid.org/0000-0002-5709-2351)
- Duoru Lin (ORCID: https://orcid.org/0000-0002-7214-1801)
- Wenben Chen
- Yahan Yang (ORCID: https://orcid.org/0009-0008-6098-3244)
- Jingjing Chen (ORCID: https://orcid.org/0000-0001-7535-8494)
- Xiaohang Wu (ORCID: https://orcid.org/0000-0002-9398-4330)
- Jianyu Pang (ORCID: https://orcid.org/0009-0007-2483-6717)
- Lanqin Zhao (ORCID: https://orcid.org/0000-0002-5182-3678)
- Shaowei Bi (ORCID: https://orcid.org/0009-0002-9372-6021)
- Zhenzhen Liu (ORCID: https://orcid.org/0000-0002-4853-2474)
- Kang Xu (ORCID: https://orcid.org/0000-0002-6946-8635)
- Yiqing Li (ORCID: https://orcid.org/0000-0001-7021-0992)
- Yangfan Yang (ORCID: https://orcid.org/0000-0001-9021-9652)
- Lixue Liu (ORCID: https://orcid.org/0009-0004-5973-1067)
- Rongxin Chen (ORCID: https://orcid.org/0000-0003-4867-8331)
- Mingjie Luo (ORCID: https://orcid.org/0000-0001-7482-4975)
- Yuxian Zou
- Haotian Lin
- Ling Jin
Institutions
- Sun Yat-sen University (CN)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2025-08-04
- DOI
- https://doi.org/10.1038/s41746-025-01841-6
- Citations
- 13
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 8.51
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province