JMIR Publications

ABSTRACT

Background:

Language barriers between health-care providers and patients can compromise communication quality, patient safety, and health-care equity. When professional interpreter services are limited, particularly in outpatient settings, artificial intelligence–based translation tools may serve as supplementary communication aids.

Objective:

This study compared 3 Chinese-Japanese translation tools, ChatGPT, Google Translate, and UD Talk, in terms of their performance in real-world cardiology and pulmonology outpatient consultations.

Methods:

In this single-center prospective observational study, audio-recorded outpatient consultations between December 2024 and November 2025 were analyzed. Verbatim physician-patient dialogues were translated using the 3 systems. Selected dialogue exchanges were evaluated by professional medical interpreters for translation accuracy and by Japanese-speaking lay participants for translation satisfaction by using a 6-point Likert scale. Similarity of translation outputs was assessed at the dialogue-exchange level.

Results:

In Chinese-Japanese outpatient medical consultations, large language model–based translation tools, particularly ChatGPT, demonstrated higher translation accuracy and user satisfaction than did conventional translation systems. These findings indicate that such tools may support multilingual clinical communication when used as complementary aids alongside professional interpreter services.

Conclusions:

Large language model–based translation demonstrated superior performance and usability compared with conventional translation tools in Chinese–Japanese medical consultations, suggesting its potential role in supporting multilingual clinical communication and interpreter training. Clinical Trial: NCT06934031