Large Language Model–Based Simulated Patient Training for Heart Failure Palliative Care Communication: A Pilot Study
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ID: 321883
2026
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Abstract
Abstract Aims Heart failure palliative care communication is essential but difficult to train at scale because conventional role-play programs require facilitators and standardized patients. Large language models have emerged as potential tools for scalable communication training. This pilot study aimed to evaluate the feasibility of a web-based large language model-driven communication training application and to explore its early educational signal on physicians’ self-efficacy. Methods and results This single-arm pilot study included physicians who completed one session using a Japanese-language web-based large language model application designed to simulate patients with advanced heart failure and provide automated framework-based feedback. The primary outcome was change in self-efficacy scores assessed by pre- and post-session questionnaires. Ten sessions were analyzed. Physicians engaged in a mean of 7.6 ± 2.0 dialogue turns. Mean response time per model output and feedback generation were approximately 3 and 17 seconds, respectively. Significant improvements were observed in knowledge of palliative care communication (mean difference +1.7, adjusted P < 0.01) and confidence in heart failure palliative care communication (+1.2, adjusted P = 0.03). Other domains showed non-significant changes. Conclusion This pilot study demonstrated the feasibility of a web-based large language model simulated patient system and suggested an early educational signal in physicians’ self-efficacy for heart failure palliative care communication. Our scalable large language model-driven communication training may complement traditional educational approaches with further evaluation in larger controlled studies.
| Reference Key |
openalex_W7170057955
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| Authors | Risa Kishikawa, H Morita, Satoshi Kodera |
| Journal | European Heart Journal - Digital Health |
| Year | 2026 |
| DOI |
10.1093/ehjdh/ztag119
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| URL | |
| Keywords | Keywords not found |
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