Role-Prompting in Frontier Large Language Models Influences Clinical Reasoning in Complex Medical Cases

Background: Large language models (LLMs) are increasingly deployed in healthcare, where they may adopt different stakeholder perspectives, yet the effect of role-prompting on clinical ethical reasoning remains poorly characterized. Methods: We evaluated three frontier LLMs: Claude Opus 4.6, GPT-5.4, and Gemini 3.1 Pro across 25 ethically complex medical cases. Each model responded from three stakeholder perspectives (physician, patient, insurer) across three independent runs (675 total responses). Decisions were benchmarked against a six-physician panel. Ethical value prioritization was analyzed from physician- and LLM-provided ranked values. A Patient-Centric Decision Index (PCDI) was devel