Ethical Governance of Large Language Models in Health Care: Trust, Responsibility, and Equity in Routine Use.

Unlabelled: Large language models (LLMs) are becoming increasingly embedded in routine health care communication, raising ethical challenges that extend beyond model performance alone. This Viewpoint argues that ethical risks in LLM-enabled health care emerge through patterns of reliance, institutional embedding, and governance during real-world use. Using "adoption-phase ethics" as an analytic lens, this paper examines 3 interrelated dimensions of ethical risk. First, trust in LLM-enabled health care is shaped not only by technical accuracy, but also by institutional and relational conditions surrounding its use. Second, responsibility may become distributed and ambiguous when LLM-mediated information influences clinical communication and decision-making. Third, equity concerns arise from unequal capacities to interpret, contest, and benefit from LLM-generated information. We argue that ethical governance of LLMs in health care requires continuous, system-level oversight that extends beyond model evaluation alone, including clear accountability structures, role-sensitive implementation, and equity-oriented governance practices. By reframing ethical analysis around routine integration rather than technical performance alone, this Viewpoint aims to support more responsible and sustainable use of LLMs in health care.