Language, power, and access: large language models and equity in medicine.

Abstract

Large language models (LLMs) are increasingly being integrated into anaesthesia, perioperative medicine, and critical care, creating new opportunities to improve communication, decision support, and access to healthcare knowledge. Realising these opportunities equitably depends not only on model capability but also on how LLMs are developed, implemented, used, and governed within healthcare systems. This editorial introduces the Bias Pyramid, a conceptual framework that explains how inequity can emerge across global knowledge ecosystems, institutional information environments, and individual clinical workflows, and identifies opportunities for equitable implementation. By incorporating reinforcing feedback, the framework conceptualises equity as an evolving property of learning healthcare systems that can either amplify existing inequities or progressively improve equity over successive learning cycles. The Bias Pyramid provides a practical implementation framework to guide governance, education, and coordinated action before LLMs become embedded in routine perioperative and critical care practice.