Retrieval-Augmented Generation (RAG) improves the reliability of AI in healthcare by grounding responses in verified external knowledge, addressing hallucinations typical in Large Language Models (LLMs). Anticipated growth in RAG adoption highlights its critical role in enhancing clinical decision-making and patient safety while navigating challenges such as algorithmic bias and HIPAA compliance.