GraphRAG, a graph-powered AI framework, addresses the challenges of fragmented healthcare data by transforming disparate information into a cohesive dynamic knowledge graph, enabling real-time analytics and insightful discovery. By using graph databases to model relationships between data from various healthcare systems, GraphRAG facilitates integration, standardizes terminology, and connects data silos, overcoming interoperability challenges and enhancing data-driven decision-making. Memgraph's advanced algorithms, such as Community Detection and Graph Traversals, allow healthcare teams to explore complex relationships, uncover hidden insights, and improve patient treatment, research efficiency, and operational costs. The approach surpasses traditional data models by maintaining context and structure, supporting proactive insight discovery across patient care and research, and promising to revolutionize healthcare information management by turning data silos into valuable, interconnected knowledge networks.