Healthcare organizations often struggle to see the entire system due to disconnected data, leading to high costs and inefficiencies in making quality predictions for individual care improvements. Graph databases, which are underutilized in healthcare, offer a promising solution by effectively connecting diverse and variable healthcare data, which traditional relational databases struggle to manage. Optum, part of UnitedHealth Group, is working to integrate disparate datasets from acquisitions into a comprehensive healthcare knowledge graph, aiming to improve predictive models and patient outcomes. The organization highlights the challenges of data variability, privacy, and integration across silos while emphasizing the importance of explainable AI and model-based machine learning in healthcare. Graph technologies, combined with other approaches like natural language processing and machine learning, are seen as critical to addressing complex healthcare problems and fostering cross-domain solutions that enhance data connectivity and access. Through metaphors like the neighborhood walk, open world assumption, and knowledge triangle, Optum seeks to communicate the advantages of graph databases to healthcare executives, who play a crucial role in deciding the systems to build.