Coleman Hilton is a healthcare data strategy and medical informatics leader with more than a decade of experience modernizing data ecosystems and driving AI-enabled transformation across complex clinical and operational environments. He is recognized for advancing next-generation analytics, enterprise data architecture, and responsible AI in healthcare, and is a frequent voice in national thought-leadership communities.

Coleman serves as a key architect of Shriners Children’s enterprise data and AI strategy, where he leads the development of a unified, AI-ready data architecture spanning FHIR-based ingestion, medallion-structured data engineering, enterprise semantic modeling, and advanced analytics activation. His work has accelerated systemwide initiatives including whole-genome data integration, motion-analysis informatics, enterprise dashboards, patient access analytics, and a modernized pipeline for clinical and operational data.

He led the design and execution of Shriners Children’s recent work attribution engine, an OpenAI-powered system that reliably interprets clinical documentation and generates high-fidelity metadata for downstream reporting and workforce analytics. This initiative has become a template for safely and responsibly integrating generative AI into enterprise data pipelines.

Coleman is also championing the creation of a healthcare Data Science Institute at Shriners Children’s, a multidisciplinary hub focused on AI readiness, data literacy, ethics, resident and student training, exploratory research, and industry-academic partnership. His vision centers on scaling advanced analytics to support novel care models for children with complex medical needs and ultimately expanding that impact across the healthcare sector.

Professional Accomplishments

• Enterprise Data Strategy Leadership: Architect of an enterprise-wide data ecosystem supporting clinical, operational, financial, and research domains. Guided the shift from legacy ETL to a standards-based FHIR/OMOP model and modern data lakehouse architecture aligned with organizational governance.
• Advanced AI & Analytics Engineering: Leader in applying generative AI, machine learning, and Large Concept Models to solve real-world healthcare challenges. Delivered production-grade AI augmentation pipelines that improve data quality, documentation understanding, and analytic accuracy.
• Platform Modernization & Operational Impact: Directed initiatives that increased analytic scalability, reduced reporting friction, and enabled role-based access to insights across the enterprise. Known for transforming data processes into high-value operational and clinical decision tools.
• Collaboration Across Disciplines: Experienced in uniting technical teams, clinicians, researchers, and administrators around shared data goals, ensuring systems are usable, trustworthy, and aligned with frontline needs.
• Thought Leadership & Community Engagement: Active contributor to national healthcare analytics and AI communities. Presenter for Microsoft’s Health & Life Sciences Data Platform engineering team and contributor to professional forums on AI readiness, data governance, and enterprise analytics design.