From Innovation to Impact: Rewiring Global and Regional Health Delivery at Scale
Arturo LoAIza-Bonilla, Network Chief of Hematology and Oncology at St. Luke’s University Health Network, joins host Fern Lazar, Managing Partner and Global Health Practice Leader at FINN Partners, for a Global Health and Purpose Summit conversation on what it takes to move healthcare innovation from promising pilots to measurable impact.
The session examines how artificial intelligence, clinical workflows, implementation infrastructure, interoperability, governance, sustainability, and patient access must come together to transform health delivery at regional and global scale. LoAIza-Bonilla argues that AI cannot simply be added onto broken workflows. It must be embedded into clinical pathways, supported by appropriate governance, measured through patient-centered outcomes, and designed to help people live longer and better.
Drawing from his work as a practicing oncologist, health system leader, and co-founder of MassiveBio, LoAIza-Bonilla explores how AI can help match patients to clinical trials, identify biomarker and treatment opportunities, support decentralized access, and connect real-world data to better care decisions. The session also addresses the need for shared digital rails, public-private collaboration, patient-centered information exchange, and sustainability-minded implementation.
Session Intelligence
This session positions implementation as the defining challenge of the next era of healthcare innovation. AI, data, digital platforms, clinical trials, and precision medicine will create value only when they are integrated into workflows, governed responsibly, connected across systems, and translated into access for patients.
Implementation at Scale
Health systems must move from pilots to auditable infrastructure that improves real patient outcomes.
Oncology Access
AI-enabled matching, navigation, testing, and decentralized pathways can help expand clinical trial and treatment access.
Interoperable Systems
Shared digital rails, governance, and information exchange are essential to scalable and equitable care delivery.
Human-Centered AI
Technology should extend clinical capacity while preserving empathy, judgment, and shared decision-making.
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