Healthcare That Learns: Value-Based Care and the AI-Enabled Learning Health System

Health care overflows with data and AI, but better information alone doesn’t guarantee better care. Healthcare That Learns reveals the challenge is converting practice into data, data into knowledge, and knowledge into action—making learning, equity, and improvement routine across systems. Healthcare That Learns: Value-Based Care, Artificial Intelligence, and the Learning Health System provides a timely and pragmatic exploration of how healthcare organizations can transform into continuously learning systems – a shift rapidly becoming imperative as value-based care accelerates and artificial intelligence reshapes practice. The book provides a unified roadmap for transforming healthcare systems into continuously learning organizations capable of delivering true value-based care. Healthcare today faces converging pressures: unsustainable costs, uneven outcomes, payer demands for value, and disruptive advances in AI. At the same time, the 17-year “know-do gap” between evidence and practice undermines progress. Healthcare That Learns offers a blueprint for bridging this gap by uniting three critical forces – value-based care, artificial intelligence, and the learning health system framework. Unlike works that treat AI or quality improvement in isolation, this book integrates them into a single, practical framework. Readers will gain actionable strategies to close evidence-practice gaps, improve outcomes, and reduce waste. Key themes include micro-to-macro learning cycles, knowledge transfer, sociotechnical alignment, AI governance, and equity by design. Each chapter begins with a real-world vignette and translates concepts into practical tools. Topics span the urgency of value-based care, foundations of learning health systems, enabling technologies (data, AI, generative AI), leadership and cultural change, ethics and equity, and case-based roadmaps for implementation.