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.
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