AI, Learning Health Systems, and Libraries

The integration of artificial intelligence (AI) into Learning Health Systems (LHS) presents significant opportunities for improving healthcare by translating research findings into patient care, embedding clinical research into practice, and enabling continuous quality improvement. However, implementing LHS is complex, requiring collaboration across a diverse set of stakeholders, including healthcare leaders, clinicians, researchers, patients, and librarians. This presentation explores the evolving role of libraries in supporting AI-driven LHS, with a focus on the iTHRIV model. It highlights the critical contributions of libraries in data harmonization, informatics, health equity, and AI ethics, showcasing innovative initiatives such as AI-driven research support, coding applications, and critical appraisal. By leveraging their expertise in information management and emerging technologies, libraries are positioned as key partners in advancing LHS to improve healthcare outcomes.