The article discusses the concept of learning health systems (LHS), which aim to continuously improve healthcare through the integration of internal data and external evidence. Despite increased focus on quality improvement in healthcare over the past 50 years, many challenges persist, such as 60% of care not aligning with guidelines, 30% being low value, and 10% involving adverse events. While technology and data analytics have advanced, progress remains slow. LHS offer a pathway for continuous improvement by systematically integrating data, evidence, and learning. The US Institute of Medicine first proposed the concept, emphasizing the alignment of science, informatics, incentives, and culture for continuous improvement. However, there is a lack of practical guidance and evidence of return on investment, leading to skepticism about their feasibility. Examples of successful LHS include MQ Health in Australia and ImproveCareNow in the US, which have improved patient outcomes and care delivery. Learning health systems rely on learning communities, which include diverse stakeholders such as clinicians, researchers, patients, and administrators. These communities co-design strategies, identify data and tools, and drive continuous improvement. Key components of LHS include data collection, analysis, and sharing, as well as the use of technology platforms for data management. Learning communities must have the appropriate expertise and skills to engage in learning cycles, and patients play a crucial role by contributing data for the greater good. The article emphasizes the importance of culture, leadership, and organizational structures in supporting LHS. A culture that values curiosity, learning, and innovation is essential. Leadership is crucial in motivating staff and fostering a collaborative environment. The article also highlights the need for tools and frameworks, such as the NASSS framework, to manage complexity and support the implementation of LHS. The LHS Toolkit has been developed to help practitioners share tools and case studies. The article concludes that while LHS remain the exception, many health systems can benefit from some components of LHS, and the focus on enablers and actions outlined in the article can help achieve continuous, intelligent improvement in patient care.The article discusses the concept of learning health systems (LHS), which aim to continuously improve healthcare through the integration of internal data and external evidence. Despite increased focus on quality improvement in healthcare over the past 50 years, many challenges persist, such as 60% of care not aligning with guidelines, 30% being low value, and 10% involving adverse events. While technology and data analytics have advanced, progress remains slow. LHS offer a pathway for continuous improvement by systematically integrating data, evidence, and learning. The US Institute of Medicine first proposed the concept, emphasizing the alignment of science, informatics, incentives, and culture for continuous improvement. However, there is a lack of practical guidance and evidence of return on investment, leading to skepticism about their feasibility. Examples of successful LHS include MQ Health in Australia and ImproveCareNow in the US, which have improved patient outcomes and care delivery. Learning health systems rely on learning communities, which include diverse stakeholders such as clinicians, researchers, patients, and administrators. These communities co-design strategies, identify data and tools, and drive continuous improvement. Key components of LHS include data collection, analysis, and sharing, as well as the use of technology platforms for data management. Learning communities must have the appropriate expertise and skills to engage in learning cycles, and patients play a crucial role by contributing data for the greater good. The article emphasizes the importance of culture, leadership, and organizational structures in supporting LHS. A culture that values curiosity, learning, and innovation is essential. Leadership is crucial in motivating staff and fostering a collaborative environment. The article also highlights the need for tools and frameworks, such as the NASSS framework, to manage complexity and support the implementation of LHS. The LHS Toolkit has been developed to help practitioners share tools and case studies. The article concludes that while LHS remain the exception, many health systems can benefit from some components of LHS, and the focus on enablers and actions outlined in the article can help achieve continuous, intelligent improvement in patient care.