The health care field continuously generates a large amount of real-world data, and the increasingly digitized nature of health care presents opportunities to leverage that data to actively drive iterative improvements in care practices. While the concept of “learning health systems” has been present for some time, broad implementation of learning health principles has fallen short of expectations. In this paper, we explore the current status of real-world data (RWD) use in a subset of U.S. health systems with the aim of gaining a clear understanding of the current state of implementing learning health system enabled by real-world data. Additionally, we sought to identify current health system practices that involve collecting, acquiring, and leveraging real-world data to achieve systematic and intentional data collection and actionable evidence generation and implementation. Based on these findings, we provide recommendations pertaining to infrastructure development, supportive payment models, informed consent considerations, and workforce training needs.