The authors interviewed 32 individuals with expertise in learning health systems to explore how such systems can work towards diagnostic excellence. Data, management, and behavioral barriers are discussed, such as the need to standardize measurement, the need for measures that both define and track errors, and that clinicians lack tools to self-assess diagnostic skills. The authors discuss how machine learning and artificial intelligence can be leveraged to advance diagnostic excellence, but that any meaningful integration must be accomplished through mutually beneficial collaborations among researchers and care providers.