This project is part of AcademyHealth’s efforts to better understand and address disparities in diagnosis with funding from the Gordon and Betty Moore Foundation. The goal of this project is to inform targets for intervention in future studies to improve diagnosis and promote diagnostic excellence for pediatric rheumatic diseases. Diagnostic inequities and delays exacerbate disparities based on race, insurance status, socioeconomic status, and household income for children with Juvenile Idiopathic Arthritis (JIA), resulting in the unequal distribution of poor outcomes such as joint damage, chronic pain and disability, and blindness. The research team will use innovative machine learning techniques to generate archetypal trajectories to diagnosis and identify patient characteristics associated with delayed referral to rheumatology. The study involves a retrospective chart review in a large tertiary care center to examine referral pathways and healthcare utilization prior to diagnosis. Using data from the chart review, the team will quantitatively examine diagnostic inequities by assessing associations between social determinants of health and the length of time to one receiving a diagnosis. To construct a detailed understanding of the diagnostic process, the researchers will then conduct and analyze semi-structured interviews with the parents or guardians of patients with JIA to identify barriers and facilitators to receiving a timely diagnosis. Deliverables will include a project work plan, narrative and financial reports, and a range of products to reach clinicians, policymakers and other audiences for study findings.