Without early and aggressive treatment of juvenile idiopathic arthritis (JIA), patients can suffer destructive joint damage, long-lasting pain, and disability. There are safe and effective options for managing arthritis that not only treat but also halt disease progression. Unfortunately, an accurate diagnosis often takes many months, causing families unnecessary pain and stress. First, this project will use a national claims database to characterize healthcare utilization in the year preceding JIA diagnosis and use machine learning to generate archetypal trajectories to diagnosis. Second, this project will leverage a panel of CARRA physicians and parent stakeholders to establish a consensus definition of diagnostic delay. This research will lay the foundation for future work to design interventions to eliminate barriers to timely, accurate, and equitable diagnosis for patients with JIA.