Project 435304

When arthritis strikes a child, families face tough questions. Will their child suffer? Will they outgrow arthritis? Will they respond to treatment? Will there be side effects? The answers to these questions are crucial to choosing the best treatment for their child. Using information provided by thousands of families, we have developed a way of providing answers to these questions that are specific for the child and accessible right on the doctor's smartphone. The answers are generated automatically based on the child's circumstances using "personalized prediction algorithms" and presented in an app. In this study, we will test whether a structured discussion between families and doctors (guided by a graphical report produced by our personalized prediction algorithms and presented in the doctor's smart phone or computer) improves the tailoring of treatment to the child and control of the disease. The report is called the PERSON-JIA report and it presents the expected severity of disease for the child, the likelihood that the child will be arthritis-free as an adult, and the chance that treatments will be effective and/or have side effects. We will randomize (like flipping a coin) all willing Canadian pediatric rheumatologists to either (a) review the PERSON-JIA report in clinic with the family, or (b) continue to provide standard care. We will then check the decisions made and how well the children are doing six months later. We expect that using our personalized prediction algorithms in a frank and thoughtful discussion will help physicians and families make better decisions for managing the child's disease. This in turn will result in better disease control, greater family engagement and satisfaction with care and better-tailored treatment. If so, we will have a ground-breaking way to use information provided by families to improve the care provided to and the outcomes of children with arthritis in Canada, and establish a world-leading approach for JIA care.