Inform Shared Decision-making with Advanced Bayesian Causal Inference to Improve Quality of Pediatric Rheumatology Care - PROJECT SUMMARY/ABSTRACT When faced with treating a child with Juvenile Idiopathic Arthritis (JIA), a heterogeneous chronic condition with no known etiology or cure, there is no one-size fits all solution. Clinicians rely on their past experiences and learnings from peers and the scientific community to make the best decision for JIA patients. Yet despite multiple FDA approved treatments, only 40 percent of patients with a polyarticular form of JIA achieve a state of controlled disease, it is hard to treat. While clinical expertise is invaluable, relying on clinician experience alone at point of care (POC) when treating an uncommon (1 in 1000 children) and disabling disease with heterogeneous presentation and variable treatment response may result in missing a critical window of opportunity for early remission and suboptimal outcome. Imagine the power of a digital health technology (DHT) that uses real world data to inform effectiveness of different treatment strategies for every child. By learning collectively from past experiences of a network of providers and patients that leverage a shared clinical data registry, the DHT synthesizes, and updates knowledge centered for the patient at the POC, while considering the values and preferences of patients for shared decision-making (SDM). Currently, there is no such DHT available to deliver the patient-centered comparative effectiveness evidence at the POC. This study aims to close such a gap with novel user-centered design to adapt for use at POC an existing researcher facing application package based on advanced Bayesian causal learning methods applied to real world electronic health record (EHR) data. This DHT, called PCATS.JIA (Patient centered adaptive treatment strategies for JIA care) will be implemented within the setting of a 23-center learning health network. In R21 phase, the study aims to: 1) bring the PCATS platform to the POC by developing a PCATS.JIA DHT that is EHR system agnostic; 2) co-design a graphic user interface for PCATS.JIA as a patient-centered SDM tool together with key stakeholders (patients, parents, and clinicians); and 3) pilot test PCATS.JIA as a SDM tool at POC in a single rheumatology practice. In R33 phase, we will refine, test, and evaluate the PCATS.JIA in three pediatric rheumatology clinics by 1) using quality improvement science and implementation science principles to implement PCATS.JIA into the clinic workflow with high reliability; and 2) demonstrating that use of PCATS will result in improved health care service as reflected in more patient-centered care, improved health outcomes, and health equity. The study promises to deliver a novel patient centered DHT that is robust, flexible and improves quality and equity of care and treatment outcomes as tested within the practice of pediatric rheumatology. Being EHR system agonistic, it is scalable to different clinical centers. This DHT has the potential to be generalizable to broader disease conditions and patient populations.
