Inform Shared Decision Making with Advanced Bayesian Causal Inference to Improve Quality of Pediatric Rheumatology Care

Approximate 80,000 children in the United States have juvenile idiopathic arthritis (JIA), a group of chronic inflammatory arthritic conditions that begin in childhood and have no known cause or cure. Of the seven subtypes, polyarticular JIA (pJIA) is the most difficult to control.  Despite multiple FDA-approved biologic and immunomodulatory medications available, the majority of those with pJIA have uncontrolled disease due to the differences in how individual patients respond to any given treatment. These differing responses may be related to timing of treatment following diagnosis, the sequence of treatment given, individual patient tolerance to treatment, and degree of treatment adherence. Therefore, approaching treatment in a patient-centric way is critical to treatment success and improving outcomes.

Research has shown that a “treat to target” approach, involving active monitoring and medication adjustments when treatment targets are not achieved, results in tighter disease control. However, given how uncommon the disease is, clinicians may simply not know what the next best treatment option might be. The use of evidence-based clinical decision support at the point of care, incorporating data from the electronic health record (EHR) and information regarding patient values and goals, would allow for improved shared decision making (SDM) and awareness of possible treatment options.

This research will develop and evaluate a patient-centered app to be used at the point of care called the Patient Centered Adaptive Treatment Strategies (PCATS) JIA tool, or “PCATS.JIA.”

The specific aims of the research are as follows:

• Bring the PCATS platform to the point of care by developing PCATS.JIA digital healthcare technology that is EHR agnostic.
• Codesign a graphic user inference for PCATS.JIA as a patient-centered SDM tool together with key stakeholders (patients, parents, and clinicians).
• Pilot test the PCATS.JIA as an SDM tool at the point of care in a single rheumatology practice.

An existing researcher-facing app will be adapted to incorporate EHR data in a manner that is EHR agnostic, so that it is scalable and interoperable. A graphical user interface will be developed for PCATS.JIA with input from patients, parents, and clinicians. The tool will use real-world data to analyze and predict the comparative treatment effectiveness of available medications to assist clinicians and patients in making treatment choices when a current method is failing. An initial pilot will be conducted in one rheumatology practice; the tool will then be refined, tested, and evaluated in three additional clinics. All participating clinics are within the setting of the Pediatric Rheumatology Care and Outcomes Improvement Network, a 23-center learning health network. The researchers intend to demonstrate that PCATS.JIA will result in more patient-centered care, improved health outcomes, and health equity.