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Digital health technology to support patient-centered shared decision making at point of care for juvenile idiopathic
Bin Huang1,2, Michal Kouril2,3, Chen Chen1
1Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
Insights
New digital tools can help personalize juvenile idiopathic arthritis (JIA) treatments. By analyzing real-world data, these technologies support shared decision-making between doctors and families for better outcomes in pediatric rheumatic disease.
Area of Science:
- Pediatric Rheumatology
- Digital Health
- Health Informatics
Background:
- Juvenile idiopathic arthritis (JIA) affects 1:1,000 children, causing pain and disability despite available therapies.
- Current JIA treatment selection relies on average patient data from clinical trials or insurance restrictions, not individual patient needs.
- Existing treatment paradigms lack personalization and do not account for heterogeneous treatment effects in JIA.
Purpose of the Study:
- To introduce a novel digital health technology concept for personalized JIA treatment decisions.
- To enable shared decision-making by integrating patient-centered, real-world evidence into clinical practice.
- To leverage comparative effectiveness analysis of electronic health record data for individualized care.
Main Methods:
- Utilizing digital health technology to capture and analyze electronic health record or observational registry data.
- Performing comparative effectiveness analysis on data from patients with similar characteristics.
- Developing a tool to present individualized, patient-centered information for shared decision-making.
Main Results:
- The proposed digital tool aims to organize and present relevant data for individual JIA patients.
- It facilitates evidence-based, individualized treatment decision-making in a collaborative setting.
- This approach aligns with the principles of a learning health system at the point of care.
Conclusions:
- Digital health technology offers a promising avenue for optimizing JIA treatment selection.
- Personalized treatment decisions based on real-world evidence can improve outcomes for children with JIA.
- Integrating patient-centered data into rheumatology practice enhances the collaborative decision-making process.
Abstract:
Despite availability of multiple FDA approved therapies, many children with juvenile idiopathic arthritis (JIA) suffer pain and disability due to uncontrolled disease. The term JIA includes a heterogeneous set of conditions unified by chronic inflammatory arthritis, collectively affecting 1:1,000 children. When reviewing treatment options with families the rheumatologist currently refers to the experience of the average patient in relatively small controlled clinical trials, to consensus-based treatment plans, or increasingly the choice is dictated by the formulary restrictions of insurance payers. The current paradigm for treatment selection does not incorporate real-world evidence of treatment effectiveness centered to the individual patients with whom decisions are to be made. Treatment decisions based on the evidence of the average patient are not optimized to reflect the unique clinical characteristics of an individual with JIA and their disease course, nor does it account for heterogeneous treatment effects. To guide treatment choices centered around each patient, we describe a novel concept of utilizing digital health technology to bring patient-centered information into shared decision-making discussions based on comparative effectiveness analysis of electronic health record or observational clinical registry data of patients with similar characteristics. The envisioned digital tool will organize and present data relevant to the individual patient and enable evidence-based individualized treatment decision making when used in a collaborative manner with the patient family and rheumatologist. Capabilities in digital health technology, data capturing, and analytical methodologies are ripe for this endeavor. This brings the concept of a learning health system directly to the point of care.
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