Leveraging the PEDSnet clinical research network and electronic health record data to enhance efficiency of trial enrollment for a rare pediatric rheumatic disease

Year of Publication:

Categories of Publication:

Lay Abstract and Manuscript Citation:

Title: Finding Kids With Rare Arthritis Using the PEDSnet Network
Key Words: PEDSnet, juvenile spondyloarthritis, rheumatology, rare diseases, clinical trials
This study looked at how well the PEDSnet network can help doctors find children with juvenile spondyloarthritis, a rare type of arthritis. Researchers used electronic health records from eight children’s hospitals to identify kids with different rheumatic diseases. They studied data from 2009 to 2023.
They found more than 2,500 children with juvenile spondyloarthritis across the PEDSnet hospitals. Most children were around 13 years old when they first saw a rheumatologist. The team created special computer “typologies,” or search tools, to help quickly find patients who might qualify for research studies.
When these tools were used to help recruit for a clinical trial, they saved many hours of work compared to reading charts by hand. This shows that PEDSnet can make it much easier to find children with rare diseases for important studies. Faster identification means research can move forward more efficiently.
Takeaways 
 
Why does this matter? Finding kids with rare diseases quickly helps researchers learn more and develop better treatments.
What does this mean for patients and families? Tools built using PEDSnet make it easier for children to be matched with clinical trials, giving families more opportunities for specialized care and advancing research that can improve future treatments.

Citation

Weiss, P.F., Utidjian, L., Maltenfort, M. et al. Leveraging the PEDSnet clinical research network and electronic health record data to enhance efficiency of trial enrollment for a rare pediatric rheumatic disease. Pediatr Rheumatol (2026). https://doi.org/10.1186/s12969-025-01181-5

Find publication:

https://link.springer.com/article/10.1186/s12969-025-01181-5

The lay abstract for this publication was generated using an AI model and reviewed by the lead author and the PEDSnet Engagement Core team.

Scroll to Top