video1.0<iframe src="https://www.loom.com/embed/c70bdf7c168f406a82e30ec8303c1382" frameborder="0" width="1148" height="861" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>8611148Loomhttps://www.loom.com8611148https://cdn.loom.com/sessions/thumbnails/c70bdf7c168f406a82e30ec8303c1382-818132a0c75c0064.gif92.504This Loom demonstrates how Spotted Zebra uses decision support to identify patterns in pediatric longitudinal patient records. It shows a child’s record containing primary care visits, developmental assessments, and pediatric cardiology follow-ups across 592 records. When the user clicks Analyze Longitudinal Record, the tool identifies character patterns such as delayed ability to walk, hypotonia, and short stature, which are then cross-checked and either confirmed or rejected. The results can be converted into tasks and guidance, and users can download a JSON FHIR bundle or open FHIR resources for further investigation.