CaptureDX

Background and Challenge

Pediatric trauma centers face unique obstacles to delivering expert-level care: low physician confidence with ultrasound and inefficient documentation often delay diagnosis and treatment. CT scans can fill the gap, but they carry long-term cancer risks for children. Dr. Kornblith wanted to change this. His lab at UCSF developed CaptureDX, an algorithm designed to work with point-of-care ultrasound (POCUS) to provide safer, faster, and more effective care—while advancing equitable access to expert-level pediatric trauma care.

To move from concept to practice, Dr. Kornblith partnered with SOM Tech to create an MVP and test whether an app-based POCUS workflow could integrate seamlessly into the clinical environment and run across a wide range of machines.

Ensuring Seamless Integration into the Workflow

Our collaboration began with discovery. We mapped the Pediatric ER workflow to identify where the app could fit and how it would interface with ultrasound devices and the EHR, while in parallel creating sketches of user actions and system interactions.

Turning Insights into Innovation

With a shared understanding and clear product vision, we began wireframing the app, envisioning features to:

• Capture: AI-assisted image capture that evaluates scan quality, identifies key landmarks, and prompts rescans when necessary

• Interpret: AI-assisted diagnostic interpretation, that clinicians can review, accept, or modify

• Document: Automated documentation to the EHR and billing system

Testing and Iteration

Wireframes became a clickable prototype, which we tested directly with physicians. Their feedback shaped refinements to the interface and confirmed what mattered most in high-pressure clinical scenarios.