ROLE · User Experience Designer | CATEGORY · Healthcare | TIMELINE · 4 Weeks
The Problem: High Pressure, Blind Decisions
This project was designed alongside Global Ties at UC San Diego, a team developing a portable, dry-node EEG cap to help EMTs differentiate ischemic from hemorrhagic stroke in the field. The device is still in development. As the UX team, our role was to design the interface responders would use to interpret and act on its output during transport, since existing diagnostic tools are too bulky for a moving ambulance, and a wrong call in the field often means a costly secondary transfer.
Three breakdowns defined the failure:
Uninterpreted Signals. Responders lacked tools to translate neurological data into an actionable signal under pressure.
Distance-Only Routing. Ambulances were routed to the nearest hospital, not the one equipped for the specific stroke type.
Blind Handoffs. Receiving teams got incomplete pre-arrival data, forcing them to react at the ER door instead of preparing in advance.
Field Validation: The Power of Intentional Friction
We ran moderated simulations with four EMS responders through a scripted stroke scenario. The clearest failure was in the BE-FAST assessment: "Time," meaning last known well time, a critical metric for treatment eligibility, was represented by an unlabeled checkbox. When responders saw a patient wearing a watch, all four checked it, capturing nothing clinically useful.
We replaced the checkbox with an explicit time-entry field. On retest, all four responders correctly entered the last known well time, up from zero.
The Solution: Surfacing Actionable Clarity Under Pressure
We designed the interface around the decisions responders needed to make: identify the stroke type, select the right hospital, prepare the receiving team.
Interpreted Stroke Signal.
Raw EEG waveforms mean nothing in a moving ambulance. We translated the cap's output into a single interpreted signal, ischemic or hemorrhagic, paired with a confidence score.
Designing for Uncertainty.
The BE-FAST checklist guides responders through each indicator without relying on memory, including the explicit time field rather than an ambiguous checkbox.
Capability-Based Routing.
The app ranks nearby hospitals by real-time treatment capability and staff availability rather than distance, removing that judgment from high-stress conditions.
Pre-Arrival Handoff Package.
Patient history, symptoms, witness notes, and EEG classification are transmitted before arrival so ER teams can prepare trauma bays ahead of time.
Outcome: Eliminating Hesitation at Handoff
100% accurate data capture. All four responders captured the exact last known well time on retest, up from zero.
Reduced hesitation. Once the checkbox was replaced, responders moved through BE-FAST without pausing over what "Time" meant.
Reflection: Resisting the Urge to Add
This project taught us to resist the urge to add. Every decision came down to one question: does this help a responder make the next decision, or is it noise?
The BE-FAST checkbox made that lesson concrete. It looked right and worked as designed, yet captured nothing clinically useful, and all four responders misread it the same way. Designing alongside a real hardware team made us more deliberate about what earned space on the screen. If we continued the project, we'd validate the other side of the handoff: whether the pre-arrival summary actually helps receiving teams prepare faster.
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