Research
Use user research to understand the people and workflows around clinical review.
Healthcare UX · SiteRx · AI-assisted exploration
TrialMatch AI.
Cognitive support for clinical reviewers — a decision-support platform designed to reduce the cognitive load on clinical coordinators.
The challenge
Clinical work needed clearer review.
Clinical trial matching and patient recruitment involved complex workflows for physicians, healthcare teams and patients.
The design work translated clinical and operational requirements into user journeys, wireframes, prototypes and production-ready interfaces.
The design opportunity
Make the system easier to reason about — without hiding the complexity behind it.
Structure
Translate clinical and operational requirements into clear journeys and interaction patterns.
Explore
Use rapid, AI-supported exploration to evaluate alternative flows and content structures.
Prototype
Move from workflow definition to wireframes, prototypes and production-ready interfaces.
My role
End-to-end product design for clinical trial matching.
User research
Translated clinical and operational requirements into user journeys and interaction problems to solve.
Complex workflows
Worked across clinical trial matching and patient recruitment experiences with attention to healthcare context.
Rapid exploration
Created wireframes, prototypes and production-ready interfaces while evaluating alternative flows and content structures.
Cross-functional design
Collaborated with US-based product, engineering and healthcare stakeholders while balancing user, business and regulatory considerations.
Outcome
Cognitive support, not cognitive replacement.
TrialMatch AI was positioned as decision support: helping clinical coordinators work through complex matching tasks while keeping the human review process central.
The work combined user research, complex-system thinking, prototyping and AI-supported exploration to make difficult clinical workflows easier to understand and act on.