TrialBridge
EHR-integrated clinical decision hub that matches patients to trials.
The Brief · Design Challenge"How might we reduce the cognitive and logistical burden of clinical trial matching so that no eligible patient misses a life-changing opportunity?"
Design Principles
Clarity over completeness
Surface the right data at the right time.
Risk mitigation by design
Every decision reduces a failure mode.
Progressive disclosure
Earn trust before asking for data.
−40%
Steps cut
54% → 89%
Onboarding completion
3
Physicians embedded
7
Core UX modules
Key Challenges
User Challenges
- 1.Patients couldn't assess trial eligibility without medical knowledge.
- 2.Physicians had no time for manual matching.
- 3.Trust in digital health tools was low.
Design & Constraint Challenges
- 1.EHR data is sensitive — privacy constraints shaped every flow.
- 2.Physician pushback on onboarding data collection required a pivot.
- 3.WCAG 2.2 compliance was non-negotiable across all 7 modules.
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Research artifact
Drop in an affinity diagram, journey map, or synthesis board that shaped the direction.
Situation
Clinical trial recruitment at Mayo Clinic was broken — patients couldn't find relevant trials, and physicians had no efficient way to match them. The manual process caused eligible patients to miss life-changing opportunities.
Task
As lead UX designer, working directly with Mayo Clinic physicians Dr. Umar, Dr. Riaz, and Dr. Kumar, I designed TrialBridge — an EHR-integrated clinical decision hub bridging patients and clinical trials.
Action
- Ran stakeholder interviews with 3 Mayo Clinic physicians to map pain points in the existing trial-matching workflow.
- Built 7 core UX modules: patient dashboard, trial search with filters, eligibility screener, physician referral flow, onboarding, notifications, admin panel.
- Usability tested and mapped findings to Nielsen's 10 Usability Heuristics — surfaced critical issues with navigation clarity (#6) and error prevention (#5).
- Applied WCAG 2.2 Level AA standards throughout — contrast ratios, focus states, screen-reader labels.
- Took physician pushback on upfront data collection → pivoted to progressive disclosure, lowering perceived friction.
- Framed every decision through a Human Factors Engineering lens — systematic risk mitigation, not preference.
- Iterated through 3 design rounds with EHR-integrated physician-side wireframes.
Result
- Delivered a fully documented UX system with annotated wireframes, usability report, and design rationale.
- Navigation redesign reduced task-completion steps by 40% in testing.
- Onboarding redesign lifted simulated completion from 54% → 89%.
- Presented to Mayo Clinic physicians who validated clinical utility.
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Process & exploration
Sketches, flow diagrams, wireframes, or iteration shots.
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Final outcome
Hero shot of the final screen, artifact, or installed deliverable.
Tech Stack
FigmaFigJamMazeWCAG 2.2 audit tools
Research Methods
Stakeholder interviewsThink-aloud usability testingHeuristic evaluation (Nielsen)Task analysisHuman Factors Engineering
Tags
Healthcare UXEHR IntegrationAccessibilityResearchInteraction Design
Lessons Learned
- "Physician pushback was the best thing that happened to this project. It forced me to question my assumptions about what 'helpful' looks like in a clinical context."
- "Human Factors Engineering gave me a framework I now apply to every design decision — not 'does this look good' but 'what fails if this is wrong.'"
- "Designing for healthcare taught me that clarity isn't just good UX — it's a patient safety issue."