Lab results dashboard

Jan 29, 2026

Patient portal app

AI Agent–Driven Lab Experience

A comprehensive lab results dashboard designed to help users interpret complex biomarker data with clarity and confidence. The system organizes laboratory results into structured health categories, highlights out-of-range markers, and surfaces personalized recommendations — transforming static reports into an interactive health intelligence platform.

Scope: Product UX, data visualization, information architecture, system design
Platform: Responsive web + mobile experience

0M+

users reached

months of collaboration

7000+

hours of time saved

The process

Traditional lab reports are dense, technical, and difficult for non-clinicians to interpret. Users often struggle to:

Understand what results mean
Identify priority markers
See trends over time
Know what actions to take

The challenge was to reduce cognitive overload while preserving medical accuracy and clinical credibility.

Discovery

/research and insights

Analyzed how users interpret lab reports, where confusion occurs, and how prioritization could be made clearer through structured categorization.

Discovery

/research and insights

Analyzed how users interpret lab reports, where confusion occurs, and how prioritization could be made clearer through structured categorization.

Discovery

/research and insights

Analyzed how users interpret lab reports, where confusion occurs, and how prioritization could be made clearer through structured categorization.

Design

/concepts and execution

Developed a modular system for biomarker presentation, including scoring models, visual sliders, radar graphs, and contextual explanations.

Design

/concepts and execution

Developed a modular system for biomarker presentation, including scoring models, visual sliders, radar graphs, and contextual explanations.

Design

/concepts and execution

Developed a modular system for biomarker presentation, including scoring models, visual sliders, radar graphs, and contextual explanations.

Testing & Iteration

/feedback and refinement

Iterated on alert states, color use, density, and microcopy to ensure users could distinguish urgency without feeling overwhelmed.

Testing & Iteration

/feedback and refinement

Iterated on alert states, color use, density, and microcopy to ensure users could distinguish urgency without feeling overwhelmed.

Testing & Iteration

/feedback and refinement

Iterated on alert states, color use, density, and microcopy to ensure users could distinguish urgency without feeling overwhelmed.

Delivery

/handoff and launch

Delivered a scalable dashboard experience optimized for both desktop and mobile, ensuring accessibility and consistency across health categories.

Delivery

/handoff and launch

Delivered a scalable dashboard experience optimized for both desktop and mobile, ensuring accessibility and consistency across health categories.

Delivery

/handoff and launch

Delivered a scalable dashboard experience optimized for both desktop and mobile, ensuring accessibility and consistency across health categories.

Scaling

/growth optimization

Designed the system to support expanding biomarker panels, new recommendation types, and longitudinal health tracking without disrupting structural clarity.

Scaling

/growth optimization

Designed the system to support expanding biomarker panels, new recommendation types, and longitudinal health tracking without disrupting structural clarity.

Scaling

/growth optimization

Designed the system to support expanding biomarker panels, new recommendation types, and longitudinal health tracking without disrupting structural clarity.

Performance at scale

Satisfaction

Score

87%

37+

Countries

37+

Countries

37+

Countries

0K+

Views

0K+

Views

0K+

Views

Languages

17M+

Active users

2021

2022

2023

2024

2025

Patient portal app

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