Transforming Healthcare Billing
ROLES
Research
User Testing
UX Design
UI Design
AI Prototyping
PLATFORM
Web
RESULTS
60% reduction in development cycle
40% user billing efficiency gain
4.6/5 User Satisfaction
At MD Clarity, our legacy UI codebase and manual handoffs between design and dev made prototyping a slog—building a single working prototype often took 3–4 weeks, bogged down by outdated components, brittle integrations, and endless back-and-forth.I pioneered the use of AI-powered prototyping tools to break the bottleneck. By generating high-fidelity, interactive flows in hours—not weeks—I enabled rapid design validation, real-time user testing, and seamless dev handoff. This shift accelerated the full product development cycle by 60%, slashed rework, and drove a significant lift in user satisfaction scores as complex healthcare workflows became clearer, faster, and more intuitive.
The Challenge
Healthcare billing systems are notoriously complex. Our users needed intuitive tools to manage patient visits, track payments, and resolve billing issues—all while maintaining compliance and accuracy.
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Work Lists
Designed an intelligent work queue system that helps staff prioritize patient visits, track outstanding balances, and identify billing issues before they escalate.
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Patient Billing
Created a comprehensive billing interface that simplifies payment collection, insurance management, and benefit verification for medical practices.
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AI Prototyping
Leveraged AI tools to rapidly generate interactive prototypes, enabling weekly user testing sessions that informed critical design decisions.
User Journey Flows
Before diving into prototyping, we mapped detailed user journey flows to understand the complete workflow of medical billing specialists. These flows identified critical pain points and opportunities for improvement.
Work Lists JTBD
Work Lists Journey Flows
Key Finding
Users were spending 40% of their time navigating between multiple systems to complete a single billing task. Consolidation was critical.
Opportunity Identified
The lack of real-time payment status visibility led to delayed collections and frustrated patients. This became our top priority.
Early Prototype
Work Lists Dashboard
This AI-generated prototype served as our foundation for user testing. Within two weeks, we gathered feedback from 5+ medical billing specialists that shaped the final design. Beforehand the team would have talked a customer through the dashboard with no visuals except a static diagram and spent months developing.
Key Insight #1
Users needed quick access to payment status without navigating away from the work list
Key Insight #2
Visual indicators for snoozed visits and unresolved benefits were critical for workflow efficiency
Key Insight #3
The ability to filter by patient, provider, and insurance was the most requested feature
Design Process
By combining traditional UX methods with AI-powered tools, we created a design process that was both thorough and incredibly fast.
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User Journey Mapping
Created detailed user flows identifying pain points in current billing workflows.
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AI-Powered Prototyping
Used AI tools to generate interactive prototypes in hours instead of weeks
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Rapid User Testing
Conducted weekly testing sessions with billing specialists to validate concepts
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Iterative Refinement
Quickly incorporated feedback and refined designs based on real user insights
✨The AI Advantage
Traditional prototyping would have taken 3-4 weeks per iteration. With AI tools, we generated functional prototypes in 2-3 days, allowing us to test multiple concepts simultaneously and get our designs in front of users 10x faster.
Time Saved
60% reduction in design cycles
User Sessions
25+ testing sessions conducted
Early Prototype
Patient Visit Billing Dashboard
I transformed MD Clarity’s client-facing patient billing dashboard from a scattered, multi-tab mess that buried out-of-pocket costs, secondary insurance details, and payment blockers into a single, at-a-glance screen. Using an AI-generated interactive prototype as the core, I consolidated all key data for instant clarity. In just two weeks, testing with 10+ medical billing specialists refined the final design through real-time feedback. What once dragged on for months with static diagrams and verbal walkthroughs now wraps in days, delivering sharper visuals, zero confusion, and lightning-fast dev handoffs.
“the first time I’ve ever understood a patient bill on the first try.” - user tester
Key Insight #1
Billing specialists instantly grasped patient responsibility in less than 4 seconds. No more hunting across tabs for out-of-pocket amount and blockers.
Key Insight #2
Secondary insurance status & unresolved benefits warnings surfaced upfront, cutting follow-up questions by 80% and preventing surprise bills.
Key Insight #3
One-screen clarity replaced 5–7 clicks — testers called it “the first time I’ve ever understood a patient bill on the first try.”
Final Product
After multiple rounds of user testing and iteration, the AI prototypes evolved into production-ready designs that addressed every pain point we identified in our research. Below are customized branding examples.
Work Lists Dashboard
Production
Smart Filtering
Advanced filters by patient, provider, insurance, and status based on user feedback
Inline Actions
Quick access to payment status and patient details without leaving the work queue
Visual Priorities
Color-coded status indicators for snoozed visits and unresolved benefits
Patient Billing Interface
Production
Payment Collection
Streamlined payment processing with multiple payment method support
Insurance Management
Real-time benefit verification and automated eligibility checks
Patient Portal
Self-service billing options reducing staff workload by 30%
Impact & Results
The combination of AI-powered prototyping and user-centered design delivered measurable improvements across the product development process and user experience.
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60%
Faster Design Cycles
AI prototyping reduced iteration time from weeks to days
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4.6/5
User Satisfaction
Post-launch satisfaction score from billing specialists
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40%
Efficiency Gain
Reduction in time spent resolving billing issues
Key Learnings
AI accelerates ideation, not replace
AI tools enabled us to explore more design directions quickly, but human insight and user feedback remained essential for validating the right path.
Speed enables better testing
AI tools enabled us to explore more design directions quickly, but human insight and user feedback remained essential for validating the right path.
Complex domains need real user input
Healthcare billing is too nuanced for assumptions. Weekly testing with actual billing specialists was crucial to getting the details right.