Medimatch

Streamlining healthcare access by designing an AI-powered mobile app that intelligently matches patients to providers.

Role

UX/UI Designer

Industry

Health

Duration

4 weeks

Background

In the US, patients report difficulty finding and booking appointments with appropriate specialists, often waiting weeks for care while navigating a fragmented healthcare system. Existing healthcare booking platforms require users to have an understanding of medical diagnoses, insurance networks, and provider specialties which creates barriers before care even begins.

Problem

Patients struggle to answer a fundamental question: "Which doctor should I see, and when can I see them?" Current booking experiences assume users already know what type of provider they need, forcing them through time-consuming searches across multiple platforms, phone calls, and insurance verification—often leading to abandoned bookings or delayed care.

Solution

A healthcare booking app that guides patients from symptoms to scheduled appointments. Using conversational AI, the app translates user concerns into appropriate provider matches, checks real-time availability across insurance networks, and confirms bookings while still giving users full transparency and control to adjust recommendations at any step.

Background

Problem

Solution

Understanding the Healthcare Booking Problem

Competitive Analysis

Current healthcare booking platforms streamline logistics, but fail to support the decision-making and post booking process.

My analysis revealed that platforms like Zocdoc and Healthgrades excel at real-time booking and insurance verification but assume patients already know which provider to see. None offer symptom-based guidance, cost transparency, or appointment preparation which leaves users to navigate complex medical decisions alone, resulting in anxiety and abandoned bookings.

User Research

Patients need faster booking and trusted guidance.

I interviewed patients who had recently booked medical appointments to pinpoint where users get stuck and why current solutions fall short. These interviews uncovered a need for trusted guidance throughout the care journey — from symptom interpretation to provider selection to appointment confirmation.

Key Insights

Insurance is the first and biggest barrier. Every participant prioritized confirming in-network coverage before considering any provider, but current tools still cause difficulty.
Patients don't know which doctor to see. Once insurance was verified, users struggled to match symptoms to the right provider type. Reviews helped but weren't trusted without cross-referencing multiple sources.
Online booking feels unreliable. Outdated listings, duplicate forms, and integration issues led patients to call offices for confirmation—undermining the convenience of digital booking.
Appointment preparation is inadequate. Users felt unprepared about costs, what to bring, and what to expect, relying on handwritten notes to track symptoms and questions.
Trust requires human reassurance. Beyond credentials, patients valued empathy, clear communication, and personal confirmation that their appointment was real.

Meet the Patients Behind the Problem

Personas

Who struggles with navigating healthcare services?

Using insights gathered from the user interviews, I created user personas to reflect the personality types of the users and their pain points and goals.

Problem Statements

What are their problems with the healthcare booking journey?

Patients feel overwhelmed throughout the booking journey - from choosing providers with unreliable information to arriving at appointments unprepared and anxious about communicating symptoms.

Designing the Experience

User Flow

The AI-guided booking flow.

This user flow illustrates how patients are guided from initial symptom input through provider selection to appointment confirmation, reducing friction and building trust throughout the process.

Wireframes

Designing and testing the core experience.

Starting with low-fidelity sketches, I explored key user flows—particularly the AI-guided provider matching and scheduling. These initial concepts were digitized and tested to validate usability and interaction patterns.

Putting the Designs to the Test

Usability Testing

High fidelity testing achieved 100% task completion with positive user feedback, revealing opportunities to clarify terminology, reduce redundancy, and improve navigation discoverability.

Usability testing at each stage ensured the design remained user-centered while increasing visual polish. Informed by usability testing insights, I made iterations then added branding and visual polish to create high-fidelity wireframes.

Bringing It All Together

Final Designs

The final iteration incorporated testing insights to fine-tune interactions, visual hierarchy, and user flows.

Final refinements addressed key testing feedback to create a polished, user-centered interface that balances guidance with efficiency, and ensuring an intuitive and engaging experience.

What I Learned

Reflection

Designing with purpose, speed, and strategy.

This project strengthened my end-to-end design skills while pushing me to balance innovation with practical constraints. Managing scope and timeline challenges taught me to make strategic trade-offs —prioritizing core differentiating features and leveraging proven design patterns. Moving forward, I'll recruit participants earlier in the process and continue exploring AI tools to enhance both design thinking and execution speed.