VAST: Usable & Accessible Clinical App Redesign

I led the redesign of VAST, a voice ai swallow test app designed for clinicians and patients, to incorporate AI features and increase the usability and accessibility of the mobile app.

Company

Weill Cornell Medicine

Team

Product Designer

PM (Dr. Rameau, MD), 3 Dev engineers (Alex, Pantelis, Jeff), 2 ML researchers (Chen, John)

Role

Time

Apr 2025 - Present

Unclear flows and inaccessible UI blocked clinicians from finding patients, tracking visits, or viewing AI insights—leading to delays and errors.

The challenge

Specific goals

1. Enable Fast Patient Lookup
2. Ensure Complete Session Tracking
3. Surface AI Diagnostic Insights
4. Improve UI Usability & Accessibility

Key metrics

1. Patient‑Search Time (≤ 10 s)
2. Session‑Capture Completion (≥ 95%)
3. Accessibility Compliance (100%)
4. Clinician Satisfaction (≥ 80 (SUS) / ≥ 4 out of 5)

From problem to solution

Uncovering Accessibility & Usability Redflags

To identify the problems within the current screens, I audited current flows, friction points, accessibility and usability of the app and reported to the team.

I conducted interviews with 3 clinicians and researchers to map workflow challenges and confusions. The main problems I identified include:

Difficulty to look up patients or return to the most recent data entry
Unable to record multiple sessions for a patient
Unclear states & system indications
Difficult navigation and hand interactions

Identifying clinicians’ frustrations

Resolving product, technical, and user considerations with PM, engineers, and users in co-design workshops

I gathered PM, engineers, and clinician users together in 5 workshops to sketch and test new flows and ideas.

Updated Wireflows (Search and Patient Profile)

Designing for privacy

When I conducted user testing, I received the feedback that patients always try to look at screens, and listing patient names might cause leaks.

To resolve this problem, I changed the landing page into a powerful search feature and tutorials on how to perform tasks that helps patients before they enroll new data.

The users are very happy with the final design that balances privacy and practicality well.

Enhancing operation efficiency

Because the app is both client facing and clinician facing, the task screens added patient centered features—adjustable text sizes for senior patients, and expanding reading passage to ensure uninterrupted recording experience.

Another feedback from the PM was that the AI feature was not highlighted enough. Users have to hit user profile to be able to see AI diagnosis. To increase visibility, I added entry points of key user actions to search results, ensuring strong highlights on the product features.