Context
K Health is a leading AI-powered healthcare platform serving millions of patients across the U.S. The challenge was to design a patient experience that balances accessibility and trust and at scale.
Contribution
Timeline: November 2022 - July 2025
I worked as a Senior Product Designer, leading design for onboarding, AI-chat triage, design system governance, and accesibility. My focus was implementing a delightful and unified experience for patient facing apps while working cross-functionally with PMs, engineers, clinicians, and researchers.
Highlights
"Cedars-Sinai's AI tool [powered by K Health] delivered 24/7 care to 42,000 patients. Now, doctors can focus more on treatment, less on paperwork."
- Business Insider
From sign up to visits
I worked with product managers and engineers to design the leanest flow to get patients from auth to a visit with their doctor. Some challenges we collaboratively resolved were: removing extra steps in auth by implementing SSO, implementing out-of-band profile completion anytime for a visit, and syncing medical history with from Epic.  
K Health User Flow after iterative refinements
Design system adoption across product teams
I inherited a design system called Jonas, and managed its evolution through product team turnover and onboarding new team personnel. I was able to implement a process that helped to create consistency across components used in different product team contexts and incorporated new features such as semantically named color tokens.

These included form fields, photo inputs, cards, modals and more.  
WCAG 2.0 and accessible resizing
Patient feedback from our App Store experience revealed a clear expectation for iPad support — many users said they would be more likely to use the app if it were available in that format.

This launched a comprehensive deep dive into how K Health's offerings worked on various screen sizes with different type ramp settings.
K Health's pharmacy selection using Apple's type ramp for xSmall, Large(default), and xxLarge
WCAG color contrast testing for most common foreground and background combinations