LEAD
PRODUCT
DESIGN

AI-driven enterprise contact tracing app for hospitals

A PDF preview is available upon request

UX strategy and research: journey maps, provisional personas, experience visualizations, UX research, competitive analysis, stakeholder interviews, usability research sessions

UX and UI design: user flows, screen designs and iterations, content creation

Cross-team collaboration: integrated UX with sales strategy and ROI metrics, workflow modeling, collaborated with development team on focused solutions, developed product direction and collaborated on outreach content with CEO



As the first wave of Covid-19 inundated the New York City area, the staff at a major area hospital network were getting infected at an alarming rate.

Ethermed AI was pivoting their AI technology to address this problem within hospital settings, and the CEO asked me on board to lead the product design in the creation of their solution.

In true start-up fashion, the small globally-distributed team worked 7 days a week to develop a contact tracing and risk stratification product that had been concepted during a global hackathon. Design worked quickly and concurrently with the development team, data scientists, and the CEO create a simple, easily scalable product, while conducting constant research in a variety of ways including news stories, science reports, competitive analysis, and weekly video interviews and testing with hospital staff at various levels.

I took the lead developing personas based on individual experiences and news articles covering the same individuals. Expanding those into in-depth series of journey maps, we were able to see where the app would deliver the most value to different categories of users. A value proposition was clarified, experience visualizations were created to gain clarity and differing viewpoints, all while iterating a minimized version of the app. Consistently zooming in to details and zooming out to wider research became a pattern I established to ensure we remained relavant and focused.

Stakeholder interviews reinforced some assumptions while uncovering other areas to focus on, ultimately leading to a simpler solution for a narrowed user set. Regular usability sessions were conducted over video as the apps iterations moved forward.

In a few short months, the team delivered an app for hospital staff that paired with AI anonymized voice sensors and a personal sensor for each staff member. This app paired with a responsive dashboard for a variety of senior hospital staff to assess, monitor, and manage covid within their own staff. The app allowed instant contact tracing with all other staff members within a given amount of time within an infection, paired with risk stratification for those most at risk based on proximity, time, direction of speaking, and voice volume, and allowed a variety of quick-contact response options to reach out to potentially affected high-risk staff; cutting down days of manual work to under a minute, while increasing the accuracy.
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