Cura

Overview

Process

From research on who gets left out of trials to an app concept, then a small pilot test.

1. 1 Research

   Start With Who Gets Left Out.

   Our secondary research looked at trust, representation, geography, cost and how people are recruited. Three numbers shaped the project:

   • 67%

     of FDA-reported medical device injuries or deaths involved women, because devices are often designed around male bodies.

   • 40.8M

     adults in the U.S. (12.5%) live in clinical trial “deserts,” far from the hospitals that run trials.

   • 39% vs 5.7%

     enrollment when community advisory members help recruit, compared with recruitment without them.

2. 2 Synthesis

   Four Groups, Three Insights.

   I sorted every finding into an affinity diagram with four groups: minority patients, non-minority patients, hospitals and staff, and external groups like community leaders and AI tools. Three insights came out of it.

   1. Patients & communities

      Trust

      Key insight

      Mistrust runs deep, from the Tuskegee study to pain being dismissed. People trust other people, not portals: community peers raise enrollment from 5.7% to 39%.

   2. Barriers

      Access

      Key insight

      Cost, distance and language decide who can join. Travel costs and lost wages, trial deserts and language barriers keep eligible people out.

   3. Hospitals / Staff

      Family

      Key insight

      Health decisions are made with family, but recruitment ignores that. People need plain-language information they can share before deciding.

   4. Bias in care

      Devices and tests are built around male, lighter-skinned bodies: pulse oximeters misread darker skin.

   5. Staff

      Dedicated trial staff recruit best, but often lack training to reach minority communities.

   6. Technology

      AI cut recruitment time by 42% and found 35% more underrepresented eligible patients.

   Overall Objective

   How might we reduce cultural friction and socio-economic barriers so the clinical trial process is safe, easy to understand and welcoming, to increase engagement from people of color?

3. 3 Exploration

   Compare Four Ideas, Pick One.

   We explored ideas for patients, families and doctors before choosing the one that could reach the most people without needing more staff.

   1. Physician Training App

      Simulations and real patient stories to build doctors’ empathy and trust with patients.

   2. Family Consent Workshop

      Community-led sessions that explain trials to whole families, with peer facilitators.

   3. 60-Second Explainers

      Short, multilingual videos that cut the jargon and anxiety around trials.

   4. Chosen

      Trial Match & Readiness App

      Matches people to trials in plain language, with family sharing and explainers built in.

4. 4 Design

   Four Tabs, Plain Language.

   We built the app’s structure from scratch around four tabs. Home shows upcoming trials, 60-second videos and a map of what’s nearby. Search filters across videos, trials and articles. Library keeps everything you’ve saved, and Profile holds your trials and personal information.

   Navigation

   1. Home
      • Trials
      • 60s videos
      • Map
   2. Search
      • Filter
      • Videos
      • Trials
      • Articles
   3. Library
      • Saved
      • Videos
      • Trials
      • Articles
   4. Profile
      • Past trials
      • Completed videos
      • Personal info

5. 5 Testing

   Test the Video and the App.

   We ran a small pilot with three students on campus, so the results aren’t representative of real trial participants. We tested how they responded to a short explainer video and how easily they could find information in the app.

   • 2 of 3

     were more willing to take part in a trial after watching the 60-second video.

   • 2 of 3

     found the screens easy to navigate.

   • Once a month

     is how often two of them check a healthcare portal, so the app can’t rely on daily use.

Final Design

The finished app: a home for upcoming trials, search across trials and learning, and a profile to track it all.

Screen 1 of 3