From Questions to Next Steps

Salud × Cedars-Sinai

User Research Service Design 2025

An AI-powered, community-centered cancer screening experience designed with and for underserved Latinx communities in Los Angeles.

Salud — From Questions to Next Steps
Role
UI Designer, UX Research, Physical Experience Designer
Team
Balinda, Lanna, Max, Sabrina
Duration
14 weeks, Spring 2025
Tools
Figma, Miro, Field Research
Methods
Co-design, Service Blueprint
Partner
Cedars-Sinai Medical Center

Help Latinx middle-aged and elderly adults aged 45–80 in Antelope Valley discover screening information they may not have heard before — empowering early detection and access within underserved communities.

AI Salud Station — full product overview

AI Salud Station — deployed at Ralphs, Antelope Valley, Spring 2025

Why this community, and why now

Antelope Valley is a community in northern Los Angeles County where 53% of residents identify as Latinx — one of the highest concentrations in the region. Cedars-Sinai's Cancer Research Center for Health Equity already had an active outreach program here, with trained Community Cancer Navigators working directly with residents. But despite this infrastructure, cancer screening rates remained low and mortality rates remained high.

Secondary Research — Why colorectal cancer
Colorectal screening gap
52% vs 73%
Immigrant vs US-born — the largest gap across all cancer types
Late-stage CRC rising
28% → 41%
Among Latinx aged 20–29, 2000–2016
Culturally tailored education
18% → 55%
Completed screening rate with Spanish-language community intervention
Primary research — navigator interviews
Primary Research — Navigator interviews

We interviewed Community Cancer Navigators with the Cedars-Sinai Antelope Valley program. What we found: the navigators themselves were the most trusted channel — but the materials they were given to deliver were working against them.

Insight
100% of participants identified lack of awareness — not lack of access — as the biggest barrier to cancer screening. Free, nearby services went unused simply because people didn't know they existed.

"There is a need for culturally tailored interventions to increase cancer awareness, education, cancer prevention, and access to early detection and screening."

— Antelope Valley Health Navigator, Cedars-Sinai
How Might We
How might we increase ethnic community awareness and understanding of cancer screening programs so that more people feel informed and motivated to take preventive action?

From research to service design

We mapped the full journey — from the moment someone hears about screening to when they leave with a summary ticket — to find where trust breaks down and where design could intervene.

Concept ideation — early sketches
Concept ideation — early sketches and explorations

Early concept sketches — exploring service touchpoints and interaction models

Community Cancer Navigator — the human at the center
Ralphs — a familiar, trusted community space
Why Ralphs
  • Cedars-Sinai already had navigator presence here
  • Familiar, low-pressure environment — not a clinic or government building
  • Highest-frequency community touchpoint — weekly routine for most families
User journey map
User journey map — 6 stages from awareness to action
Figma design process
Figma design process — survey UI components and design system

An AI station that educates, not diagnoses

AI Salud Station is a tablet kiosk introduced by a promotora at Ralphs. Our goal was not to tell people what to do — but to build understanding quickly, educate, and support early detection so people are more open to learning, more willing to ask questions, and more likely to consider taking action. Users take a 10-question survey and receive a personalized printed summary. No diagnosis. No judgment. Just a gentle next step.

My role — kiosk interaction flow, all 10 survey questions UI, per-question feedback design, privacy system, AI boundary definition, physical kiosk enclosure design

Experience walkthrough — full kiosk prototype demo

The Survey — 10 questions, designed by Lanna

Each of the 10 survey questions was designed to feel like a conversation, not a clinical assessment. I designed the UI for all 10 screens and the per-question AI feedback that appears after each answer — giving users a moment of gentle acknowledgment before moving forward.

Design decisions — privacy system, designed by Lanna
Welcome screen showing privacy statement
Privacy communicated upfront

The welcome screen states our privacy stance before users begin — in plain language, in both English and Spanish. Trust is established before a single question is asked.

Contact opt-in screen with skip option
Contact is always opt-in

The contact screen appears only after the survey ends, with a visible Skip option and an unchecked checkbox — consent is never assumed.

CTA screen offering health navigator connection
A human option, always available

A clear call-to-action allows users to connect with a health navigator for questions or next steps — without requiring additional data sharing or digital follow-up.

AI output contains no personal data

The printed and electronic summaries include no identifiable information. All recommendations are based only on user responses, not stored records.

AI Boundary — by design
AI is used for one thing only: generating a personalized summary ticket based on your survey answers. It does not diagnose. It does not evaluate risk. It does not give medical advice.

This boundary was a deliberate design decision — not a technical limitation. In a community where mistrust of AI is high, clarity about what AI can and cannot do is itself a trust-building act. The ticket contains three things: your next gentle step, one screening fact relevant to you, and nearby Cedars-Sinai resources. Nothing more.

AI does not
Diagnose conditions
Assess your health risk
Store your personal information
Make medical recommendations
AI does
Personalize your summary ticket
Surface a relevant screening fact
Suggest one gentle next step
Connect you to local Cedars-Sinai resources

What we built, what we left behind

The most important lesson: effective health design requires meeting people in their existing networks of trust, not building new ones. The promotora is not a workaround — she is the system.

Physical deliverables — tote bag, keychain, mirror, cookie, kiosk enclosure

Physical touchpoints — tote bag, keychain, mirror, cookie, summary ticket, iPad kiosk enclosure