Discovery
To understand the frustration behind the "data dump," I interviewed 4 users across different life stages. I discovered that the problem wasn't a lack of data—it was a lack of relevance.
Finding 1
Users felt buried by a dashboard that mixed years of irrelevant history with current needs. They wanted segmented spaces (e.g., a "Diabetes Space") to stay focused on specific goals.
I get lost in years of old data. Most of it is irrelevant now. I just want a place where I can stay focused on the conditions I'm actually managing today.
-Middle aged user with multiple conditions
Finding 2
Users felt the app was too passive. They wanted the app to actively check in, recognize their progress, and support them throughout their journey.
I wish the app felt more like my health guide—like it knew what I’m working on and helped me track it, not just throw info at me.
-Expecting mother
In a collaborative ideation session, we explored several ideas to organize the data, but each one created new friction points for the user:
Early ideas
Separate Niche Apps: Creating a different app for every condition (e.g., Pregnancy vs. Heart Health).
Deep Folder Menus: A traditional nested hierarchy for all medical records.
Manual Tagging: Letting users categorize their own lab results.
Started from sketches
Tradeoff
One Unified App vs. Specialized Niche Apps
Initially, we debated if we should launch separate apps for different specialties (e.g., a dedicated Pregnancy app vs. a Heart Health app).
The Conflict: Specialized apps offer a tailored experience but fragment the user’s data.
The Decision: I advocated for a single, unified ecosystem. Since many patients manage multiple conditions at once, jumping between separate apps would fragment their data and their care. We chose Modular Journeys inside one app to provide a specialized experience without losing the "big picture" of a user's total health.
Solutions
The Problem: Information Overload. Critical medical alerts were "buried" under years of medical data.
The Fix: I created dedicated "Journeys" that isolate data. Whether it's a pregnancy or a lifelong asthma, the UI only surfaces milestones and alerts relevant to that specific journey.
Dedicated space for any health Journey, such as pregnancy.
The Problem: Lab reports filled with medical jargon like FEV1, HbA1c, or SpO₂ create anxiety for users at any point in their health journey.
The Fix: I introduced a proactive AI Assistant that translates complex medical trends into intuitive, human-readable insights. To further support the user journey, I designed an integrated Chatbot that allows for 24/7 plain-language health queries, like an intelligent health companion.
Converts complex clinical metrics into clear, human-level language.
Usability test
I ran usability testing with 6 participants to evaluate the high-fidelity prototypes and understand their trust in the new AI model.
Our goals for the testing were to:
Discoverability: Can users naturally find "Journeys" within their existing dashboard?
Flow Efficiency: Does the "Propose & Confirm" model feel like a shortcut or an interruption?
User Trust: Are users comfortable letting an algorithm handle their private health information?
Iterations
Users couldn't find their "Journeys." They were buried in a second-level menu, requiring too many clicks to access specific tracking like Pregnancy or Asthma.
I widened the left navigation to pull individual Journeys into the top level. This removed the "hidden" feeling and made their most important health data visible at a glance.
Setting up goals felt like "homework." Answering 10+ questions per goal was frustrating, causing many users to quit halfway through.
The solution
I replaced manual entry with AI-powered suggestions. The system now analyzes existing data to pre-fill answers and suggest relevant goals, , turning a 10-minute task into a 2-minute review.
Users were skeptical about AI handling sensitive medical data. They worried about privacy and accuracy. One user said:
The solution
To build trust, we introduced an onboarding transparency screen that explains exactly how data is used.
We added user control over what they share with AI, and they can stop sharing at any time.
Final results
After iterating, I ran a final validation round with 4 participants to ensure the new changes solved our initial friction points.
Trust Restored: The AI introduction screen and the user control successfully neutralized privacy concerns. Users reported feeling "more in control" of their data.
Seamless Navigation: All participants could instantly find their specific Journeys, describing the experience as "focused" and "easy to navigate."
The Empowerment Factor: Contrary to typical AI fears, users felt “more in control” of their condition because the AI-generated insights made their data actionable rather than overwhelming.
The Impact
Final solution
Personalized Onboarding
The Journey selection screen with AI curated Journeys prominently displayed at the top
The AI-Prefilled review screen to reduce onboarding fatigue
Guided Health Tracking & Insights
The Pregnancy Journey: One of many modular Journeys designed to support various life stages and health paths. Proactive AI insights translate complex health data into clear, human-level updates that matter most.
Health Trends: Long-term tracking of all health data related to the active journey.
Deep-Dive Body Insights: Detailed analysis and personalized action plans
Proactive AI Companion
Proactive Chat: Chatbot initiating a conversation about a health metric
Suggested Content: Chatbot suggests educational resource based on users' data
Mobile designs
