Build
A focus app that rewards going offline with a world that grows the more you disconnect
Screentime Management
Timeline
7 Weeks (Oct 27 - Dec 11 2025)
Role
Tools
Overview
Parameter is a patient-facing genetic health app designed to reduce health data fragmentation. By centralizing daily health metrics, wearable signals, and medical reports into a single experience, Parameter helps people understand how their data connects over time and what it means for their health.
Design Challenge
How might we design a trusted experience that turns fragmented health data into clear, actionable guidance?
Problem Space
Managing your health shouldn't feel like a second job
What's happening today
People have more access to their health data than ever, from wearables, labs, and provider portals. But that data lives across disconnected platforms, often filled with medical jargon and numbers without context. Patients are left to connect the dots themselves, turning scattered information into decisions without clear guidance.
50%
of adults had health records spread across more than one portal or provider type
Solution
From raw metrics to understandable, personalized guidance
How the experience works
Parameter is designed around four connected moments: personalised dashboard, health information in plain language, AI integration, and data aggregation. Together these layers reduce cognitive load, improve comprehension, and help users translate information into practical next steps.
Key Screens
From raw metrics to understandable, personalized guidance
How the experience works
Parameter is designed around four connected moments: personalised dashboard, health information in plain language, AI integration, and data aggregation. Together these layers reduce cognitive load, improve comprehension, and help users translate information into practical next steps.
Key Feature 1
Customizable metrics dashboard
No two patients track the same things. Someone managing diabetes cares about blood glucose first. Someone with a heart condition checks resting heart rate. Parameter lets users pin exactly what matters to them, so the first screen they see every day is built around their condition and goals, not a generic overview designed for everyone and useful to no one.
Key Feature 2
Contextual AI health assistant
The AI assistant is a single hub that branches into whatever you need: interpreting a lab result, spotting a trend in your data, preparing for an upcoming appointment, or learning what a genetic predisposition actually means for your daily life. It is framed as educational, not diagnostic, and the interface makes that boundary clear.
Key Feature 3
Reports, labs, and metrics in one view
Most people piece their health picture together from a patient portal, a wearable app, a separate lab results site, and a folder of paper documents. Parameter pulls all of it into a single organized view: reports, lab results, and daily health metrics side by side.
Key Feature 4
Plain-language results and FAQ
Lab values, genetic risk factors, and health metrics are presented with plain-language descriptions, color-coded range indicators, and an FAQ section for deeper context. Instead of showing a number and leaving you to Google it, Parameter tells you what the number means, what range is healthy, and what might be affecting it.
User Interviews
Health data is everywhere, but understanding it is not
Who I talked to
To better understand the gap between how health information is currently managed and how it could be, I conducted interviews with 7 participants: 5 patients managing a range of conditions including diabetes, glaucoma, and bipolar disorder, and 2 medical professionals. Participants were selected to reflect a range of relationships with digital health tools, including those who relied on them regularly and those who avoided them entirely.
The research focused on:
How patients currently track and manage their medical information across different tools and systems
Where digital health tools fall short in supporting that process
What barriers exist between patients and doctors when it comes to accessing and communicating health information
1.0 Current devices show the data, but users are left to carry the cognitive load.
Key Insights
Too many tools, too little clarity, and a gap between patients and their doctors
Health data is fragmented and manually managed
"I use an Excel sheet, keep paper documents in a folder, or jot things down in my Notes app."
Most patients only engage with their data reactively
"I only look at my health data when something feels wrong or I have an appointment coming up."
Difficulty understanding health information
"I can see my results, but I don't really know what they mean or what I should do next."
Trust, usability, and privacy concerns
"I don't use most health apps because they feel confusing, and I'm not sure who can see my data."
Competitive Research
Today’s tools are improving, but still fragmented for patients.
Competitive takeaway
Across wearables, portals, and consumer health apps, we observed strong point solutions but weak continuity. Each tool solves part of the journey, yet users still have to assemble the full story themselves. Parameter positions itself as the connective layer between these isolated moments.
Key Insight 1
Organization doesn't equal understanding
Apps structure data by record type or metric, but this prioritizes storage logic over how users actually navigate and make sense of their health information.
Key Insight 2
Numbers without context
Most apps display charts and values without explaining healthy ranges or what influences changes, making it difficult for users to interpret their own data without medical knowledge.
Key Insight 3
Information overload without clarity
Without guidance on what a result means or what to do next, users are left to interpret clinical information on their own, creating confusion and disengagement.
1.0 Current devices show the data, but users are left to carry the cognitive load.
1.0 Current devices show the data, but users are left to carry the cognitive load.
Ideation & Testing
Translating complex healthcare constraints into a usable product flow
Competitive takeaway
Across wearables, portals, and consumer health apps, we observed strong point solutions but weak continuity. Each tool solves part of the journey, yet users still have to assemble the full story themselves. Parameter positions itself as the connective layer between these isolated moments.
Reflection
Key takeaway
Designing Parameter reinforced that trust in health products comes from clarity, not just capability. The most valuable shift in this project was moving from “showing more data” to “supporting better decisions.” It also sharpened my approach to information architecture in sensitive domains where language, hierarchy, and timing directly impact confidence.
Next Steps
Paths for further development
01
Clinical Validation
Evaluate recommendation quality with clinicians and domain experts to improve medical reliability and safety.
02
Personalization Engine
Expand adaptive models that learn from user behavior, preferences, and history to make guidance more relevant over time.
03
Data Partnerships
Integrate directly with additional labs, providers, and wearable ecosystems to reduce manual upload friction.
04
Longitudinal Testing
Run longitudinal pilots to measure comprehension, confidence, and behavior change across longer care cycles.