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Breast Cancer Experience Daily Log
A conversational, low-burden logging experience that turns qualitative patient experiences into longitudinal insight.
Overview
Patients struggled to identify patterns across symptoms and treatment effects. I designed a conversational daily log that reduces manual burden and structures freeform entries into analyzable, trend-friendly data — without crossing into medical advice.
Problem / Opportunity
What was broken (or missing), and why it mattered.
Existing tools required manual entry and didn’t match patient capacity during fatigue and stress.
Patients wanted clarity and patterns, not raw logging.
The experience needed to support observation without diagnosis or treatment recommendations.
My role
Explicit ownership and responsibilities.
- Product strategy + discovery
- User experience definition
- Conversational interaction planning
- AI workflow design
- Data structuring concepts
- Stakeholder communication
- Product positioning
Process / Approach
Where the strategy, structure, governance, and tradeoffs live.
- 1) Community signal discovery
Identified recurring behavioral patterns and unmet needs in community discussions to ground the experience in real user context.
- 2) Conversational log flow
Defined natural-language logging rather than rigid forms to reduce friction during treatment and recovery periods.
- 3) AI-assisted structuring
Planned transformation of freeform entries into structured fields suitable for longitudinal analysis.
- 4) Trend detection design
Outlined how changes over time could be surfaced as patterns, summaries, and “what’s different this week” insights.
- 5) Safety framing + guardrails
Built language and boundaries that emphasize observation and understanding, not clinical interpretation.
Prioritized user burden reduction first; structured outputs are only valuable if capture is sustainable.
Designed guardrails to prevent medical advice while still supporting reflective insight and self-advocacy conversations.
Visual systems diagrams
Placeholders for architecture maps, flows, governance models, and lifecycle diagrams.
A lightweight daily loop: capture → structure → summarize → trend surfaces.
Technology
Tools and systems involved.
- Conversational AI systems
- AI-assisted data structuring
- Product workflow design
- Figma
- Product documentation
- Research synthesis
- Community insight analysis
Outcome / Impact
The organizational and product-level effect.
- Created a scalable concept for longitudinal patient experience tracking
- Reduced friction vs traditional symptom logging tools
- Aligned product design to real patient behavioral needs
- Established a framework for structuring qualitative experiences without increasing burden
Start with an AI Ops audit to identify high-ROI workflows, governance needs, and a pragmatic 30/60/90-day plan.