Improving symptom-tracking experience for accurate diagnosis
Improving symptom-tracking experience for accurate diagnosis
Details have been anonymized due to NDA.
Details have been anonymized due to NDA.
Timeline
Timeline
Phase 1 (2024): Research & Strategy
Phase 2 (2025):
UI Refinement
Phase 1 (2024): Research & Strategy
Phase 2 (2025):
UI Refinement
Role
Role
UX Researcher
Product Designer
UX Researcher
Product Designer
Summary
Summary
Patients with gut health issues track symptoms on paper diaries, an unstructured format that limits diagnostic accuracy. I led cross-functional alignment between leadership and clinical teams to design a digital symptom-tracking system built for long-term patient compliance and clinical utility.
Patients with gut health issues track symptoms on paper diaries, an unstructured format that limits diagnostic accuracy. I led cross-functional alignment between leadership and clinical teams to design a digital symptom-tracking system built for long-term patient compliance and clinical utility.
Impact
Impact
Contributed to user research repository
Created prototypes and reusable interview templates ready for testing
Contributed to user research repository
Created prototypes and reusable interview templates ready for testing
PROBLEM AREA
PROBLEM AREA
"Your tests came back fine," but you still feel something is off.
"Your tests came back fine," but you still feel something is off.
Diagnosis relies on patient-reported data, but insights are hard to filter.
Patients suffering from functional gut disorders often feel unheard. They can appear healthy in clinical tests and still experience symptoms in daily life. To bridge this gap, clinicians rely on patient reported soft-data to treat undiagnosed symptoms.
The current tool for capturing this context is a paper diary. However, feedback from clinicians revealed that the system involved logistic issues:
Diagnosis relies on patient-reported data, but insights are hard to filter.
Patients suffering from functional gut disorders often feel unheard. They can appear healthy in clinical tests and still experience symptoms in daily life. To bridge this gap, clinicians rely on patient reported soft-data to treat undiagnosed symptoms.
The current tool for capturing this context is a paper diary. However, feedback from clinicians revealed that the system involved logistic issues:
01 Patient records diary
Paper diary is messy and hard to keep track of.
01 Patient records diary
Paper diary is messy and hard to keep track of.
02 Nurse files diary
The nurse struggles to transcribe and file the data in their busy workflow.
02 Nurse files diary
The nurse struggles to transcribe and file the data in their busy workflow.
03 Doctor reviews diary
Extra effort to relate the poor quality data to the clinical test.
03 Doctor reviews diary
Extra effort to relate the poor quality data to the clinical test.
hypothesis
hypothesis
Will digitizing the diary close the gap?
Will digitizing the diary close the gap?
As a result, the clinicians we interviewed requested a digital app to complement the paper diary, initially targeting the more tech-savvy patient group.
To align this product request with the business goals, I lead the discovery phase:
Competitive Analysis: Patient soft-data is a key leverage for reimbursement.
Interview protocols: Customizable templates structured to uncover “what” the clinician needs in terms of the specific data hierarchy.
As a result, the clinicians we interviewed requested a digital app to complement the paper diary, initially targeting the more tech-savvy patient group.
To align this product request with the business goals, I lead the discovery phase:
Competitive Analysis: Patient soft-data is a key leverage for reimbursement.
Interview protocols: Customizable templates structured to uncover “what” the clinician needs in terms of the specific data hierarchy.
MVP DESIGN
MVP DESIGN
MVP Exploration: Capture the most valuable data with a few simple taps.
MVP Exploration: Capture the most valuable data with a few simple taps.
To address the challenge, I developed an initial design concept focused on capturing the most clinically valuable data with minimal effort.
To address the challenge, I developed an initial design concept focused on capturing the most clinically valuable data with minimal effort.
To address the challenge, I developed an initial design concept focused on capturing the most clinically valuable data with minimal effort.
BEFORE
BEFORE
Entry is loosely structured
Entry is unstructured
Entry is loosely structured
Paper may be lost
Paper may be lost
Clinicians can’t quickly identify patterns
Clinicians can’t quickly identify patterns
AFTER
AFTER
Labelled insights
Labelled insights
Accessible data system
Accessible data system
Data is preserved from the point the patient records
Data is preserved from the point the patient records
I started the design with 4 high-signal categories, built as a modular framework. Patients simply tap and record through guided entry, and doctors can spot a diagnostic pattern within 60 seconds. The categories are designed to be replaced with validated data once usability testing confirms patients' mental models and clinicians' diagnostic priorities.
I started the design with 4 high-signal categories, built as a modular framework. Patients simply tap and record through guided entry, and doctors can spot a diagnostic pattern within 60 seconds. The categories are designed to be replaced with validated data once usability testing confirms patients' mental models and clinicians' diagnostic priorities.
I started the design with 4 high-signal categories, built as a modular framework. Patients simply tap and record through guided entry, and doctors can spot a diagnostic pattern within 60 seconds. The categories are designed to be replaced with validated data once usability testing confirms patients' mental models and clinicians' diagnostic priorities.
Check-in
Track
Insights
Check-in
Recording symptoms and bowel movement
Recording symptoms and bowel movement
Log events with a few simple taps.
4-Category framework
4-Category framework
Focused guidance on relevant insights.
Focused guidance on relevant insights.
Automatic timestamp
Automatic timestamp
Staying on track without manually checking and writing it down.
Staying on track without manually checking and writing it down.
Labelled entry
Labelled entry
Group insights at a glance.
Group insights at a glance.
View insights with pre-identified patterns.
Timeline
Timeline
Time is the key for diagnosis. This allows doctors to read the latency between events and make decisions.
Time is the key for diagnosis. This allows doctors to read the latency between events and make decisions.
Tagged events for attention
Tagged events for attention
System detects the relationships between events and generates tags.
System detects the relationships between events and generates tags.
Insights
Viewing insights shown in a timeline
Viewing insights shown in a timeline
DESIGN CHANGE
DESIGN CHANGE
Dashboard Alternatives: filtering noise at entry point
Dashboard Alternatives: filtering noise at entry point
The first screen a user sees determines their long-term compliance. I explored three iterations to balance feature requests with clinical clarity:
The first screen a user sees determines their long-term compliance. I explored three iterations to balance feature requests with clinical clarity:
V1
V1
The Minimalist
The Minimalist
No clear hierarchy
No clear hierarchy
Minimal primary navigation
Minimal primary navigation
V2
The Full-fledged
It’s got all the feature requests
It’s got all the feature requests
But! While commonly used among successful competitors, it does not reduce the noise for clinicians
But! While commonly used among successful competitors, it does not reduce the noise for clinicians
Complicated navigation
Complicated navigation
V3
1-tap logging
Guides the user towards focused categories
Guides the user towards focused categories
Minimal primary navigation
Minimal primary navigation
ACCESSIBILITY
ACCESSIBILITY
Accessibility and WCAG considerations
Accessibility and WCAG considerations
Accessibility was evaluated against WCAG 2.1 Level AA standards, with particular attention to the constraints of a medical context, where clear, unambiguous communication directly affects patient confidence and safety. These have been flagged for aria-label additions at the development handoff stage:
Accessibility was evaluated against WCAG 2.1 Level AA standards, with particular attention to the constraints of a medical context, where clear, unambiguous communication directly affects patient confidence and safety. These have been flagged for aria-label additions at the development handoff stage:
BEFORE
AFTER
Color & contrast
Time labels and Type badges were adjusted to meet the 4.5:1 contrast minimum. Also reduced red to reserve the color exclusively for high-urgency alerts in clinical UI design.
Labelled interactive elements
Added text labels to Filter and Edit functions and flagged for aria-label additions.
Color & contrast
Time labels and Type badges were adjusted to meet the 4.5:1 contrast minimum. Also reduced red to reserve the color exclusively for high-urgency alerts in clinical UI design.
Labelled interactive elements
Added text labels to Filter and Edit functions and flagged for aria-label additions.
IMPACT
IMPACT
Unlocking a product roadmap
Unlocking a product roadmap
Built the research foundation: Documented templates for interviews and analysis, giving the team a reusable starting point for future clinical discovery projects.
From concept to prototype: Created prototypes ready for clinical validation, taking the project from an idea to something that could generate real feedback.
NEXT STEP
NEXT STEP
Validating the data hierarchy and correlation
Validating the data hierarchy and correlation
With the system architecture built, the next phase of discovery focuses on testing with clinicians to validate the most clinically relevant category types. I also want to explore correlating patient-reported events with clinical test data in real-time:
With the system architecture built, the next phase of discovery focuses on testing with clinicians to validate the most clinically relevant category types. I also want to explore correlating patient-reported events with clinical test data in real-time:
Potentially correlate the timeline of events with the clinical test in progress.
Potentially correlate the timeline of events with the clinical test in progress.
Potentially correlate the timeline of events with the clinical test in progress.
Learnings
Learnings
The biggest takeaway is to design for a multi-sided workflows. Patients needed simplicity to stay compliant; clinicians needed signal density to make decisions. By slowing down to map the tension, we build the system coherently without designing for one user at the expense of the other.
The biggest takeaway is to design for a multi-sided workflows. Patients needed simplicity to stay compliant; clinicians needed signal density to make decisions. By slowing down to map the tension, we build the system coherently without designing for one user at the expense of the other.