My Role
Tools
Duration
Team
UI/UX Design
Product Designer
Figma
Zoom
July 2024- Present
1 UX- Designer
1 Developer
1 UX researcher
Context
Mental health conditions are often underdiagnosed and poorly managed due to complex symptoms and limited monitoring capabilities. NanoMood addresses this challenge through AI-powered, continuous symptom assessment using multimodal data.
Problem
Mental health care lacks continuous monitoring tools, relying instead on periodic assessments that offer limited insight. This gap prevents personalized treatment and early risk detection.
Solutions
Developed an integrated system with two key components: a patient app for easy symptom tracking and visualization, and a physician dashboard with AI-powered tools for risk assessment and treatment planning.
Problem Statment
How might we transform mental health care by developing user-friendly technologies that capture comprehensive, multimodal symptom data?
Solution
Clinician Platform
.
- Comprehensive Patient Profiles: Centralized health data, activity trends, and mental health episodes.
- Data Visualization: Clear graphs for health trends, progress tracking, and medication insights.
- Personalized Care Tools: Risk assessments and action-driven insights for clinicians.
- Secure Multimodal Data Integration: Combines EMRs, wearables, and other inputs.
- Smart Scheduling & Notifications: Alerts for critical tasks with seamless appointment management and updates.
- At-a-Glance Overview: Centralized dashboard for managing all patients efficiently.
- Sortable Tables & Filters: Organize data by admission status, symptom scores, or medication needs.
- Search & Sort Functionality: Quickly identify and focus on high-risk patients.
- Visual Aids: Pie charts provide a snapshot of patient statuses.
- Comprehensive Mental Health Summary: Includes score summary of assessments like PHQ-9, GAD-7, and PCL-5.
- Progress Tracking: Highlights improvements or deteriorations in patient condition.
- Visualized Trends: Clear graphs of questionnaire responses and overall scores.
- Efficient Documentation: Quickly document patient conditions with structured note templates.
- Auto-Generated Notes: Full-sentence notes created from selected problems and symptoms.
- Customizable Insights: Space for additional inputs or instructions.
Patient Mobile Application
Seamless Onboarding: Quick and intuitive entry into the platform with easy access options.
Multimodal Data Integration: Combines EHRs, wearables, and user inputs for a holistic view
Integrated Health Data: Access to health details, insurance cards, and medical history.
Easy Data Visualization: Clear analytics and metrics for patients to track health trends.
Analystics Calculation Tagging of events to calculate analytics such as sleep, stress
Detailed Analytics Interpretation: Provides insights into each metric, such as stress, with trend analysis.
Chatbot Assistance: Provides real-time answers to user questions about tracked data or app functionality.
Data Insights: Helps users access updates and insights from their tracked data instantly.
24/7 Support: Ensures constant availability for guidance and troubleshooting.
User Research
To lay the foundation for the redesign of NanoMood’s patient and physician platforms, we began with an in-depth user research phase. This included a comprehensive competitive analysis and a thorough audit of the existing design. These steps were crucial in identifying gaps, understanding the industry standards, and aligning the platform’s redesign with user needs and expectations.
Competitive Analysis
We analyzed several leading platforms in the mental health and neuropsychiatric space to benchmark best practices and uncover opportunities for differentiation. The analysis focused on:
Usability: How well competitors facilitated real-time data input, monitoring, and reporting for users and healthcare professionals.
Features: Identifying standard and innovative features offered by competitors, such as multimodal data integration, AI-driven insights, and risk stratification tools.
Visual Appeal: Comparing visual design styles to evaluate trends, clarity, and how effectively they conveyed complex health information.
User Engagement: Studying techniques competitors used to retain user engagement, such as reminders, gamification, or personalized content.
Previous Application Design Audit
- For Patients:
- The interface lacked clarity and consistency, making it less engaging and harder to navigate.
- Inputting multimodal data was cumbersome, leading to frustration and reduced user adherence.
- Visual feedback on symptom trends was minimal, leaving users with little actionable insight.
- For Physicians:
- The platform provided a fragmented view of patient data, making it difficult to interpret trends or prioritize care.
- Limited support for risk stratification and treatment planning hindered timely and effective decision-making.
- The overall design felt outdated and visually cluttered, detracting from usability and professional trust.
Findings
Based on the research insights, I established four success criteria to evaluate whether the final designs effectively address the identified problems.
- Clarity and Understanding
- Is the multimodal nature of the app easy for patients to comprehend?
- Are the data visualizations clear, concise, and intuitive for all users?
- Can patients easily understand how to tag their data, ensuring accurate symptom tracking?
- Clinician Usability
- Can clinicians view all patient data in a visually clear and organized manner?
- Is the "All Patients" dashboard easy to navigate and sort through based on key priorities, such as risk level or admission needs?
- Does the platform enable clinicians to quickly interpret a concise summary of mental health questionnaires for better decision-making?
- Patient Engagement and Accessibility
- Are patients able to engage with the platform effortlessly, with clear workflows for data input and symptom monitoring?
- Does the system provide actionable insights and personalized feedback that patients can easily understand and act on?
- Effectiveness of Summaries and Insights
- Are the summaries of patient data, such as trends, risk scores, and activity, presented in a way that is easy to interpret for clinicians?
- Does the app support seamless communication and understanding between patients and clinicians through well-structured data and visual elements?
To refine the NanoMood platform, we conducted thorough user testing and iterative design, leveraging diverse feedback. Weekly meetings with founders and team members addressed pain points and aligned the design with strategic goals, guided by user research findings. This process improved multimodal data clarity, dashboard usability, and mental health summary comprehension. Presenting prototypes at industry events and gathering expert feedback further refined workflows, data visualization, and user experiences. Each iteration was rigorously tested against success criteria, ensuring a user-centered design that effectively bridges mental health challenges with innovative solutions.
Before
After
We initially designed the onboarding process with three separate screens to collect basic health information. However, during user testing, we received feedback that this approach was too time-consuming and made the onboarding process feel unnecessarily lengthy. To address this, we streamlined the experience by consolidating all the health information questions into a single, simplified screen.
Reflection
Working on NanoMood's platform in a startup environment was an enriching experience that taught me the value of designing an MVP by balancing simplicity, functionality, and feasibility within tight timelines. Collaborating with a multidisciplinary team, including developers, machine learning experts, and user researchers, allowed me to align technical constraints, data-driven insights, and user needs into a cohesive product. The iterative process, driven by continuous feedback loops, ensured that the platform remained user-centered while leveraging cutting-edge AI capabilities. This experience emphasized the importance of cross-team collaboration, adaptability, and clear communication in creating impactful solutions for complex challenges like mental health care.
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