A mobile application designed for family caregivers to streamline patient health tracking, enhance communication with healthcare providers, and prevent caregiver burnout through better care coordination.
Timeline & Status
3 Months, Shipped in January 2025
Team
1 Principal researcher
1 PM
1 Front-end developer
1 AI Engineer
1 Design lead (me)
Platform
Mobile application
My Role
UX Lead
Contribution
Primary research
Concept ideation
Prototyping
User Flows
High-fidelity designs
Overview
Family caregivers are often overwhelmed—juggling daily tasks, emotional strain, and fragmented health records without proper tools or support.
I led the design of CarePilot’s MVP, a mobile-first AI assistant that helps caregivers log wellness data, coordinate care tasks, and retrieve insights through natural language.
The resulting prototype reduced cognitive load, enabled faster journaling, and laid the groundwork for collaborative, data-driven caregiving within families.
As the Solo UX Designer on the team, I led the end-to-end design of the experience from discovery to delivery. I worked closely with the Product Manager to set goals for the MVP and the vision for the next iteration. Additionally, I collaborated with the researcher, developer and AI engineer in the company for research and ideation workshops.
Family caregivers often experience a state of physical, emotional, and mental exhaustion known as caregiver burnout.
22 hours
Time spent per week on caregiving tasks
Family caregivers juggle full-time jobs, family responsibilities, and personal lives—while also taking on the added commitment of caregiving.
40 million +
Family caregivers in the United States
In the United States alone, over 40 million people provide unpaid care to family members aged 50 or older.
41%
Caregivers who report low overall well-being
Around 47% of family caregivers have reported increased anxiety, depression, or other mental health issues in the past year.
29%
Disruption to work schedules and career
One in five caregivers has taken a leave of absence and/or accepted a demotion to accommodate caregiving duties
Caregiving often feels like a second job—one that most aren’t prepared for. Caregivers must juggle multiple roles and responsibilities, often all at once, with little guidance or support.
Problem context
The message was loud and clear
A quick dive into online communities revealed common struggles among caregivers: Information overload, lack of support and the emotional stress of watching the decline of a loved one were the biggest causes of burnout.
A Reddit User
r/AgingParents
How do you deal with your own stress/mental health helping your aging parents?
50
A Reddit User
r/AITAH
AITAH for telling my significant other that i'm done taking care of her mother after 12 years and just wanna have some fun in our life
1.1K
A Reddit User
r/CaregiverSupport
I've been caregiving for my son for years. I'm disabled and retired now. This country survives on unpaid labor like ours.
49
“
You stop being a daughter, a spouse, or a friend. You become a nurse, a financial manager, and a grief counselor overnight
The Caregiver Space
“
Caregiving can feel lonely - even when you’re surrounded by people. No one really talks about how isolating caregiving can feel.
Medium
A Reddit User
r/Millenials
Older Millennials who may soon face the prospect of caring for older parents with dementia or who are incapacitated, are you dreading the next ten years of your life yet?
419
Solution Overview
An AI assistant that eases patient management with quick journaling, rapid information recall, and seamless provider communication.
Click to try out prototypes
Tracking daily activities of the patient
Current tracking methods are fragmented and manual, making it difficult to maintain a centralized record and retrieve accurate, timely information.
Coordination among multiple caregivers
Multiple caregivers in the same family have different tracking styles and communication needs, making consistent tracking challenging.
Miscommunication with healthcare providers
Caregivers often struggle to relay critical patient information to doctors without structured records or a quick way to retrieve past health data.
Monitoring long-term patient health trends
Caregivers lack tools to visualize changes in mood, symptoms, and treatment effectiveness, making it hard to spot key patterns over time.
Through preliminary research, I identified a few recurring problems that caregivers routinely face.
Many products focus on patient care, not caregiver wellbeing
No product provides holistic tracking of patient health over time
Existing products don’t support multiple caregivers well
What are the biggest pain points caregivers face?
How do caregivers navigate daily obstacles
How can technology best aid in managing a patient’s Activities of Daily Living (ADLs)
What are the biggest stressors for high-intensity caregivers?
How do caregivers currently share responsibilities, and what’s missing?
Data I already had
(Market Research & Competitor Analysis)
Data I needed
(User Pain Points & Product Opportunities)
The project was in its early stages, requiring open-ended discovery to understand the problem space better.
Being new to the caregiving space, I partnered with a UX researcher to interview 20 family caregivers, exploring their biggest challenges and how they use technology.
Research
How might we assist caregivers in managing the daily activities of patients so that they can accurately track and communicate patient outcomes to healthcare providers?
Project scope
User need
Tracking daily activities
Communication with healthcare providers
Monitoring long-term patient health
Coordination among multiple caregivers
Pain point
The process is manual and time consuming.
Limited time to record and recall medical advice.
Difficult to identify patterns as data is scattered.
Different caregivers have different tracking methods.
Difficulty in sharing patient-related updates/info.
Missing critical medical details at appointments.
Unstructured information makes retrieval difficult.
Design opportunity
Reduce time and effort required to log daily activities and record medical advice in real-time.
Categorise information to help with quick and relevant information retrieval.
Create relevant summaries of patient during doctor visits.
Analyse trends from daily activities over time.
Allow multiple caregivers to access and update patient records in real time.
I proposed several features for the first release of the product, with the goal of prototyping each of them, testing with users and gathering feedback.
I collaborated with the researcher, developers and PM in a
brainstorming workshop to distill research insights, explore technology-driven solutions, and assess technical feasibility.
Ideation
3 clicks
Key features should be accessible within 3 clicks
Lightning-fast entry and retrieval
User should be able to input data within 10s
Product-lifestyle fit
Natural interactions that do not require training
North Star design principles:
Mind map
A mind map that visually articulates the patient’s entire care ecosystem including medications, symptoms, doctors etc.
Pushed to next iteration
Why?
This feature was pushed due to limitations in the backend knowledge graph, which produced trivial insights for the mind map. More backend testing was required.
Trend analysis
The trend analysis feature that would provide caregivers with data-driven insights into a patient’s health over time.
Pushed to next iteration
Why?
Although trend analysis is a core feature, additional testing was needed to refine LLM output. Due to time constraints, it couldn't be included in the initial launch.
Caregiver check-in
A feature enabling caregivers to log their own daily mental health status and track their burnout levels over time.
Feature scrapped
Why?
This feature emerged from a team brainstorming session but lacked research backing. It was ultimately scrapped as it strayed too far from the product's core value proposition.
This process helped us refine the feature list for the MVP. Some of the features I prototyped were scrapped, mainly due to technical constraints.
I had a lot of feature ideas, so I quickly prototyped key functionalities and collaborated with developers to assess technical feasibility.
Rejected features
Notebook
Daily activities, notes from doctor appointments
Calendar / Alarms
Scheduling, track doctor appointments
Pill Organizers
Medication management
Filing System
Storage of test reports, medical history
Most caregivers rely on inefficient and fragmented methods involving both physical and digital tools in order to store information, track daily activities, manage medicines and maintain schedules.
Current (lack of) user flow followed by caregivers
Currently, the caregiving experience is ad hoc and lacks a defined workflow. The proposed solution brings more structure to the experience.
Overall Flow
Caregiver Profile
Caregiver time budget
Dashboard overview
Patient Profile
Journal
Chatbot
Chatbot Query
Journal Entry
Creating these flows allowed my team and me to take a macro view of the system, helping us identify and address potential gaps.
To visualise how each feature integrates into the system, I created user flows for both individual features and the overall experience.
Proposed user flow
Final solution
An AI assistant that eases patient management with quick journaling, rapid information recall, and seamless provider communication.
monitoring caregiver burnout
A feature that allows caregivers to track their mental well-being over time, by tracking the time spent on different types of caregiving tasks.
Pain points addressed:
Coordination among multiple caregivers
Chatbot for rapid information recall
A conversational assistant that allows caregivers to quickly retrieve important patient information, upcoming appointments, or medication details through natural language queries, thereby aiding in communication with medical providers.
journaling and insight generation
A feature that enables caregivers to easily log daily patient-related updates and automatically generates meaningful insights, helping them identify health trends and communicate more effectively with healthcare providers.
Pain points addressed:
Tracking daily activities of the patient
Monitoring long-term patient health trends
Coordination among multiple caregivers
Pain points addressed:
Tracking daily activities of the patient
Monitoring long-term patient health trends
Coordination among multiple caregivers
Miscommunication with healthcare providers
AI generated insights from journal entries of the care crew. The insights can be filtered by tags.
The LLM can detect life events such as injuries, hospitalizations etc
A collection of patient-related journal notes shared by the entire care crew
The caregiver sets a time budget per week to allocate to various Activities of Daily Living (ADLs) of the patient.
A overview of the wellbeing of the care crew.
The chatbot responds to the caregiver’s queries based on past journal entries
Summarizes past trends, medical reports etc in a SOAP format that can be easily communicated to a medical professional
Clicking on a journal insight provides more information such as medication history etc
I handed over the designs to the dev team to build a prototype iOS application, ready for user testing.
Next Steps
The next step for this app was to put it in the hands of family caregivers who signed up to be our beta testers. These participants agreed to provide weekly feedback that would help us measure the value delivered by our solution, as well as usability and technical issues.
If I had a do-over and more time, I would have focused more on user research and problem validation. Also, I would have let technical feasibility drive my design decisions.
Conclusion and Learnings
We faced challenges implementing some of the features I proposed, primarily because the LLM outputs didn't align with the requirements for those features. As a result, several ideas were pushed to a future iteration. This experience reinforced for me that when working with AI, technical feasibility needs to play a stronger role earlier in the design process.
Additionally, when I joined the team, initial market research and problem validation had already been done. However, looking back, I would have prioritized spending more time understanding the pain points of caregivers and what solutions would help them the most. Including users early on would have been ideal.
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© 2025 Rohan Pinto