Designing a Multi-Role AI Dashboard for Elder Care Insights
Transforming behavioral data into actionable insights for better care decisions
Team
AI / Data Science
Clinical Research Team
Product & Strategy
Software Engineering
Responsibilities
- Defined role-based system architecture, access, and data visibility
- Designed scalable UX/UI patterns that transformed complex data into clear, actionable insights
- Researched and introduced new workflows and features to support AI-driven care coordination
Overview
Product Ecosystem
Designing for care environments.
Key product and UX decisions to simplify complex healthcare workflows and large-scale behavioral data.
Different roles required different levels of visibility, access, and actions based on operational and privacy needs.
AI insights were designed to support decisions with clear prioritization, recommendations, and follow-up actions.
Complex resident data was grouped into summaries, trends, alerts, and visual patterns to improve readability and scanning.
Same Data, Different Meaning
From Data to Care Decisions
Turning fragmented data into care-ready insights
Data design · UX system
Data transformation
From raw signals to role-based action — four steps that turn noise into clarity.
Roles, Access & Actions
Different roles required different levels of visibility, access, and control across the system.
Design decision rather than five separate dashboards, the system uses a single data layer with role-based filters. This reduces maintenance and keeps the experience consistent across all user types.
Role Deep Drive
Caregiver Dashboard
Core Caregiver Workflow
Identify
Detect risks, behavior changes, missed routines, or critical incidents
Monitor
Review activity, alerts, and AI insights
Follow Up
Track progress and care outcomes
Take Action
Schedule, communicate, and respond
Caregivers needed a fast and reliable way to monitor residents, review AI-generated insights, manage schedules, communicate through robots, and take immediate action when risks were detected.
Caregiver Dashboard
Resident Profile & Care Context
A centralized view of resident wellness, behavioral trends, AI-supported recommendations, and caregiver coordination.
AI-supported alerts
Highlights changes in speech, cognition, and activity patterns
Caregiver notes
Allows staff to leave contextual notes for ongoing care and robot interactions
Wellness & cognitive trends
Tracks behavioral and cognitive changes over time
Actionable recommendations
Connects insights directly to care decisions and follow-up actions
Turned fragmented resident data into a centralized care view with AI-supported insights, behavioral trends, and actionable follow-up tools.
Caregiver Dashboard
AI Insights & Critical Alerts
AI-supported insights helped caregivers identify urgent risks, prioritize residents, and take faster action.
Detect pattern → Prioritize risk → Recommend action → Caregiver response
Priority-based alerts
Highlights residents who need immediate attention
Actionable AI recommendations
Connects detected patterns to suggested next steps
Faster response workflow
Reduces time spent scanning reports and identifying risks
This view turns a long resident list into a prioritized care queue
Caregiver Dashboard
Care Coordination & Communication
Managing schedules, broadcasts, and communication workflows across residents and care teams.
Broadcast
Robot-assisted communication
Send reminders, announcements, and media directly through robots
Shared scheduling
Coordinate therapy, visits, and daily activities across residents
Calendar
Unified scheduling and communication into a single caregiver workflow
Supporting Multiple User Roles
The platform supported multiple stakeholders with different access levels, priorities, and workflows across the care ecosystem.
Family Member
System-wide operational visibility
Resident
Personal wellness tracking & engagement
Outcomes & Impact
Helped caregivers identify high-risk residents more quickly.
Transformed fragmented behavioral data into readable patterns and trends.
Unified monitoring, communication, scheduling, and follow-up actions into one system.