TrackableHealth.AI empowers elder care facilities with wearable insights that cut falls by up to 69% and reduce hospitalizations by around 39% both confirmed in a peer-reviewed JMIR Aging study of continuous wearable monitoring.
Early detection of falls, wandering, or vital sign changes through continuous monitoring. AI identifies patterns that precede falls enabling intervention before an incident occurs. Continuous monitoring keeps seniors safer and independent longer while reducing the operational burden on care staff.
“Early detection of falls, wandering, or vital sign changes enabling staff to intervene before a situation becomes an emergency.”
TrackableHealth.AI Elder Care Platform Overview
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Unlike traditional AI tools that rely on humans to initiate queries, Trackable Health enables event-driven GenAI activation based on real-world changes so the system flags a problem before a person can report an issue.
Platform Capabilities
Everything You Need In One Platform
Fall Detection and Prevention
AI identifies patterns that precede falls enabling intervention before an incident occurs. The 69% fall reduction figure is drawn from a peer-reviewed JMIR Aging study.
Wandering and Location Monitoring
Real-time location awareness for residents with dementia or cognitive decline. Geofence alerts notify staff the moment a resident leaves a safe zone.
Vital Sign Change Detection
Continuous monitoring of heart rate, sleep patterns, and activity levels surfaces subtle health deteriorations enabling intervention before hospitalisation is required.
Reduced Hospitalisations
Identifies subtle declines in activity, behaviour, or health trends before they become acute. The ~39% hospitalisation reduction is from the same peer-reviewed JMIR Aging study.
Faster Staff Response
Real-time AI alerts reach the right caregiver before a situation escalates improving response coordination and reducing the lag between a detected risk and a staff intervention.
Extended Independent Living
Better insight into wellness and early intervention helps residents maintain independence longer data-driven care that respects resident dignity and autonomy.
Better Resource Allocation
Data reveals patterns in resident needs helping management optimise staffing, prevent caregiver burnout, and allocate care resources more effectively.
Regulatory Compliance Support
Continuous monitoring data supports regulatory compliance documentation and provides evidence for accreditation and quality reporting requirements. The MAHA ELEVATE program mandates documenting outcomes.
Results
What the Evidence Shows
The fall reduction and hospitalisation figures below are drawn from a peer-reviewed pilot study published in JMIR Aging examining continuous wearable monitoring in assisted-living communities. Other outcomes are directional based on operational experience.
TrackableHealth.AI works with comfortable, familiar consumer wearables that residents are willing to wear improving participation and delivering richer data than clinical-grade devices alone.
1
Connect Resident Wearables
Comfortable consumer-grade or clinical wearables pair automatically with the platform. No complex IT setup required.
2
Continuous Passive Monitoring
Heart rate, HRV, sleep duration and quality, activity, and patient vitals monitored continuously. Staff go about their normal duties, but can be proacitve in their interventions to reduce friction by building trust.
3
AI Detects Risk Patterns Early
Models identify patterns preceding falls, wandering, or health deterioration. Staff receive prioritized alerts with recommended actions.
4
Families Stay Informed
Optional family-facing reports and alerts provide peace of mind building trust between residents, families, and the facility.
5
Management Gains Intelligence
Trend data reveals staffing needs, care protocol gaps, and resource allocation opportunities for continuous improvement.
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