F

Fellowship Square Mesa reduces falls by 70% with Helpany AI radar-based fall prevention

“Fellowship Square Mesa reduces falls by 70% with Helpany AI radar-based fall prevention” documents a Patient Safety & Fall Prevention deployment in Senior & Home Health at Fellowship Square Mesa. fellowshipsquare-mesa.org reports fall reduction: 70%; this directory has not independently verified that result.

Maintained by Peter Korpak, Founder & Chief AnalystHow evidence is checked

Evidence at a glance

Evidence status:
Automated evidence gate passed
Deployment timeframe:
Not reported by source
Reported outcome metrics:
3 cited below
Directory entry published:
Source link checked:

The source-link check confirms reachability, not independent re-verification of every claim.

70%Fall Reduction
ZeroNighttime Falls
$200,000Resident Value Generated

Source-reported figures — cited source: fellowshipsquare-mesa.org

The Challenge

Falls are a serious and ongoing safety concern in senior living communities, particularly during nighttime hours when staff availability is reduced. Fellowship Square Mesa needed a proactive solution to identify at-risk residents and intervene before falls occurred, without compromising resident privacy or dignity.

The Solution

Fellowship Square Mesa deployed Helpany's AI-powered fall prevention device, 'Paul,' in every assisted living apartment. The device uses AI and radar-based technology to monitor residents' movements and analyze unique motion patterns, sending real-time alerts to caregivers when potential fall risks are detected — enabling timely interventions 24/7.

Results

Within just two months, the community achieved a 70% reduction in falls compared to prior monthly averages, with zero nighttime falls recorded during the period. The system also reduced severe fall-related injuries and emergency room visits, and provided over $200,000 in resident value by eliminating the need for nighttime companions.

Key Takeaways

  • Radar-based AI monitoring can achieve dramatic fall reduction (70%) in a short deployment window (2 months) without camera-based intrusion.
  • Proactive real-time alerting eliminates the highest-risk period (nighttime) entirely when implemented consistently across all units.
  • Fall prevention technology delivers measurable financial value beyond safety outcomes, including reduced staffing costs.

Share:

Details

AI Technology
IoT & Edge AI
Company Size
SME
Evidence status
Automated evidence gate passed
Deployment timeframe
Not reported by source
Directory entry published
Source link checked

Have a similar implementation?

Share your customer's AI results and link it to your vendor profile.

Submit a case study →