Many fall “prevention” companies aren’t actually preventing falls at all, but rather notifying caregivers after a resident is already on the floor. There’s a big difference between detecting falls and preventing falls, depending on the technology you use.
Most “solutions” in the marketplace are reactive, and thus ineffective:
- In-room sitters are expensive and not scalable
- Telesitters require additional IT infrastructure while still requiring costly sitters to monitor video feeds
- Bed and floor pads often send false alerts causing alarm fatigue. When real alerts are sent, it’s usually too late–the resident is already on the floor.
These tactics serve as Band-Aids that cause more disruptions for residents without making a real impact on falls.
Not All AI is the Same
Artificial Intelligence (AI) is a game changer in fall prevention in long-term care for older adults, but not all systems utilizing AI are the same. In fact, there are major discrepancies between fall reduction providers when it comes to their AI capabilities.
Real-Time AI Detects Falls
Some products on the market use AI-enabled video surveillance that notify staff after a resident is already on the floor. These systems tout their ability to get to a resident within 10 to 20 minutes after a fall, but is that really effective, especially if the resident is injured? A fall is a fall.
Predictive AI Prevents Falls
At VirtuSense, we believe the best approach to stopping a fall is to prevent it altogether. Using AI and a remote monitoring platform, VSTAlert can identify and alert staff of bed and chair exits 30 to 65 seconds before a resident gets up. One community saw an 82% decrease in falls after implementing VSTAlert.
It’s 98% accurate which means fewer false alarms and fewer falls so your staff can care for those who need it most when they need it.
Detecting falls after the fact, doesn’t inspire confidence. Predicting and preventing falls offers the best protection for residents and peace of mind for their families.
This article originally published here.