Fall Prevention Solutions

Patient Falls Are a Challenge

Since the Joint Commission published Sentinel Alert 55, focusing on fall prevention, falls remain at 7.6 per 1000 patient stays. The Agency for Healthcare Research and Quality within the US Department of Health and Human Services estimates:

Patient Falls/Year: 800,000 to 1,000,000
Injury Rate: 35%
Deaths: 10,000+
Hospital cost per fall: $6,700 (excluding litigation)

Plus, falls are one of the three top events resulting in hospital litigation, and fall rates are expected to rise for over the next ten years seniors, 75 and over (the most prone fall group), will become the dominant hospital patient.

The Cause

Causes are often age-related: sensory impairment, chronic health conditions, unstable gait, altered mental status, and high risk medications.

The Challenge

Seniors fall at a rate 28% higher than others and over the next 10 years will account for 55% of hospital stays - while hospitals experience a nursing shortage.

The Solution

With bed exits unpredictable, constant patient visual monitoring is becoming the norm. The only solutions are in-room sitters or centralized patient monitoring.

In-Room Sitters Are Expensive and Not A Proven Solution

Patient sitters are often prescribed for at-risk patients. For an average 4.5 day hospital stay, the sitter cost can exceed $1,700. As noted in the Journal of Nursing Education and Practice, A Comparative Study of Patient Sitters with Video Monitoring versus In-Room Sitters...Use of in-room sitters to prevent a patient’s fall or injury is widespread. expensive, seldom reimbursed, controversial in the literature, and not supported by a strong body of evidence.

KnowFalls Virtual
Patient Observers
Replace Sitters

The KnowFalls Virtual Patient Observation System (VPO). As noted in the Journal of Nursing Education and Practice, A Comparative Study of Patient Sitters with Video Monitoring versus In-Room Sitters… video monitoring is less expensive than sitters and does not impose a patient safety risk for falls. Centralized patient monitoring replaces 14 patient sitters with 1 remote patient observer.

KnowFalls AI App
Predicts Bed
Exit Attempts

The AI Fall Prevention System (AI-System) reduces falls by providing patient observers with early detection and prediction of bed early prediction of patient bed exit attempts. After confirming the alert, the patient observer engages the patient or has the attending nurse/CNA intervene.
The AI-System will be available in 2020 for the KnowFalls and other industry VPOs.