KnowFalls Announces the Development of an
AI-based Fall Detection and Prevention Systems
Hospitals can save over $2.9 billion in fall expenses not reimbursed by CMS
PRESS RELEASE
Orlando, Feb 11, 2019, HIMSS Conference. KnowFalls, today announced, the development of a fall prevention and detection system. It will enable hospitals to increase patient safety and reduce the financial burden of bearing the expense of inpatient falls imposed by the Centers for Medicare and Medicaid.[i]
Falls are Costly
Annually, 700,000 to 1,000,000 patients fall within the hospital environment. Fourteen percent[ii] result in moderate injury (e.g. suturing or splinting), major injury (e.g., bone fracture or brain injury) or death. On average, hospitals stays are extended by six to twelve days at a current cost of over $20,000[iii]. The 2019 hospital financial burden, excluding liability claims, is $.330 million per 100 beds or over $2.9 billion for all US hospitals.
And More Costly by 2030
According to US Census Bureau, by 2030 all baby boomers will be older than age 65[iv], resulting in 1 in 5 US hospital charges being covered by CMS. At current patient fall rates, the total US hospital financial burden of falls not reimbursed by CMS will be $3.4 billion.
Tools Needed to Control Fall Injuries and Costs
The KnowFalls System provides hospitals with fall prevention tools recommended by the Patient Safety Network[v] and the Joint Commission[vi]. These tools offer responders situational awareness, improve team communications, workflow interaction, and reliable patient monitoring.
Detection and Prevention
The KnowFalls Fall System acquires and processes video from cameras within patient rooms and patient accessible areas twenty-four hours a day, seven days a week[MH1] . Upon detecting a patient fall, the KnowFalls System transmits an alarm notification to the attending nurse’s smartphone, tablet, or clinical communication system utilized by the hospital. The notification includes a video of the patient’s fall (or filtered video when used in high privacy-sensitive locations). The nurse can immediately view and communicate with the patient via camera audio and determine the optimal response.
The KnowFalls Fall Detection System automates the recognition of activity-restricted patient movements preceding a fall (I.e. bed or chair exiting).
Why AI Video Processing
KnowFalls utilizes video processing for three reasons:
▪ Situational Awareness
The KnowFalls system delivers actionable information in real-time audio video format empowering faster decisions for the best response. This system enables nurses to receive visual detail of the fallen or at-risk patient combined with two-way audio communications.
▪ Video and Patient Privacy
The KnowFalls AI model enables users to view a patient’s true or filtered video. Filtered video provides the responder with full information about the patient’s movements while maintaining privacy within designated sensitive locations. Exhibit 1 seen below, illustrates the contrast between true and filtered video.
▪ Audio and Video Audit Trail
Video combined with audio creates a more robust audit trail of an event. The KnowFalls system combines audio and video to provide the data needed to implement many of the Joint Commission’s Sentinel Alerts recommendations for fall prevention. It generates audio and video before, during and after the fall.
About KnowFalls
KnowFalls is transforming fall detection, prevention and risk management within healthcare. The KnowFalls Systems utilize state of the art artificial intelligence and off-the-shelf cameras. The System operates passively and there is no use of electromagnetic radiation or patient wearables.
KnowFalls was founded by executives and technologists from prominent healthcare companies including McKesson, Philips, Northwell Health and Wellcare. The company was founded in 2018 and is headquartered in Tampa Bay.
[i] In October 2008, the Centers for Medicare and Medicaid Services (CMS) stopped reimbursing hospitals for costs related to patient falls.
[ii] Based on the National Database of Nursing Quality Indicators
[iii] See Exhibit 2 - Annual Fall Financial Burden per 100 bed hospitals for CMS non-reimbursement for inpatient fall injuries
[iv] Older People Projected to Outnumber Children for First Time in U.S. History, https://www.census.gov/newsroom/press-releases/2018/cb18-41-population-projections.html
[v] Key Issues in Developing a Successful Hospital Safety Program, US Department of Health Care and Human Services, https://psnet.ahrq.gov/
[vi] A New Approach to Preventing Falls With Injuries, The Joint Commission Update
https://www.centerfortransforminghealthcare.org/-/media/CTH/Documents/What-We-Offer/A_New_Approach_to_Preventing_Falls_With_Injuries.pdf
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Media Contact
John Montelione
JohnMontelione@knowfalls.com
c#941.724.9700
Note: KnowFalls is a dba for AI Video Analytics, Inc.
Exhibit 1
KnowFalls Fall Detection Systems Generate Patient Imagery via True Video and/or Filtered Video
