Utilizing Artificial Intelligence for Falls Management in PA/LTC: Now recruiting for study sites!

Each year, more than one in four older adults aged 65 and older will fall. Among older Americans, falls are the number one cause of injuries and death from injury (1). This represents 29 million falls, 3 million emergency department (ED) visits, 800,000 hospitalizations, and 28,000 deaths. As the leading cause of fatal and nonfatal injuries among older adults, falls will continue to soar, as America’s baby boomers grow older (2).

Falls are often the number one reported adverse event in Skilled Nursing Facilities (SNFs) and each SNF’s fall rate is monitored by CMS as part of a facilities overall quality metric (https://www.medicare.gov/nursinghomecompare/search.html?)

Advancements in technology by using artificial intelligence (AI) provides additional insight with enhanced support and fall evaluation (3).  After written informed consent, SafelyYou installed AI-enabled camera technology in all memory care neighborhood apartments.  The technology detects a fall by analyzing cameras video feed, stores video only when a fall is detected and sends alerts when a fall occurs. To adhere to privacy requirements the system does not record audio and automatically deletes any video unrelated to the detected fall within minutes. Captured video from study participants is used to provide analysis in supporting decision making and Root Cause Analysis.  In SNFs, the fall specific videos and related analysis and interventions can be incorporated into the QAPI process.   

By leveraging AI-enabled fall detection with immediate staff review of falls, we recently published a 3-month pilot study that showed a reduction of ED visits by 80% and EMT calls by 75%, in memory care facilities (4).  Other outcomes include reduced number of falls among residents living in memory care, lowered average response time, and reducing the average time a resident spends on the ground.  We caution that these results are preliminary and with a total of 59 residents in 6 communities. 

SafelyYou is currently recruiting study sites and participants to enroll in large scale waitlist-controlled studies of up to 480 participants in SNFs and 280 in Memory Care ALF facilities to validate the pilot results.  The major aims of the studies include reducing fall rates,  ED visits and hospitalizations, when compared to waitlist control. 

For more information about this study, please contact Glen Xiong; MD, CMD at [email protected]

  1. Burns E, Kakara R. Deaths from falls among persons aged ≥65 Years — United States, 2007–2016. MMWR Morb Mortal Wkly Rep. 2018;67(18):509-514.
  2. Center for Disease Control and Prevention.  (2017).  Take a stand on falls.  Retrieved from https://www.cdc.gov/features/older-adult-falls/
  3. Bayen E et al. Reduction in fall rate in dementia managed care through video incident review: Pilot study. J Medical Internet Res. 2017;19(10):e339:1-16.
  4. Xiong et al. Real-time video detection of falls in dementia care facilities and reduced emergency are. Am J Managed Care. 2019;25(7):314-315.
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