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How AI is Helping to Predict and Prevent Senior Falls

nurse holding senior hand on a walking stick

Falls can be dangerous for anyone, but they are particularly dangerous for seniors. Not only are the elderly at a higher risk for falls, but falls also tend to cause more serious injuries more often than in younger populations. On top of that, recovery after a fall can be tougher and slower for seniors. Because of this, and more, fall prevention and detection are essential components of any risk management solution in an assisted living or senior living facility. Here?s how AI is helping to predict and prevent senior falls:

1. It Can Process a High Volume of Data Efficiently

In order to determine the probability and risk of a fall, a ton of data and details need to be calculated. AI often provides the power needed to process these high volumes of data quickly and accurately to assist in those calculations.

2. AI Helps Provide Predictive Analytics

Analytics can tell you what happened, but predictive analytics can help tell you what is likely to happen. AI can take all of the calculations, individual patient information, and more and turn it into predictive analytics. This can help use all of the data available and pair it with intelligent video analytics capabilities to predict the risk of falls, detect cues that indicate a fall is going to happen, and assist in fall prevention.

When this technology is integrated with a good emergency alert or nurse call system, falls and injuries from them can be prevented and reduced. In California, the El Camino Hospital did just that. In 2017, they used this type of predictive analytics and reduced falls by 39% within the first 6 months.

3. Integrating AI Can Use a Variety of Cues to Predict Falls

By using data from AI and machine learning, paired with your current resident safety and security systems, you can use a variety of cues specific to the residents in your facility to predict falls. There have been successful implementations using mobility cues as well as visual cues.

Mobility Cues

Stumbling, slowing, swaying, and more can all increase the risk of a fall and can be indicators that a fall is about to occur. If you are able to create a baseline of walking speed and stride length for your residents and then detect significant differences in them for individuals, you can help predict and prevent senior falls.

That is exactly what a retirement home located in Missouri did. TigerPlace used sensors around their facility to first establish the baseline of walking speed and stride length for their residents. The sensors were linked to the alert system. If there was a significant decrease from the baseline, which would predict a fall, staff were alerted and could mobilize to help prevent it.

Visual Cues

Swaying, stumbling, and other visual cues can also indicate the likelihood of a fall. Combining video surveillance with AI can help evaluate how falls are most likely to occur in your facility and also identify visual cues that predict a fall.

This information, especially when integrated with an alert or call system, can help predict falls and help you prevent them. Evidence shows that wall-mounted cameras paired with AI and successfully combined with the alert system in long-term care facilities can use visual cues to predict falls, alert staff, and help reduce falls by around 40%.

This is how AI is helping to predict and prevent senior falls. As it continues to develop and become even more accurate at early prediction, AI will continue to become more essential to any fall monitoring & prevention technology or product and also any residential care facility.

If you are exploring fall prevention and detection solutions for your retirement home, senior living facility, or healthcare facility, contact NEPPS for a free site assessment, and make sure you get a customized plan for your needs!