The Biggest Challenge in Fall Prevention Isn't Preventing Falls

Guest Blog: Contribution by LeadingAge PA Business Partner, Eugenie Nicoud, COO & Co-Founder of Helpany

Ask senior living leaders what they want for their residents, and prevention is often at the top of the list. Prevent falls. Prevent decline. Prevent an avoidable emergency. Prevent an earlier move to a higher level of care.

Nearly every community pursues some version of that goal through care plans, mobility programs, scheduled checks, and staff observation.

But prevention runs into a fundamental problem before it can even begin: you cannot act on a risk you do not know exists.

Fall risk rarely announces itself. It can develop gradually—a slightly slower walk to the bathroom, more time spent sitting, greater restlessness at night, or a change in how frequently someone gets out of bed. None of these changes necessarily triggers an alarm, and many may not become obvious until they have persisted for days or weeks.

That creates the central challenge of fall prevention: How do you recognize that something is changing before it contributes to a fall?

The challenge is not a lack of attention or effort from caregivers. It is the reality that no care team can observe every resident every hour of the day.

Each resident also has an individual baseline. One person may routinely get up several times during the night. Another may naturally walk slowly but steadily. A change becomes meaningful only when it is understood in the context of what is normal for that individual.

That makes gradual shifts difficult to identify through isolated interactions. A caregiver may notice that someone appears less steady today, but recognizing that the resident's walking pattern has slowly changed over several weeks is much harder—particularly across multiple shifts and staff members.

Some patterns simply become evident only when information is collected consistently over time, which is why many communities are exploring technologies that can help identify subtle changes earlier.

Motion as an Early Signal — and Why AI Matters

Daily movement patterns can provide important context about changes in a resident’s well-being.

Shifts in gait, nighttime activity, bathroom routines, sedentary behavior, sleep, or overall mobility may indicate that something in a resident’s condition or daily routine is changing. One unusual night or a slower walk does not mean that a fall is imminent. What matters is whether that change becomes part of a broader pattern over time.

This is where AI, combined with privacy-preserving sensing technology, can add another layer of insight.

Technologies such as radar are well suited to continuously sensing movement. AI can then make sense of thousands of motion patterns over time, compare them with a resident’s individual baseline, and help determine which deviations may warrant closer attention.

Helpany, for example, uses ceiling-mounted radar devices to recognize changes in gait, sleep, bathroom frequency, sedentary behavior, and other daily movement patterns. The technology does not diagnose a condition or determine what care a resident should receive. Instead, it brings emerging changes to the attention of the care team so caregivers can investigate further and decide whether additional support may be appropriate. 

How this information is collected matters just as much as what can be learned from it. Residents should not have to trade privacy and dignity for greater insight into their well-being. Radar-based sensing provides a way to understand motion patterns without capturing images or conversations. 

But identifying a change is only valuable if the information helps caregivers decide what to do next.

Senior living communities already operate in an environment filled with alerts, notifications, documentation, and competing priorities. Adding more data without context can create more noise rather than better care.

The practical question technology should help answer is much simpler:

Who may need my attention today?

Instead of asking staff to interpret endless streams of data, technology can help highlight residents whose patterns have changed enough to warrant a closer look.

What happens next remains deeply human.

A caregiver or nurse speaks with the resident, observes what is happening, and considers the information alongside their knowledge of that person. They may explore whether pain, illness, medication changes, dehydration, reduced mobility, or another factor could be involved. The result may be additional observation, therapy involvement, a clinical review, increased assistance, or an adjustment to the care plan.

What This Looks Like in Practice

United Zion Retirement Community in Lititz, Pennsylvania, offers one example of what can happen when these insights become part of daily care workflows.

United Zion implemented Helpany across its personal care units in January 2026. Over the following four months, the community reported a 70% reduction in falls compared with its historical baseline. By March, its monthly fall reduction had surpassed 80%, and April ended with zero recorded falls—the lowest monthly fall count in the community's history. 

Another finding showed how earlier awareness can influence more than fall rates. Helpany's service plan assessment identified that one in three care plans required realignment, meaning the documented level of care no longer fully reflected residents' evolving needs and risks. 

The significance is not that technology independently prevented those falls or made care decisions for the team. United Zion's outcomes depended on caregivers using the information, evaluating residents, and taking appropriate action.

What the experience demonstrates is the potential value of moving the point of intervention earlier—from responding only after an incident to investigating when a resident's patterns begin to change.

Being Proactive Is the Future of Care

The future of senior living care will be more personalized, continuous, and responsive to changing resident needs. Technology can help care teams understand each person’s patterns over time, recognize meaningful changes earlier, and tailor support accordingly.

This shift may also become an important competitive differentiator. Residents and families increasingly expect greater transparency, more individualized support, and higher standards of care. Communities that can demonstrate how technology strengthens caregiver decision-making and helps them respond to changing needs may be better positioned to build trust and distinguish themselves in an increasingly competitive market.

Used well, technology does not make care less human. It can make care more compassionate by giving caregivers better context, helping them focus attention where it is needed most, and supporting more thoughtful decisions.