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By merging world class care with research and artificial intelligence, St. Joseph’s Health Care London is catching falls before they happen.  

They wreak havoc on independence and well-being, making them one Canada’s most pressing health challenges: falls.  

A leading cause of injury-related hospitalizations, even death, among older adults, a fall can happen anytime, anywhere – with 50 per cent occurring at home. But what if we could predict and prevent falls before they happen?   

A pioneering initiative at St. Joseph’s Health Care London (St. Joseph’s) is doing just that. The 3FM Clinic, short for Falls, Fractures, Frailty and Mobility, at St. Joseph’s Parkwood Insitute is at the leading edge of falls prevention in Canada, integrating research with clinical practice to offer hope and practical solutions to older adults.

Led by St. Joseph’s geriatrician Dr. Jaspreet Bhangu and Western University rehabilitation scientist and physiotherapist Janelle Unger, PhD, the visionary 3FM Clinic is working to prevent falls before they happen.

“We know there are a number of factors that can cause an older adult to fall such as illness, medication side effects, balance and gait issues, cognitive impairment, visual changes and environmental hazards,” says Bhangu. “What we’re working to understand is how those factors together impact individual patients and their risk of falling.”

To do so, the 3FM Clinic team – one of the largest, most diverse teams of its kind in the country – completes a multi-step evaluation of patients: 

• Nurses gather their medical history, current medications, functional abilities and personal goals.
• Physical therapists measure the patient’s gait (how they walk) and balance to understand their physical capabilities.
• Occupational therapists test their vision, cognitive function and identify issues that might hinder the individual’s ability to perform routine tasks safely.
• A geriatrician focuses on medical risk factors such as bone health, medications and cardiovascular health to help manage risks associated with aging. The team then creates a customized care plan that incorporates exercises, therapeutic interventions and educational strategies.

On the research side, Unger and her team in the RED Neuro Lab at St. Joseph’s Gray Centre for Mobility and Activity are leveraging artificial intelligence (AI) to predict falls more accurately.  

“Traditional fall prediction models often rely on limited data and lack real-world input from clinicians and patients,” explains Unger. “By partnering with Bhangu and the clinical team, as well as the patients in the 3FM Clinic, we’re able to integrate clinical information with biomechanical data collected from wearable sensors known as inertial measurement units (IMUs).”

An IMU is a device that tracks and measures a person’s movement and orientation and provides valuable data on how that person moves and stays stable. 

“We plan to use AI to analyze the data collected through the IMU’s and are working to create accurate fall prediction models,” says Unger. “This research, funded by Western’s Bone and Joint Institute, has the potential to improve care decisions, enhance preventive strategies and ultimately reduce the incidence of fall-related injuries and hospitalizations for our patients and people across the globe.”

By embracing innovative research and compassionate care, the 3FM Clinic is a model for future efforts in fall prevention and geriatric care, offering a safer, more independent future for older adults.

You can prevent falls too:

• Use assistive devices: Properly fitted walkers or canes provide essential support and stability.
• Fitted footwear: Shoes (not slippers or flip-flops) with appropriate tread and low heels help prevent slips and falls. They should also fit your feet.
• Home improvements: Improved lighting, clear walkways and assistive bathroom fixtures.
• Exercise: Participate in strength and balance exercises to enhance physical fitness.
• Medication reviews: Regularly have your medications reviewed to identify if you are at risk of falling.