Exciting Falls Prevention Study uses AI to Predict Falls in Long-Term Care

Building photograph © FJ Davey Home

The Sault Ste. Marie Academic Medical Association is proud to announce an exciting new research study that will be piloted at a long term care home in Northern Ontario in the upcoming months.

Falls are the leading cause of injury in older Canadians and can have life changing implications on individuals and their families. Up to 30% of seniors experience at least one or more falls per year and over one third of seniors are admitted to long-term care (LTC) facilities following hospitalization for a fall. Falls also cause 85% of seniors’ injury-related hospitalizations and 95% of all hip fractures, resulting in 2 billion dollars per year in direct healthcare costs (Stinchcombe, Kuran, & Powell, 2014).

To address this issue, partnered with local tech company, Digital Grounds, our team will be testing a falls prevention protocol in a long-term care setting that utilizes machine learning. This project will using Digital Grounds’ innovative Gentroo app.

Gentroo connects to wearable sensors that track the movement patterns of residents and then organizes this information to alert healthcare providers of resident’s real-time falls risk. We hope that this project will not only help prevent falls to increase resident quality of life, but also to improve the daily workflow of healthcare providers in a long-term care setting.

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Stinchcombe, a., Kuran, N., & Powell, S. (2014). Seniors’ Falls in Canada. In Chronic Diseases and Injuries in Canada (Vol. 34).