AI-Powered Tool Revolutionizes Fall Prevention in UCHealth Hospitals
Healthcare IT News
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Contributed by: Kate Gamble
Summary
UCHealth in Aurora, Colorado, has developed an AI-enhanced risk modeling tool to reduce patient falls in hospitals by providing customized prevention strategies. This system addresses the limitations of traditional fall prevention methods, like bed alarms, that can overwhelm healthcare staff. By utilizing mobility data and behavioral indicators, the model predicts fall risk and incorporates these assessments into the Epic electronic health records system. A multidisciplinary team identified 12 risk domains and 92 variables from over 181,000 inpatient admissions, ultimately creating a logistic regression classification that categorizes patients into three risk tiers: Highest Risk, Elevated Risk, and Universal Risk. The implementation of this model into clinical workflows emphasized the need for straightforward, actionable precautions that clinicians can easily understand and apply.
