Before the Fall: How AI-Enabled Proactive Care Reduced Falls by 70%

Falls, hospitalizations, and staff burnout are not isolated clinical challenges - they are signs of a reactive care model that no longer meets the demands of today's senior living environment. As resident acuity rises and staffing pressures continue, senior living leaders must rethink how care teams identify risk, prioritize interventions, and act before incidents occur.


This session will explore how Westminster Village in Scottsdale, Arizona used AI-enabled, non-camera-based technology to support a shift from reactive response to proactive care. By turning resident activity patterns, mobility trends, disrupted sleep, restlessness, and changes in routine into actionable care insights, the team was able to identify concerns earlier, prioritize interventions more effectively, and reduce falls by more than 70% while preserving resident privacy and dignity. The session also explores the power of measuring what matters at scale: continuous population-level insights can reveal early risks and predictors that would otherwise remain invisible and make them actionable across communities.


Through this real-world case study, Katherine Barney, MHA, BSN, RN, Assisted Living Manager at Westminster Village, will show how a nursing-led team implemented proactive care workflows in daily operations and how earlier visibility into resident change can help teams intervene before concerns escalate into falls, hospital transfers, or broader clinical decline.


Attendees will leave with practical strategies to integrate proactive insights into daily care routines, support staff adoption, identify early risk factors and predictors that can inform intervention, measure progress and outcomes through meaningful KPIs, and advance a more proactive, resident-centered model of senior living care.