Don’t Get Tripped Up! Leverage Live AI-Driven Data to Inform Quality Improvement Strategies and Prevent Falls

According to the Centers for Disease Control and Prevention (CDC), falls are the leading cause of injury for adults ages 65 years and older. A recent analysis of nearly 10,300 closed claims by global insurance broker and risk advisor Marsh,¹ shows that falls in long-term care account for nearly 50% of claims paid by facilities, equating to an estimated $448.8 million annually! This is a key metric closely monitored in many Skilled Nursing Facility (SNF) Value-Based Purchasing (VBP) programs and the CMS Five Star Quality Measures. Despite these staggering numbers, falls among the senior population are preventable through appropriate screening and interventions in care.

This session examines how nursing facility clinical leadership can proactively reduce fall-related injuries and deaths by implementing strategies that leverage live AI-driven data analytics for Quality Assurance and Performance Improvement (QAPI). Utilizing the PLAN-DO-STUDY-ACT framework, we will delve into how live clinical data can be harnessed to identify risk factors and inform actionable prevention strategies, while sustaining regulatory compliant quality of care for your residents.

To serve as a guiding case study throughout the session, MaryPat Carhart, Vice President Clinical Services at Upstate Services Group (USG), will share her insights on Root Cause Analysis (RCA) and illustrate the steps required to identify the underlying risk factors of falls. She will also review the application of a 4-point QAPI planning approach, showcasing how 7 of USG’s facilities in New York have been able to create effective data-driven plans that mitigate falls.

Joining MaryPat will be Michele Self, Customer Success Manager at Real Time Medical Systems. Michele will discuss how the use of live EHR data analytics can be incorporated into daily operations to help nursing facility care teams identify various types of high-risk patients, reduce avoidable hospitalizations due to falls, highlight the potential for medication-related fall risk, achieve regulatory compliance, and improve overall quality of care measurement.

Drawing on insights and lessons learned from USG’s experience, participants will gain a comprehensive understanding of how live data analytics can reduce fall rates in nursing facilities, improve patient outcomes, and prevent costly claims while enabling SNFs to become a valuable partner to VBP Programs, ACO’s and community reputation through the Five Star system.

Learning Objectives

• Analyze the steps of Root Cause Analysis (RCA) and the QAPI 4-point plan to develop effective fall prevention strategies in nursing facilities
• Evaluate the role of live AI-driven data analytics in identifying fall risk factors, optimizing medication management, and improving patient outcomes and Quality Measure (QM) Ratings
• Implement data-driven interventions to reduce fall rates, prevent avoidable hospitalizations, and ensure regulatory compliance in daily operations

Speakers

• MaryPat Carhart, MHA, BS, RN, Vice President Clinical Service, Upstate Services Group
• Michele Self, MA, CCC SLP, CMAC, Customer Success Manager, Real Time Medical Systems

This live session will take place at the 2026 NADONA National Conference.