32 The 4 ms strategy to fall prevention. (25th November 2019)

• Record Type: Journal Article
• Authors: Barnett, William; Dodrill, Michael; Oostra, Carson; Alkhathlan, Mujahed; Nesheiwat, Zeid; Nehme, Christian; Kayyali, Ammar
• Is Part Of: BMJ open quality. Volume 8:Supplement 2(2019)
• Page Start: A47
• Page End: A50
• Publication Date: 2019-11-25
• Subjects: Medical care -- Quality control -- Periodicals; 362.106805
• DOI: 10.1136/bmjoq-2019-ihi.32
• Languages: English
• ISSNs: 2399-6641

Abstract

Abstract : Background: Despite the fact that many organizations have implemented fall risk scales to identify patients at risk, fall management continues to challenge healthcare providers. In 2015, we noticed the Morse scale alone was an inadequate tool to fully assess a patient's fall risk and began an intensive examination of our fall prevention protocol. Objectives: Our initial aim was to assess any inadequacies in our fall prevention policies or guidelines. Subsequently, we wanted to identify and establish interventions that were effective at preventing patient falls, especially among high fall risk patients. Methods: We selected Lean Six Sigma as our robust quality improvement (QI) methodology to conduct a detailed systems-based investigation. More specifically, we utilized fishbone diagrams, value stream maps, Pareto charts, flowcharts, control charts, and the 5 Whys throughout the study. Based on our findings, our team developed the 4 M strategy that promotes a multidisciplinary approach in the individualized and comprehensive assessment of a patient's Morse score, mental status, mobility, and medications. Furthermore, we periodically evaluated our fall rates and analyzed our patient safety reporting to adjust the guidelines using additional quantitative methods. Results: Over the past 3 years, continuous monitoring of monthly falls demonstrated a 40% reduction within the acute care population after implementation of the revised fall risk protocol. Conclusions: Our strategy towards investigating the problem and devising data-driven solutions with robust QI tools was further facilitated through working with different disciplines, such as nursing, pharmacy, rehabilitation services, resident physicians, information technology, and health systems science specialists.