Implementing a Fall TIPS Program to Reduce Fall Rates Among Inpatient Adults
Wieczorek, Page
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Abstract
Problem: Nearly 1 million people fall in U.S. hospitals annually, leading to complications and higher healthcare costs. On an adult intermediate care and telemetry unit at a large academic hospital, current fall prevention methods have not been effective. In 2023, unit data showed 16 falls, six with injuries, and 10 falls by August 2024, with a peak fall rate of 4.50 falls per 1,000 patient days in July. This highlighted the need for an evidence-based fall prevention intervention. Research supports the use of the Fall TIPS toolkit to reduce falls, potentially benefiting over 1,200 patients annually. Purpose: This quality improvement project aimed to reduce fall rates in adult patients by implementing and evaluating the Fall TIPS toolkit. Methods: Baseline fall rate data was collected before the project. Forty out of 49 nursing and support staff were trained on the Fall TIPS toolkit. A laminated Fall TIPS poster was placed in each room to be filled out by nurses upon patient admission and each shift. Weekly audits were conducted to monitor adherence, with data inputted into REDCap. Barriers and facilitators were identified through in- person and email communications with staff. Unit fall data was also analyzed weekly. Results: Over 15 weeks, staff adherence to the Fall TIPS toolkit averaged 69.2%, with adherence as low as 20% and as high as 100% in one week. During this period, four falls occurred without injury. Barriers to adherence included staff shortages, fluctuating patient acuity, and utilization of float pool staff unaware of the project. Conclusions: The findings show variable staff adherence to the Fall TIPS toolkit. Efforts to improve adherence included ongoing support, education, and reminders in patient rooms and during staff huddles. Although falls decreased by 43% compared to the 15 weeks before implementation, the effectiveness of the Fall TIPS toolkit in reducing fall rates remains uncertain, requiring more data and time for conclusive results.
