1. RESEARCH POSTER PRESENTATION DESIGN © 2012
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PICO
Will patients, aged 18 and over, in the Manhattan VA Hospital (on 10 North),
who are at risk for falls via the Morse Fall Scale, show a decrease in the
prevalence of falls by implementing wearable, color-coordinated fall risk
identifiers, compared to similar patients utilizing the current “falling dot”
program?
Literature Review
• Hospital organizations influence risk for falls. Yet there is no uniform
protocol for fall prevention, the strategies vary across all settings (Mion et al.,
2012).
• Fall rates in the acute hospital setting are between 2-5%, with > 30%
resulting in physical injury or psychological morbidity, in addition to
greater use of healthcare resources (Walsh, Hill, Bennell, Vu, and Haines, 2010).
• The overall success of interventions implemented to decrease fall risk
depends on the accuracy of risk assessment in ensuring that the correct
patient is targeted (Hempel, Newberry, Wang, Booth, Shanman, Johnsen,... Ganz, 2013).
• One of the clinically significant issues in fall prevention is failing to remove
identification signs after high-risk patients are discharged from the unit
(Hempel, et al., 2013).
• A qualitative study included 560 nurses working in 68 acute care settings
across the country found single interventions i.e. only a sign on the door or
only a fall risk bracelet, were the least helpful methods (Tzeng & Yin, 2014).
• Signs above the beds, colored bracelets and fall risk colored socks as
multiple reminders for all caregivers that patient is at high risk. The
multiple reminders lead to interventions that will prevent falls (Agostini, Baker
and Borgardus, 1999).
Major EBP Recommendations
Evaluation
Methods of Implementation
Goal: Decrease fall incidence rate
Clinical Setting: 10 North Inpatient (Medical Surgical) Unit, at the
Manhattan VA
Sample Population: Patients aged 18 +, who are at risk for falls via the
Morse Falls scale (25 and above)
Implementation:
• Patients who are identified as “at risk” for falls, per the Morse Falls
scale, with a score of 25 or higher, will be randomly sorted into two
groups.
• One group will receive wearable, color coordinated risk identifiers
(bright yellow non-slip socks and bright yellow identification bracelet),
and the other will receive a “red dot” outside of their room and plain,
printed “fall risk” identifiers on their wrist band.
• Fall incidence over the next three months will be carefully documented,
noting the circumstance of the fall and the group that the fall patient
belongs to.
• At the end of the testing period (3 months), the incidence rate for falls
for both groups will be compiled and evaluated.
• A t-test with a p-value of < 0.05 will be used to determine statistical
significance between the fall rates of the two groups.
• Qualitative observations will also be made and taken into account.
Adrian Anderson, Brian Davis, Emily Elisha, Ta/ana Kochengina and Arielle Myrthil
Pace University, College of Health Professions, Lienhard School of Nursing
Evidence Based Prac/ce Improvement: Color Coordinated Fall Risk Iden/fiers
Search Strategy
• Clinical guidelines published within the past five years were
searched using “Fall Prevention” as a keyword in:
o National Guidelines Clearinghouse
o National Quality Measures Clearinghouse
• Clinical guidelines were chosen based on their suggestions on
limiting the number of falls that occur in the hospital.
• Systematic reviews and single studies were searched using terms
“fall prevention:”
o Medline by EBSCOhost
o PubMed through NCBI
o CINAHL
o Nursing and Allied Health Collection.
References
Level of Evidence: 1- Systematic Reviews, Meta- Analysis, EBP Guidelines
Agency for Healthcare Research and Quality. (2014) Preventing Falls in Hospitals: A Toolkit for Improving Quality
of Care. Retrieved from http://www.ahrq.gov/professionals/systems/hospital/fallpxtoolkit/fallpxtkmap.ht
Level of Evidence: 4- Cohort Studies or Case Control Studies
Agostini, J., Baker, D., & Bogardus, S. (1999). Chapter 26. Prevention of Falls in Hospitalized and Institutionalized
Older People. In Making Health Care Safer: A Critical Analysis of Patient Safety Practices.
Level of Evidence: 4- Cohort Studies or Case Control Studies
Bouldin, E. D., Andresen, E. M., Dunton, N. E., Simon, M., Waters, T. M., Liu, M., … Shorr, R. I. (2013). Falls
among Adult Patients Hospitalized in the United States: Prevalence and Trends. Journal of Patient Safety, 9(1), 13–
17. doi:10.1097/PTS.0b013e3182699b64
Level of Evidence: 1 – Systematic Reviews, Meta-Analysis, EBP Guidelines
Gray-Miceli, D. and Quigley, PA. Fall prevention: assessment, diagnoses, and intervention strategies. (2012).
Evidence-based geriatric nursing protocols for best practice. 4, 268-97.
Level of Evidence: 1- Systematic Reviews, Meta- Analysis, EBP Guidelines
Hempel, S., Newberry, S., Wang, Z., Booth, M., Shanman, R., Johnsen, B., . . . Ganz, D. (2013). Hospital Fall
Prevention: A Systematic Review of Implementation, Components, Adherence, and Effectiveness. Journal of the
American Geriatrics Society J Am Geriatr Soc, 61, 483-494. doi:10.1111/jgs.12169
Level of Evidence: 4- Cohort Studies or Case Control Studies
Hurley, A., Gersh-Zaremski, R., Kennedy, A., Kurowski, J., Tierney, K., Benoit, A., Chang, F., ...., Middleton, B.,
(2009). Fall TIPS: Strategies to promote adoption and use of a fall prevention toolkit. AMIA Symposium
Proceedings, 153-157.
Level of Evidence: 2- Randomized Control Trials
Mion, L.C., Chandler, A.M., Waters, T.M., Dietrich, M.S., Kessler, A.M., Miller, S.T., & Shorr, R.I. (2012). Is it
possible to identify risks for injurious falls in hospitalized patients? Joint Commission Quality Patient Safety. 38(9).
408-413.
Level of Evidence: 4- Cohort Studies or Case Control Studies
Tzeng, H., & Yin, C. (2013). Most and least helpful aspects of fall prevention education to prevent injurious falls: a
qualitative study on nurses' perspectives. Journal of Clinical Nursing. 23(17). 2676-2680.
Level of Evidence: 4- Cohort Studies or Case Control Studies
Walsh, W., Hill, K., Bennell, K., Vu, M., and Haines, T. (2010). Local adaptation and evaluation of a falls risk
prevention approach in acute hospitals. International Journal for Quality in Health Care, 23(2), 134-141. doi:
10.1093/intqhc/mzq075
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Background
• The occurrence of falls in hospitals, contribute to increased morbidity,
mortality, and hospital stays for patients. Each year 700,000-
1,000,000 patients fall in a hospital setting.(AHRQ, 2013)
• While fall rates vary based on the type of unit, a research study
canvassing 1,263 hospitals reported a 2 % prevalence, with falls
occurring at a rate at 3.3 to 11.5 per patient day. (Bouldin et. al, 2013)
• In the NY Harbor Campus of the Veteran Association Hospital, over
an 8 month period , 139 falls occurred within 27,934 bed days of care
resulting in an inpatient fall rate of 4.98 per bed days of care.
• 30-35 % of patients sustained injuries from falls. Approximately 9.8
% of falls observed resulted in moderate injury, 4.3 % resulted in
major injury and 0.1% resulted in death. (Bouldin et. al, 2013)
• In 2013 healthcare costs associated to falls was $34 billion.(AHRQ,
2013)
Change Process
•Obtain consent from administrative and nursing directors to
implement intervention.
•Discuss with 10N nurses their views on falls/fall prevention and if
the current implemented safety measurement is adequate.
•Inform CNAs of the idea of color coordinated socks and
wristbands as fall risk identifiers and request their assistance in
encouraging the residents to comply.
•Inform each resident of the benefits of wearable color coordinated
fall risk identifiers as a safety precaution to prevent falls and further
injury.
•Identify risk of falls of each patient on the Morse Scale, a score of
twenty five or greater will receive these identifiers.
•Perform weekly assessments with residents and nurses to see if the
bright colors are a better indicator of a patient at risk for falling.
•Assess if those who received color coordinated identifiers fell less
frequently after three months.
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Evaluation
•We will evaluate each residents score on the Morse Scale before
implementing the new fall risk identifiers.
•At the end of three months, each incidence of falls in residents in the
studied groups will be assessed, to determine if the level of risk for falling
has improved, stayed the same or deteriorated. Based on this assessment
we will be able to determine whether this change process is effective.
The statistical program that will be used for data analysis is the Statistical
Package for the Social Sciences (SPSS). Data will be analyzed using T tests
with p value of 0.05 to determine statistical significance.
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● The recommended ways to communicate risk for falls were visual identifiers
that communicated effectively to healthcare providers, families, and patients
(Gray-Miceli and Quigley, 2012).
● Signs above the beds, colored bracelets and fall risk colored socks are
reminders for all caregivers that patient is at high risk. The multiple
reminders lead to interventions that will prevent falls (Gray-Miceli and Quigley,
2012).
● Ineffective fall alert strategies that were not easy to read for all caregivers,
healthcare and provider were not very effective. Caregivers need to be able
to easily identify persons who are at high risk of falling (Dykes et. al, 2009.,
Tzeng, & Yin, 2013).
• Search yielded topics containing: “prevention of in-hospital
falls”, “factors associated with falls in hospitalized adult
patients,” and “bedside nurses leading the way for fall
prevention.”
• Studies were chosen based on their relevancy to these topics and
the statistical significance with a p value of less than 0.05.
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