Abstract

A typical nursing home with 100 beds reports 100-200 falls each year (CDC, 2015). It is common to see the utilization of personal alarms in nursing homes to prevent falls, although there is no evidence to support the idea that personal alarms reduce falls. The project aimed to address the question: In long-term care patients, what is the impact of an alarm elimination program versus current practice of utilizing alarms, on fall rates over a 2-month time frame? The project used a multi-pronged, alarm elimination program. Limitations of the project were an overall low compliance rate among staff, a short time frame, and isolation to a single facility. The results of the project found that no statistical significance was determined in the decrease in fall rates (p=0.29), however, fall rates decreased in frequent fallers (-3.49%, p=0.31), fall rates that excluded frequent fallers (-0.18%, p=0.47), and overall fall rates (-3.66%, p=0.29).

Angela Moses

Author Details

Angela Moses, DNP, MSN, RN

Sigma Membership

Non-member

Type

DNP Capstone Project

Format Type

Text-based Document

Study Design/Type

Other

Research Approach

Translational Research/Evidence-based Practice

Keywords:

Falls Prevention, Alarm, Nursing Home, Long-term Care

Advisor

Forsythe, Lydia L.

Second Advisor

Manty, JoAnn

Third Advisor

Richard, Palen James

Degree

DNP

Degree Grantor

Capella University

Degree Year

2016

Rights Holder

All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.

All permission requests should be directed accordingly and not to the Sigma Repository.

All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.

Review Type

None: Degree-based Submission

Acquisition

Self-submission

Date of Issue

2017-02-23

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