Development and Validation of a Fall Prevention Efficiency Scale
- PMID: 33480645
- PMCID: PMC8292432
- DOI: 10.1097/PTS.0000000000000811
Development and Validation of a Fall Prevention Efficiency Scale
Abstract
Objectives: Fall TIPS (Tailoring Interventions for Patient Safety) is an evidence-based fall prevention program that led to a 25% reduction in falls in hospitalized adults. Because it would be helpful to assess nurses' perceptions of burdens imposed on them by using Fall TIPS or other fall prevention program, we conducted a study to learn benefits and burdens.
Methods: A 3-phase mixed-method study was conducted at 3 hospitals in Massachusetts and 3 in New York: (1) initial qualitative, elicited and categorized nurses' views of time spent implementing Fall TIPS; (2) second qualitative, used nurses' quotes to develop items, research team inputs for refinement and organization, and clinical nurses' evaluation and suggestions to develop the prototype scale; and (3) quantitative, evaluated psychometric properties.
Results: Four "time" themes emerged: (1) efficiency, (2) inefficiency, (3) balances out, and (4) valued. A 20-item prototype Fall Prevention Efficiency Scale was developed, administered to 383 clinical nurses, and reduced to 13 items. Individual items demonstrated robust stability with Pearson correlations of 0.349 to 0.550 and paired t tests of 0.155 to 1.636. Four factors explained 74.3% variance and provided empirical support for the scale's conceptual basis. The scale achieved excellent internal consistency values (0.82-0.92) when examined with the test, validation, and paired (both test and retest) samples.
Conclusions: This new scale assess nurses' perceptions of how a fall prevention program affects their efficiency, which impacts the likelihood of use. Learning nurses' beliefs about time wasted when implementing new programs allows hospitals to correct problems that squander time.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.
Conflict of interest statement
D.W.B. consults for EarlySense, which makes patient safety monitoring systems. He receives cash compensation from CDI (Negev), Ltd, which is a not-for-profit incubator for health IT startups. He receives equity from ValeraHealth, which makes software to help patients with chronic diseases. He receives equity from Clew, which makes software to support clinical decision making in intensive care. He receives equity from MDClone, which takes clinical data and produces deidentified versions of it. He receives equity from AESOP, which makes software to reduce medication error rates. He receives research funding from IBM Watson Health. His financial interests have been reviewed by Brigham and Women’s Hospital and Mass General Brigham in accordance with their institutional policies. All other authors disclose no conflict of interest.
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