Development and Validation of a Fall Prevention Efficiency Scale.
Journal
Journal of patient safety
ISSN: 1549-8425
Titre abrégé: J Patient Saf
Pays: United States
ID NLM: 101233393
Informations de publication
Date de publication:
01 03 2022
01 03 2022
Historique:
pubmed:
23
1
2021
medline:
24
2
2022
entrez:
22
1
2021
Statut:
ppublish
Résumé
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. 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. 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. 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.
Identifiants
pubmed: 33480645
doi: 10.1097/PTS.0000000000000811
pii: 01209203-202203000-00004
pmc: PMC8292432
mid: NIHMS1651285
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
94-101Subventions
Organisme : AHRQ HHS
ID : R18 HS025128
Pays : United States
Informations de copyright
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.
Déclaration de conflit d'intérêts
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.
Références
Inouye SK, Brown CJ, Tinetti ME. Medicare nonpayment, hospital falls, and unintended consequences. N Engl J Med . 2009;360:2390–2393.
Tzeng HM, Yin CY. Patient engagement in hospital fall prevention. Nurs Econ . 2015;33:326–334.
Dykes PC, Carroll DL, Hurley AC, et al. Fall prevention in acute care hospitals: a randomized trial. JAMA . 2010;304:1912–1918.
Morse JM, Morse RM, Tylko SJ. Development of a scale to identify the fall-prone patient. Can J Aging . 1989;8:366–377.
Katsulis Z, Ergai A, Leung WY, et al. Iterative user centered design for development of a patient-centered fall prevention toolkit. Appl Ergon . 2016;56:117–126.
Duckworth M, Adelman J, Belategui K, et al. Assessing the effectiveness of engaging patients and their families in the three-step fall prevention process across modalities of an evidence-based fall prevention toolkit: an implementation science study. J Med Internet Res . 2019;21:e10008.
Leung WY, Adelman J, Bates DW, et al. Validating fall prevention icons to support patient-centered education. J Patient Saf . 2017.
Duckworth M, Leung E, Fuller T, et al. Nurse, patient, and care partner perceptions of a personalized safety plan screensaver. J Gerontol Nurs . 2017;43:15–22.
Denzin NK, Lincoln YS. Handbook of Qualitative Research . Thousand Oaks, CA: Sage; 1994.
Miles MB, Huberman AM. Qualitative Data Analysis: An Expanded Sourcebook . 2nd ed. Thousand Oaks: Sage; 1994.
Waltz CF, Strickland OL, Lenz ER. Measurement in Nursing and Health Research . 4th ed. New York: Springer; 2010.
Nunnally JC, Bernstein IH. Psychometric Theory . 3rd ed. New York: McGraw Hill Book Company, Inc.; 1994.
Knapp TR, Brown JK. Ten measurement commandments that often should be broken. Res Nurs Health . 1995;18:465–469.
Hurley AC, Volicer BJ, Hanrahan PA, et al. Assessment of discomfort in advanced Alzheimer patients. Res Nurs Health . 1992;15:369–377.
Mahoney EK, Hurley AC, Volicer L, et al. Development and testing of the resistiveness to care scale. Res Nurs Health . 1999;22:27–38.
Dykes PC, Rothschild JM, Hurley AC. Recovered medical error inventory. J Nurs Scholarsh . 2010;42:314–318.
Dykes PC, Carroll DL, McColgan K, et al. Scales for assessing self-efficacy of nurses and assistants for preventing falls. J Adv Nurs . 2011;67:438–449.
Trint: Automated Transcription of Audio and Video . London, United Kingdom: Trint Software Company; 2018.
Microsoft Word . Redman, WA: Microsoft; 2016.
NVivo Qualitative Data Analsis Software . Doncaster, Australia: QSR International Pty Ltd.; 2002.
Harris PA, Taylor R, Thiekle R. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform . 2008;42:377–381.
SPSS-IBM . New York: SPSS-IBM; 2017.
Teh RC, Mahajan N, Visvanathan R, et al. Clinical effectiveness of and attitudes and beliefs of health professionals towards the use of health technology in falls prevention among older adults. Int J Evid Based Healthc . 2015;13:213–223.
Higgins LW, Shovel JA, Bilderback AL, et al. Hospital Nurses’ work activity in a technology-rich environment: a triangulated quality improvement assessment. J Nurs Care Qual . 2017;32:208–217.
Dykes PC, Carroll DL, Hurley AC, et al. Why do patients in acute care hospitals fall? Can falls be prevented? J Nurs Adm . 2009;39:299–304.
Dykes PC, Bogaisky M, Carter EJ, et al. Development and validation of a fall prevention knowledge test. J Am Geriatr Soc . 2019;67:133–138.
Dykes PC. In: Dykes PC, ed. A Patient-Centered Fall Prevention Toolkit ( www.falltips.org ) . Boston, MA: Brigham and Women’s Hospital; 2020. Accessed August 4, 2020).
Carman KL, Dardess P, Maurer M, et al. Patient and family engagement: a framework for understanding the elements and developing interventions and policies. Health Aff (Millwood) . 2013;32:223–231.
Opsahl AG, Ebright P, Cangany M, et al. Outcomes of adding patient and family engagement education to fall prevention bundled interventions. J Nurs Care Qual . 2017;32:252–258.
Hendrich A, Chow MP, Skierczynski BA, et al. A 36-hospital time and motion study: how do medical-surgical nurses spend their time? Perm J . 2008;12:25–34.