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Which factors influence the prevalence of institution‐acquired falls? Results from an international, multi‐center, cross‐sectional survey
PURPOSE: Falls are a highly prevalent problem in hospitals and nursing homes with serious negative consequences such as injuries, increased care dependency, or even death. The aim of this study was to provide a comprehensive insight into institution‐acquired fall (IAF) prevalence and risk factors fo...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9542022/ https://www.ncbi.nlm.nih.gov/pubmed/34919335 http://dx.doi.org/10.1111/jnu.12758 |
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author | Hoedl, Manuela Eglseer, Doris Bernet, Niklaus Everink, Irma Gordon, Adam L Lohrmann, Christa Osmancevic, Selvedina Saka, Bülent Schols, Jos M. G. A. Thomann, Silvia Bauer, Silvia |
author_facet | Hoedl, Manuela Eglseer, Doris Bernet, Niklaus Everink, Irma Gordon, Adam L Lohrmann, Christa Osmancevic, Selvedina Saka, Bülent Schols, Jos M. G. A. Thomann, Silvia Bauer, Silvia |
author_sort | Hoedl, Manuela |
collection | PubMed |
description | PURPOSE: Falls are a highly prevalent problem in hospitals and nursing homes with serious negative consequences such as injuries, increased care dependency, or even death. The aim of this study was to provide a comprehensive insight into institution‐acquired fall (IAF) prevalence and risk factors for IAF in a large sample of hospital patients and nursing home residents among five different countries. DESIGN: This study reports the outcome of a secondary data analysis of cross‐sectional data collected in Austria, Switzerland, the Netherlands, Turkey, and the United Kingdom in 2017 and 2018. These data include 58,319 datapoints from hospital patients and nursing home residents. METHODS: Descriptive statistics, statistical tests, logistic regression, and generalized estimating equation (GEE) models were used to analyze the data. FINDINGS: IAF prevalence in hospitals and nursing homes differed significantly between the countries. Turkey (7.7%) had the highest IAF prevalence rate for hospitals, and Switzerland (15.8%) had the highest IAF prevalence rate for nursing homes. In hospitals, our model revealed that IAF prevalence was associated with country, age, care dependency, number of medical diagnoses, surgery in the last two weeks, and fall history factors. In nursing homes, care dependency, diseases of the nervous system, and fall history were identified as significant risk factors for IAF prevalence. CONCLUSIONS: This large‐scale study reveals that the most important IAF risk factor is an existing history of falls, independent of the setting. Whether a previous fall has occurred within the last 12 months is a simple question that should be included on every (nursing) assessment at the time of patient or resident admission. Our results guide the development of tailored prevention programs for persons at risk of falling in hospitals and nursing homes. |
format | Online Article Text |
id | pubmed-9542022 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95420222022-10-14 Which factors influence the prevalence of institution‐acquired falls? Results from an international, multi‐center, cross‐sectional survey Hoedl, Manuela Eglseer, Doris Bernet, Niklaus Everink, Irma Gordon, Adam L Lohrmann, Christa Osmancevic, Selvedina Saka, Bülent Schols, Jos M. G. A. Thomann, Silvia Bauer, Silvia J Nurs Scholarsh Clinical Scholarship PURPOSE: Falls are a highly prevalent problem in hospitals and nursing homes with serious negative consequences such as injuries, increased care dependency, or even death. The aim of this study was to provide a comprehensive insight into institution‐acquired fall (IAF) prevalence and risk factors for IAF in a large sample of hospital patients and nursing home residents among five different countries. DESIGN: This study reports the outcome of a secondary data analysis of cross‐sectional data collected in Austria, Switzerland, the Netherlands, Turkey, and the United Kingdom in 2017 and 2018. These data include 58,319 datapoints from hospital patients and nursing home residents. METHODS: Descriptive statistics, statistical tests, logistic regression, and generalized estimating equation (GEE) models were used to analyze the data. FINDINGS: IAF prevalence in hospitals and nursing homes differed significantly between the countries. Turkey (7.7%) had the highest IAF prevalence rate for hospitals, and Switzerland (15.8%) had the highest IAF prevalence rate for nursing homes. In hospitals, our model revealed that IAF prevalence was associated with country, age, care dependency, number of medical diagnoses, surgery in the last two weeks, and fall history factors. In nursing homes, care dependency, diseases of the nervous system, and fall history were identified as significant risk factors for IAF prevalence. CONCLUSIONS: This large‐scale study reveals that the most important IAF risk factor is an existing history of falls, independent of the setting. Whether a previous fall has occurred within the last 12 months is a simple question that should be included on every (nursing) assessment at the time of patient or resident admission. Our results guide the development of tailored prevention programs for persons at risk of falling in hospitals and nursing homes. John Wiley and Sons Inc. 2021-12-17 2022-07 /pmc/articles/PMC9542022/ /pubmed/34919335 http://dx.doi.org/10.1111/jnu.12758 Text en © 2021 The Authors. Journal of Nursing Scholarship published by Wiley Periodicals LLC on behalf of Sigma Theta Tau International. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Clinical Scholarship Hoedl, Manuela Eglseer, Doris Bernet, Niklaus Everink, Irma Gordon, Adam L Lohrmann, Christa Osmancevic, Selvedina Saka, Bülent Schols, Jos M. G. A. Thomann, Silvia Bauer, Silvia Which factors influence the prevalence of institution‐acquired falls? Results from an international, multi‐center, cross‐sectional survey |
title | Which factors influence the prevalence of institution‐acquired falls? Results from an international, multi‐center, cross‐sectional survey |
title_full | Which factors influence the prevalence of institution‐acquired falls? Results from an international, multi‐center, cross‐sectional survey |
title_fullStr | Which factors influence the prevalence of institution‐acquired falls? Results from an international, multi‐center, cross‐sectional survey |
title_full_unstemmed | Which factors influence the prevalence of institution‐acquired falls? Results from an international, multi‐center, cross‐sectional survey |
title_short | Which factors influence the prevalence of institution‐acquired falls? Results from an international, multi‐center, cross‐sectional survey |
title_sort | which factors influence the prevalence of institution‐acquired falls? results from an international, multi‐center, cross‐sectional survey |
topic | Clinical Scholarship |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9542022/ https://www.ncbi.nlm.nih.gov/pubmed/34919335 http://dx.doi.org/10.1111/jnu.12758 |
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