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Nursing workforce allocation in the intensive care units of COVID‐19‐designated hospitals: A nationwide cross‐sectional survey in China
AIM: To explore the nursing workforce allocation in intensive care units (ICUs) of COVID‐19‐designated hospitals during the epidemic peak in China. DESIGN: A nationwide cross‐sectional online survey. METHODS: A total of 37 head nurses and 262 frontline nurses in 37 ICUs of COVID‐19‐designated tertia...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415983/ https://www.ncbi.nlm.nih.gov/pubmed/37247342 http://dx.doi.org/10.1002/nop2.1830 |
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author | Ren, Hong‐fei Liu, Chang‐qing Chen, Feng‐jiao He, Ling‐xiao Zhang, Ming‐guang Gu, Bo Zhu, Hong Jiang, Yan |
author_facet | Ren, Hong‐fei Liu, Chang‐qing Chen, Feng‐jiao He, Ling‐xiao Zhang, Ming‐guang Gu, Bo Zhu, Hong Jiang, Yan |
author_sort | Ren, Hong‐fei |
collection | PubMed |
description | AIM: To explore the nursing workforce allocation in intensive care units (ICUs) of COVID‐19‐designated hospitals during the epidemic peak in China. DESIGN: A nationwide cross‐sectional online survey. METHODS: A total of 37 head nurses and 262 frontline nurses in 37 ICUs of COVID‐19‐designated tertiary hospitals located in 22 cities of China were surveyed. The self‐reported human resource allocation questionnaire was used to assess the nursing workforce allocation. RESULTS: The average patient‐to‐nurse ratio was 1.89 ± 1.14, and the median working hours per shift was 5 h. The top four majors of front‐line nurses in ICUs were respiratory (31.30%), lemology (27.86%), intensive care (21.76%) and emergency (17.18%). We also found that a smaller average patient‐to‐nurse ratio (odds ratio [OR]: 0.328, 95% CI: 0.108, 1.000), longer average weekly rest time per person (OR: 0.193, 95% CI: 0.051, 0.729) and larger proportion of 6–9 working years (OR: 0.002, 95% CI: 0.001, 1.121) decreased the occurrence of nursing adverse events. |
format | Online Article Text |
id | pubmed-10415983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104159832023-08-12 Nursing workforce allocation in the intensive care units of COVID‐19‐designated hospitals: A nationwide cross‐sectional survey in China Ren, Hong‐fei Liu, Chang‐qing Chen, Feng‐jiao He, Ling‐xiao Zhang, Ming‐guang Gu, Bo Zhu, Hong Jiang, Yan Nurs Open Empirical Research Quantitative AIM: To explore the nursing workforce allocation in intensive care units (ICUs) of COVID‐19‐designated hospitals during the epidemic peak in China. DESIGN: A nationwide cross‐sectional online survey. METHODS: A total of 37 head nurses and 262 frontline nurses in 37 ICUs of COVID‐19‐designated tertiary hospitals located in 22 cities of China were surveyed. The self‐reported human resource allocation questionnaire was used to assess the nursing workforce allocation. RESULTS: The average patient‐to‐nurse ratio was 1.89 ± 1.14, and the median working hours per shift was 5 h. The top four majors of front‐line nurses in ICUs were respiratory (31.30%), lemology (27.86%), intensive care (21.76%) and emergency (17.18%). We also found that a smaller average patient‐to‐nurse ratio (odds ratio [OR]: 0.328, 95% CI: 0.108, 1.000), longer average weekly rest time per person (OR: 0.193, 95% CI: 0.051, 0.729) and larger proportion of 6–9 working years (OR: 0.002, 95% CI: 0.001, 1.121) decreased the occurrence of nursing adverse events. John Wiley and Sons Inc. 2023-05-29 /pmc/articles/PMC10415983/ /pubmed/37247342 http://dx.doi.org/10.1002/nop2.1830 Text en © 2023 The Authors. Nursing Open published by John Wiley & Sons Ltd. 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 | Empirical Research Quantitative Ren, Hong‐fei Liu, Chang‐qing Chen, Feng‐jiao He, Ling‐xiao Zhang, Ming‐guang Gu, Bo Zhu, Hong Jiang, Yan Nursing workforce allocation in the intensive care units of COVID‐19‐designated hospitals: A nationwide cross‐sectional survey in China |
title | Nursing workforce allocation in the intensive care units of COVID‐19‐designated hospitals: A nationwide cross‐sectional survey in China |
title_full | Nursing workforce allocation in the intensive care units of COVID‐19‐designated hospitals: A nationwide cross‐sectional survey in China |
title_fullStr | Nursing workforce allocation in the intensive care units of COVID‐19‐designated hospitals: A nationwide cross‐sectional survey in China |
title_full_unstemmed | Nursing workforce allocation in the intensive care units of COVID‐19‐designated hospitals: A nationwide cross‐sectional survey in China |
title_short | Nursing workforce allocation in the intensive care units of COVID‐19‐designated hospitals: A nationwide cross‐sectional survey in China |
title_sort | nursing workforce allocation in the intensive care units of covid‐19‐designated hospitals: a nationwide cross‐sectional survey in china |
topic | Empirical Research Quantitative |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415983/ https://www.ncbi.nlm.nih.gov/pubmed/37247342 http://dx.doi.org/10.1002/nop2.1830 |
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