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Performance of the Safer Nursing Care Tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study
OBJECTIVES: The best way to determine nurse staffing requirements on hospital wards is unclear. This study explores the precision of estimates of nurse staffing requirements made using the Safer Nursing Care Tool (SNCT) patient classification system for different sample sizes and investigates whethe...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7232629/ https://www.ncbi.nlm.nih.gov/pubmed/32414828 http://dx.doi.org/10.1136/bmjopen-2019-035828 |
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author | Griffiths, Peter Saville, Christina Ball, Jane Culliford, David Pattison, Natalie Monks, Thomas |
author_facet | Griffiths, Peter Saville, Christina Ball, Jane Culliford, David Pattison, Natalie Monks, Thomas |
author_sort | Griffiths, Peter |
collection | PubMed |
description | OBJECTIVES: The best way to determine nurse staffing requirements on hospital wards is unclear. This study explores the precision of estimates of nurse staffing requirements made using the Safer Nursing Care Tool (SNCT) patient classification system for different sample sizes and investigates whether recommended staff levels correspond with professional judgements of adequate staffing. DESIGN: Observational study linking datasets of staffing requirements (estimated using a tool) to professional judgements of adequate staffing. Multilevel logistic regression modelling. SETTING: 81 medical/surgical units in four acute care hospitals. PARTICIPANTS: 22 364 unit days where staffing levels and SNCT ratings were linked to nurse reports of "enough staff for quality". PRIMARY OUTCOME MEASURES: SNCT-estimated staffing requirements and nurses’ assessments of staffing adequacy. RESULTS: The recommended minimum sample of 20 days allowed the required number to employ (the establishment) to be estimated with a mean precision (defined as half the width of the CI as a percentage of the mean) of 4.1%. For most units, much larger samples were required to estimate establishments within ±1 whole time equivalent staff member. When staffing was lower than that required according to the SNCT, for each hour per patient day of registered nurse staffing below the required staffing level, the odds of nurses reporting that there were enough staff to provide quality care were reduced by 11%. Correspondingly, the odds of nurses reporting that necessary nursing care was left undone were increased by 14%. No threshold indicating an optimal staffing level was observed. Surgical specialty, patient turnover and more single rooms were associated with lower odds of staffing adequacy. CONCLUSIONS: The SNCT can provide reliable estimates of the number of nurses to employ on a unit, but larger samples than the recommended minimum are usually required. The SNCT provides a measure of nursing workload that correlates with professional judgements, but the recommended staffing levels may not be optimal. Some important sources of systematic variations in staffing requirements for some units are not accounted for. SNCT measurements are a potentially useful adjunct to professional judgement but cannot replace it. TRIAL REGISTRATION NUMBER: ISRCTN12307968. |
format | Online Article Text |
id | pubmed-7232629 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-72326292020-05-19 Performance of the Safer Nursing Care Tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study Griffiths, Peter Saville, Christina Ball, Jane Culliford, David Pattison, Natalie Monks, Thomas BMJ Open Nursing OBJECTIVES: The best way to determine nurse staffing requirements on hospital wards is unclear. This study explores the precision of estimates of nurse staffing requirements made using the Safer Nursing Care Tool (SNCT) patient classification system for different sample sizes and investigates whether recommended staff levels correspond with professional judgements of adequate staffing. DESIGN: Observational study linking datasets of staffing requirements (estimated using a tool) to professional judgements of adequate staffing. Multilevel logistic regression modelling. SETTING: 81 medical/surgical units in four acute care hospitals. PARTICIPANTS: 22 364 unit days where staffing levels and SNCT ratings were linked to nurse reports of "enough staff for quality". PRIMARY OUTCOME MEASURES: SNCT-estimated staffing requirements and nurses’ assessments of staffing adequacy. RESULTS: The recommended minimum sample of 20 days allowed the required number to employ (the establishment) to be estimated with a mean precision (defined as half the width of the CI as a percentage of the mean) of 4.1%. For most units, much larger samples were required to estimate establishments within ±1 whole time equivalent staff member. When staffing was lower than that required according to the SNCT, for each hour per patient day of registered nurse staffing below the required staffing level, the odds of nurses reporting that there were enough staff to provide quality care were reduced by 11%. Correspondingly, the odds of nurses reporting that necessary nursing care was left undone were increased by 14%. No threshold indicating an optimal staffing level was observed. Surgical specialty, patient turnover and more single rooms were associated with lower odds of staffing adequacy. CONCLUSIONS: The SNCT can provide reliable estimates of the number of nurses to employ on a unit, but larger samples than the recommended minimum are usually required. The SNCT provides a measure of nursing workload that correlates with professional judgements, but the recommended staffing levels may not be optimal. Some important sources of systematic variations in staffing requirements for some units are not accounted for. SNCT measurements are a potentially useful adjunct to professional judgement but cannot replace it. TRIAL REGISTRATION NUMBER: ISRCTN12307968. BMJ Publishing Group 2020-05-15 /pmc/articles/PMC7232629/ /pubmed/32414828 http://dx.doi.org/10.1136/bmjopen-2019-035828 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Nursing Griffiths, Peter Saville, Christina Ball, Jane Culliford, David Pattison, Natalie Monks, Thomas Performance of the Safer Nursing Care Tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study |
title | Performance of the Safer Nursing Care Tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study |
title_full | Performance of the Safer Nursing Care Tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study |
title_fullStr | Performance of the Safer Nursing Care Tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study |
title_full_unstemmed | Performance of the Safer Nursing Care Tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study |
title_short | Performance of the Safer Nursing Care Tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study |
title_sort | performance of the safer nursing care tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study |
topic | Nursing |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7232629/ https://www.ncbi.nlm.nih.gov/pubmed/32414828 http://dx.doi.org/10.1136/bmjopen-2019-035828 |
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