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Staffing levels and hospital mortality in England: a national panel study using routinely collected data
OBJECTIVES: Examine the association between multiple clinical staff levels and case-mix adjusted patient mortality in English hospitals. Most studies investigating the association between hospital staffing levels and mortality have focused on single professional groups, in particular nursing. Howeve...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10193053/ https://www.ncbi.nlm.nih.gov/pubmed/37197808 http://dx.doi.org/10.1136/bmjopen-2022-066702 |
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author | Rubbo, Bruna Saville, Christina Dall'Ora, Chiara Turner, Lesley Jones, Jeremy Ball, Jane Culliford, David Griffiths, Peter |
author_facet | Rubbo, Bruna Saville, Christina Dall'Ora, Chiara Turner, Lesley Jones, Jeremy Ball, Jane Culliford, David Griffiths, Peter |
author_sort | Rubbo, Bruna |
collection | PubMed |
description | OBJECTIVES: Examine the association between multiple clinical staff levels and case-mix adjusted patient mortality in English hospitals. Most studies investigating the association between hospital staffing levels and mortality have focused on single professional groups, in particular nursing. However, single staff group studies might overestimate effects or neglect important contributions to patient safety from other staff groups. DESIGN: Retrospective observational study of routinely available data. SETTING AND PARTICIPANTS: 138 National Health Service hospital trusts that provided general acute adult services in England between 2015 and 2019. OUTCOME MEASURE: Standardised mortality rates were derived from the Summary Hospital level Mortality Indicator data set, with observed deaths as outcome in our models and expected deaths as offset. Staffing levels were calculated as the ratio of occupied beds per staff group. We developed negative binomial random-effects models with trust as random effects. RESULTS: Hospitals with lower levels of medical and allied healthcare professional (AHP) staff (e.g, occupational therapy, physiotherapy, radiography, speech and language therapy) had significantly higher mortality rates (rate ratio: 1.04, 95% CI 1.02 to 1.06, and 1.04, 95% CI 1.02 to 1.06, respectively), while those with lower support staff had lower mortality rates (0.85, 95% CI 0.79 to 0.91 for nurse support, and 1.00, 95% CI 0.99 to 1.00 for AHP support). Estimates of the association between staffing levels and mortality were stronger between-hospitals than within-hospitals, which were not statistically significant in a within–between random effects model. CONCLUSIONS: In additional to medicine and nursing, AHP staffing levels may influence hospital mortality rates. Considering multiple staff groups simultaneously when examining the association between hospital mortality and clinical staffing levels is crucial. TRIAL REGISTRATION NUMBER: NCT04374812. |
format | Online Article Text |
id | pubmed-10193053 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-101930532023-05-19 Staffing levels and hospital mortality in England: a national panel study using routinely collected data Rubbo, Bruna Saville, Christina Dall'Ora, Chiara Turner, Lesley Jones, Jeremy Ball, Jane Culliford, David Griffiths, Peter BMJ Open Health Policy OBJECTIVES: Examine the association between multiple clinical staff levels and case-mix adjusted patient mortality in English hospitals. Most studies investigating the association between hospital staffing levels and mortality have focused on single professional groups, in particular nursing. However, single staff group studies might overestimate effects or neglect important contributions to patient safety from other staff groups. DESIGN: Retrospective observational study of routinely available data. SETTING AND PARTICIPANTS: 138 National Health Service hospital trusts that provided general acute adult services in England between 2015 and 2019. OUTCOME MEASURE: Standardised mortality rates were derived from the Summary Hospital level Mortality Indicator data set, with observed deaths as outcome in our models and expected deaths as offset. Staffing levels were calculated as the ratio of occupied beds per staff group. We developed negative binomial random-effects models with trust as random effects. RESULTS: Hospitals with lower levels of medical and allied healthcare professional (AHP) staff (e.g, occupational therapy, physiotherapy, radiography, speech and language therapy) had significantly higher mortality rates (rate ratio: 1.04, 95% CI 1.02 to 1.06, and 1.04, 95% CI 1.02 to 1.06, respectively), while those with lower support staff had lower mortality rates (0.85, 95% CI 0.79 to 0.91 for nurse support, and 1.00, 95% CI 0.99 to 1.00 for AHP support). Estimates of the association between staffing levels and mortality were stronger between-hospitals than within-hospitals, which were not statistically significant in a within–between random effects model. CONCLUSIONS: In additional to medicine and nursing, AHP staffing levels may influence hospital mortality rates. Considering multiple staff groups simultaneously when examining the association between hospital mortality and clinical staffing levels is crucial. TRIAL REGISTRATION NUMBER: NCT04374812. BMJ Publishing Group 2023-05-17 /pmc/articles/PMC10193053/ /pubmed/37197808 http://dx.doi.org/10.1136/bmjopen-2022-066702 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ. 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 | Health Policy Rubbo, Bruna Saville, Christina Dall'Ora, Chiara Turner, Lesley Jones, Jeremy Ball, Jane Culliford, David Griffiths, Peter Staffing levels and hospital mortality in England: a national panel study using routinely collected data |
title | Staffing levels and hospital mortality in England: a national panel study using routinely collected data |
title_full | Staffing levels and hospital mortality in England: a national panel study using routinely collected data |
title_fullStr | Staffing levels and hospital mortality in England: a national panel study using routinely collected data |
title_full_unstemmed | Staffing levels and hospital mortality in England: a national panel study using routinely collected data |
title_short | Staffing levels and hospital mortality in England: a national panel study using routinely collected data |
title_sort | staffing levels and hospital mortality in england: a national panel study using routinely collected data |
topic | Health Policy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10193053/ https://www.ncbi.nlm.nih.gov/pubmed/37197808 http://dx.doi.org/10.1136/bmjopen-2022-066702 |
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