The association between nurse staffing and inpatient mortality: a shift-level retrospective longitudinal study
The association between nurse staffing and inpatient mortality: a shift-level retrospective longitudinal study
Background: worldwide, hospitals face pressure to reduce costs. Some respond by working with a reduced number of nurses or less qualified nursing staff. Objective: this study aims at examining the relationship between mortality and patient exposure to shifts with low or high nurse staffing. Methods: this longitudinal study used routine shift-, unit-, and patient-level data for three years (2015–2017) from one Swiss university hospital. Data from 55 units, 79,893 adult inpatients and 3646 nurses (2670 registered nurses, 438 licensed practical nurses, and 538 unlicensed and administrative personnel) were analyzed. After developing a staffing model to identify high- and low-staffed shifts, we fitted logistic regression models to explore associations between nurse staffing and mortality. Results: exposure to shifts with high levels of registered nurses had lower odds of mortality by 8.7% [odds ratio 0.91 95% CI 0.89–0.93]. Conversely, low staffing was associated with higher odds of mortality by 10% [odds ratio 1.10 95% CI 1.07–1.13]. The associations between mortality and staffing by other groups was less clear. For example, both high and low staffing of unlicensed and administrative personnel were associated with higher mortality, respectively 1.03 [95% CI 1.01–1.04] and 1.04 [95% CI 1.03–1.06]. Discussion and implications: this patient-level longitudinal study suggests a relationship between registered nurses staffing levels and mortality. Higher levels of registered nurses positively impact patient outcome (i.e. lower odds of mortality) and lower levels negatively (i.e. higher odds of mortality). Contributions of the three other groups to patient safety is unclear from these results. Therefore, substitution of either group for registered nurses is not recommended.
Electronic health records, Mortality, Nurses, Patient safety, Personnel staffing and scheduling, Routinely collected health data
Musy, Sarah N.
0c247df2-a393-4a58-be0d-7d1cb4ead9c9
Endrich, Olga
a2d7bb06-f801-4540-9e54-a108c87bcd22
Leichtle, Alexander B.
b93ba47e-c6b2-498f-ad28-08d03a1ab19c
Griffiths, Peter
ac7afec1-7d72-4b83-b016-3a43e245265b
Nakas, Christos T.
c5fa3862-a8bf-4a27-9923-b0b9e87abcc4
Simon, Michael
6e9ad30e-c22f-455a-945e-98d77dcec479
1 August 2021
Musy, Sarah N.
0c247df2-a393-4a58-be0d-7d1cb4ead9c9
Endrich, Olga
a2d7bb06-f801-4540-9e54-a108c87bcd22
Leichtle, Alexander B.
b93ba47e-c6b2-498f-ad28-08d03a1ab19c
Griffiths, Peter
ac7afec1-7d72-4b83-b016-3a43e245265b
Nakas, Christos T.
c5fa3862-a8bf-4a27-9923-b0b9e87abcc4
Simon, Michael
6e9ad30e-c22f-455a-945e-98d77dcec479
Musy, Sarah N., Endrich, Olga, Leichtle, Alexander B., Griffiths, Peter, Nakas, Christos T. and Simon, Michael
(2021)
The association between nurse staffing and inpatient mortality: a shift-level retrospective longitudinal study.
International Journal of Nursing Studies, 120, [103950].
(doi:10.1016/j.ijnurstu.2021.103950).
Abstract
Background: worldwide, hospitals face pressure to reduce costs. Some respond by working with a reduced number of nurses or less qualified nursing staff. Objective: this study aims at examining the relationship between mortality and patient exposure to shifts with low or high nurse staffing. Methods: this longitudinal study used routine shift-, unit-, and patient-level data for three years (2015–2017) from one Swiss university hospital. Data from 55 units, 79,893 adult inpatients and 3646 nurses (2670 registered nurses, 438 licensed practical nurses, and 538 unlicensed and administrative personnel) were analyzed. After developing a staffing model to identify high- and low-staffed shifts, we fitted logistic regression models to explore associations between nurse staffing and mortality. Results: exposure to shifts with high levels of registered nurses had lower odds of mortality by 8.7% [odds ratio 0.91 95% CI 0.89–0.93]. Conversely, low staffing was associated with higher odds of mortality by 10% [odds ratio 1.10 95% CI 1.07–1.13]. The associations between mortality and staffing by other groups was less clear. For example, both high and low staffing of unlicensed and administrative personnel were associated with higher mortality, respectively 1.03 [95% CI 1.01–1.04] and 1.04 [95% CI 1.03–1.06]. Discussion and implications: this patient-level longitudinal study suggests a relationship between registered nurses staffing levels and mortality. Higher levels of registered nurses positively impact patient outcome (i.e. lower odds of mortality) and lower levels negatively (i.e. higher odds of mortality). Contributions of the three other groups to patient safety is unclear from these results. Therefore, substitution of either group for registered nurses is not recommended.
Text
1-s2.0-S0020748921000936-main
- Version of Record
More information
Accepted/In Press date: 14 April 2021
e-pub ahead of print date: 25 April 2021
Published date: 1 August 2021
Additional Information:
Funding Information:
We would like to thank Lars Neeb, Barbara Ammann, and Wilco Laan from Inselspital, Bern University Hospital and Elias Panizza from Wigasoft for helping us to understand the nurse staffing system and for delivering additional variables necessary to conduct the analysis. We would also like to thank Chris Shultis for professional editing of the manuscript. No external funding.
Publisher Copyright:
© 2021 The Authors
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
Keywords:
Electronic health records, Mortality, Nurses, Patient safety, Personnel staffing and scheduling, Routinely collected health data
Identifiers
Local EPrints ID: 453521
URI: http://eprints.soton.ac.uk/id/eprint/453521
ISSN: 0020-7489
PURE UUID: 10d6718d-acd5-41af-95c1-5897653a6f79
Catalogue record
Date deposited: 18 Jan 2022 18:10
Last modified: 18 Mar 2024 03:17
Export record
Altmetrics
Contributors
Author:
Sarah N. Musy
Author:
Olga Endrich
Author:
Alexander B. Leichtle
Author:
Christos T. Nakas
Author:
Michael Simon
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics
