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Nurse staffing levels, missed vital signs observations and mortality in hospital wards: modelling the consequences and costs of variations in nurse staffing and skill mix. Retrospective observational study using routinely collected data

Nurse staffing levels, missed vital signs observations and mortality in hospital wards: modelling the consequences and costs of variations in nurse staffing and skill mix. Retrospective observational study using routinely collected data
Nurse staffing levels, missed vital signs observations and mortality in hospital wards: modelling the consequences and costs of variations in nurse staffing and skill mix. Retrospective observational study using routinely collected data
The NHS faces pressure to maintain the quality and safety of care in hospitals at the same or less cost than previously. The quality of nursing care and the potential for inadequate nursing to do patients harm has emerged as an issue in numerous reports into failings in NHS hospitals. Failure to ensure adequate nurse staffing has frequently been cited as a causal factor. This is consistent with many studies showing associations between low nurse staffing levels and increased mortality. However, because nurse staffing is only one factor affecting mortality, it is difficult to use these findings directly to show the effects of low staffing or to plan staffing requirements. Recent draft guidelines from NICE highlighted the need for more evidence derived from the UK and for indicators that directly reflect safe nurse staffing. Recently, studies have begun to explore missed nursing care as a key factor leading to adverse patient outcomes. Missed opportunities to observe and act on deterioration have been implicated in preventable deaths and studies have shown that low staffing levels are associated with nurse reported missed care. Our study examines the association between nurse staffing levels, and missed or delayed recording of vital signs using objective measures derived from a clinical information system. The study also explores associations between nurse staffing and adverse patient outcomes: unanticipated ICU admission, cardiac arrest and mortality. The study will model the costs and consequences of different staffing policies to achieve acceptable rates of observation and assess whether missed observations could be used as a leading indicator of nurse staffing adequacy by testing the extent to which missed observations mediate any relationship between staffing and outcomes. This retrospective observational study uses routinely collected data on ward and shift level nurse staffing, vital signs observations and patient outcomes in 32 general wards in Portsmouth Hospitals NHS Trust. Data will be derived from a database of records made using the VitalPAC system which nurses use to record clinical data on hand held devices at the bedside. Staffing data from approximately 100,000 shifts is available for the study. These data will be linked to records of all nursing staff working on a given shift; patient data derived from the hospital patient administration system; cardiac arrest database; ICU admission database; and hospital laboratory records. Relationships between registered nurse and health care assistant staffing levels and outcomes will be explored using a hierarchical generalized linear mixed model, which allows for clustering of observation in individuals, shifts and wards. We will assess whether there is evidence that missed care mediates any relationship between staffing and adverse outcomes. Parameters from regression models will be used to estimate staffing required on different wards to achieve specified levels of compliance with vital signs observations. We will assess the costs and consequences of different staffing policies to achieve specific outcomes, determined after consultation with patients, public and clinical stakeholders. The study will give guidance on the relative importance and costs of different nursing skill mixes in achieving consistent observations and safe care and determine whether the rate of missed vital signs observations could be used as an indicator of safe staffing.
2050-4349
1-120
Griffiths, Peter
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Ball, Jane
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Bloor, Karen
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Bohning, Dankmar
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Briggs, Jim
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Dall'ora, Chiara
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de Longh, Anya
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Jones, Jeremy
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Kovacs, Caroline
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Maruotti, Antonello
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Prytherch, David
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Recio Saucedo, Alejandra
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Redfern, Oliver
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Schmidt, Paul
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Sinden, Nicky
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Smith, Gary
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Griffiths, Peter
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Ball, Jane
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Bloor, Karen
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Bohning, Dankmar
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Briggs, Jim
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Dall'ora, Chiara
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de Longh, Anya
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Jones, Jeremy
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Kovacs, Caroline
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Maruotti, Antonello
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Prytherch, David
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Recio Saucedo, Alejandra
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Redfern, Oliver
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Schmidt, Paul
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Sinden, Nicky
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Smith, Gary
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Griffiths, Peter, Ball, Jane, Bloor, Karen, Bohning, Dankmar, Briggs, Jim, Dall'ora, Chiara, de Longh, Anya, Jones, Jeremy, Kovacs, Caroline, Maruotti, Antonello, Prytherch, David, Recio Saucedo, Alejandra, Redfern, Oliver, Schmidt, Paul, Sinden, Nicky and Smith, Gary (2018) Nurse staffing levels, missed vital signs observations and mortality in hospital wards: modelling the consequences and costs of variations in nurse staffing and skill mix. Retrospective observational study using routinely collected data. Health Services and Delivery Research, 6 (38), 1-120. (doi:10.3310/hsdr06380).

Record type: Article

Abstract

The NHS faces pressure to maintain the quality and safety of care in hospitals at the same or less cost than previously. The quality of nursing care and the potential for inadequate nursing to do patients harm has emerged as an issue in numerous reports into failings in NHS hospitals. Failure to ensure adequate nurse staffing has frequently been cited as a causal factor. This is consistent with many studies showing associations between low nurse staffing levels and increased mortality. However, because nurse staffing is only one factor affecting mortality, it is difficult to use these findings directly to show the effects of low staffing or to plan staffing requirements. Recent draft guidelines from NICE highlighted the need for more evidence derived from the UK and for indicators that directly reflect safe nurse staffing. Recently, studies have begun to explore missed nursing care as a key factor leading to adverse patient outcomes. Missed opportunities to observe and act on deterioration have been implicated in preventable deaths and studies have shown that low staffing levels are associated with nurse reported missed care. Our study examines the association between nurse staffing levels, and missed or delayed recording of vital signs using objective measures derived from a clinical information system. The study also explores associations between nurse staffing and adverse patient outcomes: unanticipated ICU admission, cardiac arrest and mortality. The study will model the costs and consequences of different staffing policies to achieve acceptable rates of observation and assess whether missed observations could be used as a leading indicator of nurse staffing adequacy by testing the extent to which missed observations mediate any relationship between staffing and outcomes. This retrospective observational study uses routinely collected data on ward and shift level nurse staffing, vital signs observations and patient outcomes in 32 general wards in Portsmouth Hospitals NHS Trust. Data will be derived from a database of records made using the VitalPAC system which nurses use to record clinical data on hand held devices at the bedside. Staffing data from approximately 100,000 shifts is available for the study. These data will be linked to records of all nursing staff working on a given shift; patient data derived from the hospital patient administration system; cardiac arrest database; ICU admission database; and hospital laboratory records. Relationships between registered nurse and health care assistant staffing levels and outcomes will be explored using a hierarchical generalized linear mixed model, which allows for clustering of observation in individuals, shifts and wards. We will assess whether there is evidence that missed care mediates any relationship between staffing and adverse outcomes. Parameters from regression models will be used to estimate staffing required on different wards to achieve specified levels of compliance with vital signs observations. We will assess the costs and consequences of different staffing policies to achieve specific outcomes, determined after consultation with patients, public and clinical stakeholders. The study will give guidance on the relative importance and costs of different nursing skill mixes in achieving consistent observations and safe care and determine whether the rate of missed vital signs observations could be used as an indicator of safe staffing.

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Nurse staffing levels, missed vital signs observations and mortality in hospital wards: retrospective longitudinal observational study using routinely collected data - Final report - Accepted Manuscript
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More information

Accepted/In Press date: 21 March 2018
Published date: December 2018

Identifiers

Local EPrints ID: 419217
URI: http://eprints.soton.ac.uk/id/eprint/419217
ISSN: 2050-4349
PURE UUID: 49eeea39-218d-4d90-a9d0-62eff695a5b2
ORCID for Peter Griffiths: ORCID iD orcid.org/0000-0003-2439-2857
ORCID for Jane Ball: ORCID iD orcid.org/0000-0002-8655-2994
ORCID for Dankmar Bohning: ORCID iD orcid.org/0000-0003-0638-7106
ORCID for Chiara Dall'ora: ORCID iD orcid.org/0000-0002-6858-3535
ORCID for Alejandra Recio Saucedo: ORCID iD orcid.org/0000-0003-2823-4573

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Date deposited: 09 Apr 2018 16:30
Last modified: 22 Nov 2021 03:18

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Contributors

Author: Peter Griffiths ORCID iD
Author: Jane Ball ORCID iD
Author: Karen Bloor
Author: Dankmar Bohning ORCID iD
Author: Jim Briggs
Author: Chiara Dall'ora ORCID iD
Author: Anya de Longh
Author: Jeremy Jones
Author: Caroline Kovacs
Author: Antonello Maruotti
Author: David Prytherch
Author: Oliver Redfern
Author: Paul Schmidt
Author: Nicky Sinden
Author: Gary Smith

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