Skip to main navigationSkip to main content
The University of Southampton
Health SciencesOur research

Research project: 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 - Dormant

Currently Active: 
No

The NHS in England, like many other healthcare systems, is facing intense pressure to maintain the quality and safety of care provided in hospitals at the same or less cost than in previous years. The quality of nursing care - and the potential for inadequate nursing care to do patients great harm - has emerged as a factor in several reports into failings in NHS hospitals. These reports have often noted that failing to ensure adequate nurse staffing was an important issue that was associated with poor care and preventable deaths. Recently studies have begun to explore missed nursing care, defined as nursing care that was needed but not done, as a key factor leading to negative patient outcomes. This study aims to explore how nurse staffing levels are related to missed or delayed vital signs observation (that is, measurements of blood pressure, pulse and respirations) using direct measures of the timing of observations recorded in a clinical information system and whether these missed observations contribute to patient deaths. The study will give guidance on the relative importance and costs of different nursing skill mixes and staffing levels in achieving consistent observations and safe care.

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 care to do patients harm has emerged as an issue in numerous reports into failings in NHS hospitals in England. Failure to ensure adequate nurse staffing has frequently been cited as a causal factor. (1, 2) This is consistent with many studies showing associations between low levels of nurse staffing and increased mortality. (3, 4) 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 on nursing care delivery or to guide staffing decisions. The recent NICE draft guidelines on safe staffing highlighted the need for more evidence derived from the UK and for indicators that more 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 hospital deaths (5, 6) and studies have shown that low staffing levels are associated with nurse reported missed care. (7, 8)

The current study examines the association between registered nurse and care assistant 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 42 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.These data will be linked to the following: records of all nursing staff working on a given shift (including bank and agency staff); patient data derived from the hospital patient administration system (PAS); cardiac arrest database; ICU admission database; and hospital laboratory records. Staffing data is available from 2012 onwards, with data from approximately 100,000 shifts available for the study. 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 economic implications of different staffing models by estimating costs of differing staffing policies to achieve specified 0utcomes, determined through consultation with patients, the 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. NIHR research project details.

 

Associated research themes

Health Workforce & Systems

Related research groups

Health Work and Systems

Project Team

Ms Jane Ball

Professor Karen Bloor (University of York)

Dr Jim Briggs (University of Portsmouth)

Dr David Prytherch (Portsmouth Hospitals NHS Trust)

Professor Gary Smith (Freelance consultant)

Dr Paul Meredith (Portsmouth Hospitals NHS Trust) 

Miss Nicola Sinden (Portsmouth Hospitals NHS Trust) 

Professor Dankmar Böhning (University of Southampton)

Dr Antonello Maruotti (University of Southampton)

Miss Anya de Longh (Independent patient representative)

Dr Paul Schmidt (Portsmouth Hospitals NHS Trust)

Dr Alex Recio Saucedo

Chiara Dall’Ora

Project Funder

NIHR HS&DR programme

Research Groups

Health Work and Systems

CLAHRC Fundamental Care Theme

Share this research project Share this on Facebook Share this on Twitter Share this on Weibo
Privacy Settings