Clinical Trial Summary
Background: The NHS is facing significant challenges in recruiting and retaining staff,
particularly registered nurses (RNs). Recruiting unregistered staff is often adopted as a
solution to the RN shortage; however recent research found a negative effect of low RN
staffing levels on mortality with no evidence that high levels of assistant staff could
mitigate the increased risk. Economic modelling suggested that increases in skill mix were
potentially cost-effective, but these findings derive from a single NHS hospital Trust with
limited cost and outcome data.
Aims and objectives: This project aims to estimate the consequences, costs and cost
effectiveness of variation in the size and composition of the staff on hospital wards in
England. In order to provide estimates that are more likely to apply across the NHS, this
study will include at least four hospitals and consider a wider range of outcomes and sources
of costs, including death within 30 days of admission, adverse events such as infections,
length of hospital stay, readmissions and rates of staff sickness.
Methods: This retrospective longitudinal observational study will use routinely collected
data on ward and shift level nurse staffing, and patient outcomes. Data will be derived from
the E-Roster systems, used by hospitals to record all planned and worked shifts. The
investigators will consider all rostered direct care staff. These data will be linked to
patient data derived from the hospital patient administration system (PAS); and other
clinical systems and databases of adverse events (e.g. datix). Relationships between RN and
assistant staffing levels and outcomes will be explored using survival models incorporating
mixed effects. The investigators will use the results of these analyses to model the costs
and consequences of different staffing configurations and to estimate the incremental
cost-effectiveness associated with change. Our study will provide evidence to inform staffing
levels and skill mix planning in the NHS, highlighting potential cost savings, and offering
improved patient safety and reduced adverse staff outcomes.
Note that for this study, "Study start" means the date the first hospital Trust was
recruited. "Primary completion" is the date by which the investigators anticipate data
analysis for the primary outcomes will be complete. "Study completion" is the data by which
investigators anticipate data analysis for secondary outcomes will be complete.
The investigators cannot name the hospital Trusts participating because the investigators do
not have their consent and this would breach GDPR.