The Safer Nursing Care Tool (SNCT) is a pivotal system within the NHS, designed to inform crucial decisions regarding nurse staffing levels in hospital wards. Specifically, it aims to guide hospitals in determining the appropriate number of nurses to employ, often referred to as the ‘establishment’. While the SNCT is widely adopted across English hospitals, questions remain about its effectiveness and cost-efficiency in consistently delivering staffing levels that guarantee safe, high-quality patient care.
A comprehensive study was undertaken to rigorously evaluate the Safer Nursing Care Tool. The primary objectives were twofold: first, to ascertain how well the SNCT aligns with professional nursing judgment, and second, to explore various implementation strategies for the SNCT. Furthermore, the research aimed to model the financial implications and patient care outcomes associated with different ward staffing policies derived from the SNCT’s acuity and dependency measurements.
This observational study spanned medical and surgical wards across four NHS hospital trusts. Employing a multifaceted approach that included regression analysis, computer simulations, and economic modeling, the research team assessed three distinct staffing establishment models: a ‘high’ establishment designed to meet demand on 90% of days, a ‘standard’ establishment based on mean demand, and a ‘flexible (low)’ establishment (80% of the mean) intended to be supplemented by redeployed or newly hired staff during peak demand.
The study’s setting encompassed medical and surgical wards within four NHS hospital trusts, providing a diverse representation of hospital environments. Key outcome measures included professional judgments of staffing adequacy, reported instances of omitted care, shifts staffed more than 15% below SNCT-measured requirements, cost per patient-day, and cost per life saved. Data was sourced from hospital administrative systems, staff reports, and national reference costs, ensuring a robust and comprehensive dataset.
The findings were drawn from 81 participating wards (an 85% response rate), linking SNCT ratings and staffing levels across 26,362 ward-days (a 96% response rate). Alarmingly, SNCT measures indicated that 26% of ward-days were understaffed by 15% or more. Interestingly, nurses reported feeling adequately staffed to provide quality care on 78% of shifts, suggesting a potential discrepancy between perceived and tool-measured staffing levels. Statistical analysis revealed that approximately 60 days of observation would be necessary when using the SNCT to set establishments to achieve a 95% confidence interval within one whole-time equivalent nurse either side of the mean.
Crucially, the study established a clear correlation between staffing levels below the SNCT-estimated daily requirement and negative outcomes. Lower staffing levels were associated with reduced odds of nurses reporting ‘enough staff for quality’ and increased reports of missed nursing care. However, the relationship was linear, indicating that staffing above SNCT recommendations correlated with even greater improvements in perceived staffing adequacy and reduced missed care. Simulation experiments highlighted significant risks associated with ‘flexible (low)’ establishments, demonstrating high rates of understaffing and adverse patient outcomes, even when temporary staff were assumed to be readily available. The anticipated cost savings from such flexible models were minimal, particularly when factoring in the necessity for high temporary staff availability. In contrast, ‘high’ establishments led to substantial reductions in understaffing and improved patient outcomes, albeit at higher costs. However, under most modeled scenarios, the cost per life saved with higher staffing levels was less than £30,000, suggesting potential cost-effectiveness.
Despite the valuable insights, the study design as an observational study and the simulated nature of staffing establishment outcomes represent limitations. Moving forward, it is clear that understanding the impact of workload variability on hospital wards is paramount for effective staffing level planning. While the Safer Nursing Care Tool demonstrates correlation with professional judgment, it does not inherently define optimal staffing levels. The study suggests that employing more permanent staff than strictly recommended by SNCT guidelines, aiming to meet demand on most days, could be a cost-effective approach to enhance patient safety and quality of care within the NHS. The perceived cost savings from ‘flexible (low)’ establishments are largely offset by the consequences of inadequate staffing and are further diminished when considering the practicalities of maintaining high temporary staff availability.
Further research is essential to pinpoint definitive cut-off points for required staffing levels and to conduct prospective studies measuring tangible patient outcomes. Comparative analyses of different nurse staffing systems are also feasible and necessary to refine and optimize tools like the Safer Nursing Care Tool for the NHS and beyond.
