Ward staffing guided by a patient classification system: A multi-criteria analysis of fit in three acute hospitals

Aims To assess how well the Safer Nursing Care Tool (SNCT) predicts staffing requirements on hospital wards, and to use professional judgement to generate hypotheses about factors associated with a poor fit. Background The SNCT is widely used in the UK, but there is scant evidence about factors that influence the quality of staffing decisions based upon such patient classification systems. Methods Secondary analysis of data from 69 wards in three acute hospitals to assess the precision of the estimated staffing requirement, variation of estimates, correspondence with professional judgement and achieved staffing levels. Nursing workforce leads suggested factors associated with poor fit, based on the wards that rated worst. Results 39% of wards were frequently understaffed, while frequent overstaffing was less common (12%). 24% of wards needed a sample of over 182 days to estimate the establishment precisely. Potential reasons identified for poor fit included high turnover, older patients, high levels of 1-to-1 specialing, cancer care, small ward size and high within-day variation in demand. Conclusions Using a staffing tool without applying professional judgement or triangulating against other methods can lead to inaccurate estimates of staffing requirements and unsafe staffing levels. Implications for Nursing Management Despite the availability of software to calculate staffing requirements, application of professional judgement remains essential.

Automated summary

The study assessed the accuracy of the Safer Nursing Care Tool in predicting staffing requirements in hospital wards and generated hypotheses about factors associated with a poor fit. Results showed that 39% of wards frequently experienced understaffing, with factors such as high turnover, older patients, and small ward size identified as potential reasons for poor fit.