With ward staffing costs consuming over a third of the annual pay bill, trusts know how important it is to make the most of nursing resources.
The Audit Commission’s trust practice is doing a benchmarking exercise that has so far helped 54 trusts and a growing number of primary care trusts understand how their staffing levels and associated costs compare with similar wards in other trusts. With 1,000 wards now on the database, interesting patterns are emerging which suggest a good deal of the variation in costs may be due to artificial factors rather than necessity (or “natural variation”).
The first graph illustrates the wide variation in unit costs even between wards of the same type (for example, general surgery).
The total additional expenditure on above average cost wards amounts to £2m per year in a typical trust. Managers will ask whether they are overstaffing some wards at the expense of others. And they need to know what the evidence says about the impact of ward size, specialty and patient dependency.
Ward size appears to be the most important factor, associated with about half of the variation in unit cost. Larger wards are cheaper to run. The average unit cost across all wards (except critical care and children’s) is shown in the second graph.
Economies of scale are clear across all types of ward. We estimate combining any two wards into one saves, on average, £0.3m a year, equivalent to the cost of a hypothetical “base” team of about 10 nurses to provide safe, round the clock cover, however many patients are on the ward.
But aside from size, about half of the variation in ward staffing costs remains unexplained.
Critical care wards are much more expensive (intensive therapy units typically cost £750 per occupied bed day) because of the greater needs of their patients, so they need to be considered separately. But across normal dependency wards, hardly any of the variation in cost is associated with different specialties (except gynaecology, children’s and admission wards, which are usually smaller) as the final graph shows.
Leaving aside critical care and the effect of size, dependency would have to vary twofold between similar wards to justify current patterns of spending. With such a costly resource, managers need to be sure nurses are being deployed as well as possible. In particular, they need to be certain that the large differences in nursing costs, even between wards of the same type, are genuinely attributable to need.