Back

Costs and cost-effectiveness of nurse staffing in acute hospital: a systematic review

Griffiths, P.; Saville, C.; Ball, J.; Dall'Ora, C.; Meredith, P.; Turner, L. Y.; Jones, J.

2023-02-03 health economics
10.1101/2023.02.03.23285139 medRxiv
Show abstract

BackgroundExtensive research shows associations between increased nurse staffing, skill mix and patient outcomes. However, showing that improved staffing levels are linked to improved outcomes is not sufficient to provide a case for increasing them. This review of economic studies in acute hospitals aims to identify costs and consequences associated with different nurse staffing configurations in hospitals. MethodsWe included economic studies exploring the effect of variation in nurse staffing. We searched PubMed, CINAHL, Embase Econlit, Cochrane library, DARE, NHS EED and the INAHTA website. Risk of bias was assessed using a framework based on the NICE guidance for public health reviews and Henriksons framework for economic evaluations. Inclusion, data extraction and critical appraisal were undertaken by pairs of reviewers with disagreements resolved by a third. Results were synthesised using a hierarchical matrix to summarise findings of economic evaluations ResultsWe found 22 observational studies conducted in the USA (15), Australia, Belgium, China, South Korea and the United Kingdom (3). Fourteen had high risk of bias and eight moderate. Six studies clearly favoured increased registered nurse staffing with improved outcomes and reduced or unchanged net costs, but most showed increased costs and outcomes. Studies undertaken outside the USA showed that increased nurse staffing was likely to be cost-effective at a per capita GDP threshold or lower. Three studies of skill mix favoured increased registered nurse skill mix, with reduced net cost and similar or improved outcomes. DiscussionDespite the risk of bias, evidence is largely consistent and strongly favours increased skill mix. Evidence for the cost-effectiveness of increases in registered nurse staffing is less certain although it is likely to be cost-effective. In an era of registered nurse scarcity, the results strongly favour investment in registered nurse supply as opposed to using lesser qualified staff as substitutes. What is already known?O_LIHigher registered nurse staffing levels and skill mix in acute hospitals are associated with improved care quality and patient outcomes, most notably reduced risk of death C_LIO_LIPrevious reviews of evidence strongly support a causal interpretation, but reviews of economic evidence have failed to reach firm conclusions. C_LI What is study addsO_LIDespite limitations in the evidence, results favour a richer registered nurse skill mix in the nursing workforce as an economically dominant strategy and increases in registered nurse staffing could be cost effective at a low threshold C_LI How this study might affect research practice or policyO_LIWorkforce substitution is unlikely to provide a cost-effective solution to registered nurse shortages. C_LIO_LIMore incremental cost effectiveness studies are required to guide decision making in context as specific results do not generalise C_LI CREDiT (author contributions)Jane Ball, Chiara DallOra, Peter Griffiths, Jeremy Jones, Paul Meredith acquired funding for the study Peter Griffiths, Jeremy Jones, Christina Saville designed the review and wrote the protocol Christina Saville undertook the searches Jane Ball, Jeremy Jones, Paul Meredith, Lesley Turner, Christina Saville undertook screening and application of the inclusion criteria Jane Ball, Chiara DallOra, Peter Griffiths, Jeremy Jones, Paul Meredith, Lesley Turner, Christina Saville undertook data extraction and critical appraisal of included studies Christina Saville and Peter Griffiths prepared the first draft of the paper Peter Griffiths undertook data synthesis and drafted results Jane Ball, Chiara DallOra, Peter Griffiths, Jeremy Jones, Paul Meredith, Lesley Turner, Christina Saville reviewed the first draft and provided critical comment and contribution to the discussion / suggested revisions. All reviewed the final draft RegistrationPROSPERO (CRD42021281202).

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.