Costs and cost-effectiveness of nurse staffing in acute hospital: a systematic review
Authors: Griffiths Peter , Saville Christina , Ball Jane , Dall’Ora Chiara , Meredith Paul , Turner Lesley , Jones Jeremy 
Published: February 2023

AbstractBackgroundExtensive 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 Henrikson’s 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 evaluationsResultsWe 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?Higher registered nurse staffing levels and skill mix in acute hospitals are associated with improved care quality and patient outcomes, most notably reduced risk of deathPrevious reviews of evidence strongly support a causal interpretation, but reviews of economic evidence have failed to reach firm conclusions.What is study addsDespite 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 thresholdHow this study might affect research practice or policyWorkforce substitution is unlikely to provide a cost-effective solution to registered nurse shortages.More incremental cost effectiveness studies are required to guide decision making in context as specific results do not generaliseCREDiT (author contributions)Jane Ball, Chiara Dall’Ora, Peter Griffiths, Jeremy Jones, Paul Meredith acquired funding for the study Peter Griffiths, Jeremy Jones, Christina Saville designed the review and wrote the protocolChristina Saville undertook the searchesJane Ball, Jeremy Jones, Paul Meredith, Lesley Turner, Christina Saville undertook screening and application of the inclusion criteriaJane Ball, Chiara Dall’Ora, Peter Griffiths, Jeremy Jones, Paul Meredith, Lesley Turner, Christina Saville undertook data extraction and critical appraisal of included studiesChristina Saville and Peter Griffiths prepared the first draft of the paperPeter Griffiths undertook data synthesis and drafted resultsJane Ball, Chiara Dall’Ora, 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 draftRegistrationPROSPERO (CRD42021281202).