A comparative review of nurse turnover rates and costs across countries.

J Adv Nurs

Centre for Health Services Management, Faculty of Health, University of Technology, Sydney, New South Wales, Australia; Clinical Nursing and Midwifery Research Centre, School of Nursing and Midwifery, Edith Cowan University, Joondalup, Perth, Western Australia, Australia.

Published: December 2014

Aims: To compare nurse turnover rates and costs from four studies in four countries (US, Canada, Australia, New Zealand) that have used the same costing methodology; the original Nursing Turnover Cost Calculation Methodology.

Background: Measuring and comparing the costs and rates of turnover is difficult because of differences in definitions and methodologies.

Design: Comparative review.

Data Sources: Searches were carried out within CINAHL, Business Source Complete and Medline for studies that used the original Nursing Turnover Cost Calculation Methodology and reported on both costs and rates of nurse turnover, published from 2014 and prior.

Methods: A comparative review of turnover data was conducted using four studies that employed the original Nursing Turnover Cost Calculation Methodology. Costing data items were converted to percentages, while total turnover costs were converted to US 2014 dollars and adjusted according to inflation rates, to permit cross-country comparisons.

Results: Despite using the same methodology, Australia reported significantly higher turnover costs ($48,790) due to higher termination (~50% of indirect costs) and temporary replacement costs (~90% of direct costs). Costs were almost 50% lower in the US ($20,561), Canada ($26,652) and New Zealand ($23,711). Turnover rates also varied significantly across countries with the highest rate reported in New Zealand (44·3%) followed by the US (26·8%), Canada (19·9%) and Australia (15·1%).

Conclusion: A significant proportion of turnover costs are attributed to temporary replacement, highlighting the importance of nurse retention. The authors suggest a minimum dataset is also required to eliminate potential variability across countries, states, hospitals and departments.

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http://dx.doi.org/10.1111/jan.12483DOI Listing

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