Nurse turnover in New Zealand: costs and relationships with staffing practises and patient outcomes

J Nurs Manag. 2013 Apr;21(3):419-28. doi: 10.1111/j.1365-2834.2012.01371.x. Epub 2012 May 4.

Abstract

Aims: To determine the rates and costs of nurse turnover, the relationships with staffing practises, and the impacts on outcomes for nurses and patients.

Background: In the context of nursing shortages, information on the rates and costs of nursing turnover can improve nursing staff management and quality of care.

Methods: Quantitative and qualitative data were collected prospectively for 12 months. A re-analysis of these data used descriptive statistics and correlational analysis techniques.

Results: The cost per registered nurse turnover represents half an average salary. The highest costs were related to temporary cover, followed by productivity loss. Both are associated with adverse patient events. Flexible management of nursing resources (staffing below budgeted levels and reliance on temporary cover), and a reliance on new graduates and international recruitment to replace nurses who left, contributed to turnover and costs.

Conclusions: Nurse turnover is embedded in staffing levels and practises, with costs attributable to both. A culture of turnover was found that is inconsistent with nursing as a knowledge workforce.

Implications for nursing management: Nurse managers did not challenge flexible staffing practices and high turnover rates. Information on turnover and costs is needed to develop strategies that retain nurses as knowledge-based workers.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Efficiency, Organizational / economics
  • Health Services Research
  • Humans
  • Interpersonal Relations
  • New Zealand
  • Nursing Administration Research
  • Nursing Care / standards
  • Nursing Staff, Hospital / economics
  • Nursing Staff, Hospital / organization & administration*
  • Organizational Culture
  • Personnel Turnover / economics
  • Personnel Turnover / statistics & numerical data*
  • Prospective Studies
  • Quality of Health Care
  • United States