title: How best to measure health workforce turnover and retention: five key metrics.
abstract: OBJECTIVE
  This article identifies, critically appraises and illustrates the use of five key workforce turnover and retention metrics that are well suited for use by Australian rural health workforce planners. These are crude turnover (separation) rates, stability rates, survival probabilities, median survival and Cox proportional hazard ratios. Examples of their calculation are presented using actual data obtained from payroll records in Australian rural and remote health services.
  
  
  CONCLUSIONS
  The use of this small number of metrics as a 'workforce measurement package' can help overcome many of the limitations evident when a single measure is reported in isolation, by providing a more comprehensive picture of turnover and retention patterns. We suggest that health services themselves can calculate the simplest measures, whereas regional and centralised health authorities with higher levels of expertise undertake survival analysis and comparisons of compiled data.
  
  
  CONCLUSIONS
  These key metrics can be used routinely to measure baseline levels of health worker turnover and retention, to quantify important determinants of turnover and retention, and importantly, to make valid comparisons. This enables areas for improvement to be better targeted using appropriate retention strategies, and changes resulting from retention interventions to be evaluated effectively.
authors.affiliation: School of Rural Health, Monash University, PO Box 666, Bendigo, VIC 3552, Australia. Deborah.Rusell@monash.edu
authors.forename: Deborah J
authors.initials: DJ
authors.lastname: Russell
authors.forename: John S
authors.initials: JS
authors.lastname: Humphreys
authors.forename: John
authors.initials: J
authors.lastname: Wakerman
mesh_terms: D001315:Australia; D006280:Health Workforce / Q000706:statistics & numerical data; D006801:Humans; D010558:Personnel Loyalty; D010563:Personnel Turnover / Q000706:statistics & numerical data; D016016:Proportional Hazards Models; D019035:Rural Health Services