title: Multicentre validation of frequent sickness absence predictions.
abstract: BACKGROUND
  A prediction model including age, self-rated health (SRH) and prior sickness absence (SA) has previously been found to predict frequent SA.
  
  
  OBJECTIVE
  To further validate the model and develop it for clinical use.
  
  
  METHODS
  A multicentre study of care of the elderly workers employed at one of 14 centres in Aarhus (Denmark). SA episodes recorded in the year prior to baseline and both age and SRH at baseline were included in a prediction model for frequent (three or more) SA episodes during a 1-year follow-up period. The prediction model was developed in the largest centre. Risk predictions and discrimination between high- and low-risk workers were investigated in the other centres. The prediction rule 'SRH-prior SA' was derived from the prediction model and prognostic properties of the prediction rule were investigated for each centre, using score <0 as cut-off.
  
  
  RESULTS
  Of 2562 workers, 1930 had complete data for analysis. Predictions were accurate in 4 of 13 centres; discrimination was good in five and fair in another five centres. Prediction rule scores <0 identified workers at risk of frequent SA with sensitivities of 0.17-0.54, specificities of 0.86-0.96 and positive predictive values of 0.54-0.87 across centres.
  
  
  CONCLUSIONS
  The prediction model discriminated between workers at high and low risk of frequent SA in the majority of centres. The prediction rule 'SRH-prior SA' can be used in clinical practice specifically to identify workers at high risk of frequent SA.
authors.affiliation: ArboNed Occupational Health Service, PO Box 85091, 3508 AB Utrecht, The Netherlands, Department of Health Sciences Section Community and Occupational Medicine, University Medical Center Groningen, University of Groningen, PO Box 196, 9700 AD Groningen, The Netherlands, Department of Epidemiology and Biostatistics, VU University Medical Center, VU University, De Boelelaan 1117, 1081 HZ Amsterdam, The Netherlands, corne.roelen@arboned.nl.
authors.forename: C A M
authors.initials: CA
authors.lastname: Roelen
authors.affiliation: Department of Health Sciences Section Community and Occupational Medicine, University Medical Center Groningen, University of Groningen, PO Box 196, 9700 AD Groningen, The Netherlands.
authors.forename: U
authors.initials: U
authors.lastname: Bultmann
authors.affiliation: Public Health and Quality Improvement, Central Denmark Region, MarselisborgCentret, P.P. Ørumsgade 11, 8000 Aarhus C, Denmark.
authors.forename: C M
authors.initials: CM
authors.lastname: Stapelfeldt
authors.affiliation: National Centre for Occupational Rehabilitation, Haddlandsveien 20, 3864 Rauland, Norway, Department of Public Health and General Practice, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.
authors.forename: C
authors.initials: C
authors.lastname: Jensen
authors.affiliation: Department of Epidemiology and Biostatistics, VU University Medical Center, VU University, De Boelelaan 1117, 1081 HZ Amsterdam, The Netherlands.
authors.forename: M W
authors.initials: MW
authors.lastname: Heymans
mesh_terms: D000041:Absenteeism; D000328:Adult; D000367:Age Factors; D003718:Denmark; D059026:Diagnostic Self Evaluation; D006282:Health Personnel; D006299:Health Services for the Aged; D006304:Health Status; D006801:Humans; D008875:Middle Aged; D008954:Models, Biological; D015203:Reproducibility of Results; D012307:Risk Factors; D018582:Sick Leave; D000078329:Workforce
keywords: Absenteeism; external validity; generalization; prediction model; prediction rule; sick leave.