title: Predicting job loss in those off sick.
abstract: BACKGROUND
  Evidence shows incapacity benefit claimants (those off sick >26 weeks) are at greatest risk of long-term job loss.
  
  
  OBJECTIVE
  To develop a screening tool to select those at risk of job loss, defined as failure to return to work among those off sick. The screening tool was for use in the Job Retention and Rehabilitation Pilot of the Department for Work and Pensions.
  
  
  METHODS
  A literature review identified risks for long-term incapacity and job loss as multifactorial. Potential predictors for return to work were then assembled into a set of questions and tested by a prospective study in general practice surgeries and a retrospective study of occupational health records of local authority employees referred for sickness absence management, using univariate and multivariate logistic regression analysis.
  
  
  RESULTS
  Univariate logistic regression analysis of the retrospective study produced odds ratios with 95% confidence intervals for each question (where P <or= 0.05) and a C-index was then constructed for their predictive power. Five questions holding the greatest predictive power were subjected to multivariate analysis and in the final model had a high C-index of 0.90 (0.5 = no predictive power, 1.0 = perfect prediction). They formed the screening tool. The questions cover self-assessment of ability to return to work after current sick leave, of ability to do current job in 6 months' time, sick leave in past year, current age and whether awaiting a consultation or treatment.
  
  
  CONCLUSIONS
  A screening tool identifying those most at risk of job loss has been produced.
authors.affiliation: Division of Community Based Sciences, Faculty of Medicine, Public Health and Health Policy Section, University of Glasgow, Glasgow, UK.
authors.forename: Jane
authors.initials: J
authors.lastname: Wilford
authors.forename: Alex D
authors.initials: AD
authors.lastname: McMahon
authors.forename: Jean
authors.initials: J
authors.lastname: Peters
authors.forename: Simon
authors.initials: S
authors.lastname: Pickvance
authors.forename: Alison
authors.initials: A
authors.lastname: Jackson
authors.forename: Lindsay
authors.initials: L
authors.lastname: Blank
authors.forename: David
authors.initials: D
authors.lastname: Craig
authors.forename: Alan
authors.initials: A
authors.lastname: O'Rourke
authors.forename: Ewan B
authors.initials: EB
authors.lastname: Macdonald
mesh_terms: D000704:Analysis of Variance; D004651:Employment / Q000706:statistics & numerical data; D005544:Forecasting; D006801:Humans; D011446:Prospective Studies; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D018582:Sick Leave; D011795:Surveys and Questionnaires; D014478:Unemployment / Q000706:statistics & numerical data*; D006113:United Kingdom / Q000453:epidemiology