title: Productivity costs before and after absence from work: as important as common?
abstract: Traditionally, production losses are estimated using the human capital or friction cost method. These methods base estimations of productivity costs on data on absence from work. For some diseases, like migraine, productivity losses without absence are occasionally calculated by estimating the production losses from reduced productivity at work. However, diseases typically only associated with absence may also be expected to cause reduced productivity before and after absence. In a previous study, Brouwer et al. concluded that productivity losses without absence are also very relevant in common diseases, like influenza, common cold or neck-problems. Studying a new sample of employees of a Dutch trade-firm (n = 51), who completed the questionnaire 'Ill and Recovered' upon return to work after absence due to illness, it was revealed that about 25% of the respondents experienced production losses before absence and about 20% of the respondents experience production losses after absence. This leads to an increase in estimated production losses of about 16% compared with only considering absence data. Current productivity costs estimates based solely on absence data may, therefore, underestimate real productivity costs. Compensation mechanisms in firms may reduce the underestimation.
authors.affiliation: Institute for Medical Technology Assessment, Erasmus University Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands. brouwer@bmg.eur.nl
authors.forename: W B F
authors.initials: WB
authors.lastname: Brouwer
authors.forename: N J A
authors.initials: NJ
authors.lastname: van Exel
authors.forename: M A
authors.initials: MA
authors.lastname: Koopmanschap
authors.forename: F F H
authors.initials: FF
authors.lastname: Rutten
mesh_terms: D000041:Absenteeism; D017281:Cost of Illness; D003365:Costs and Cost Analysis; D004526:Efficiency; D017049:Employer Health Costs / Q000145:classification / Q000706:statistics & numerical data*; D004651:Employment / Q000191:economics*; D006801:Humans; D017059:Models, Econometric; D009426:Netherlands; D016272:Occupational Health