Abstract
Aim. The purpose was to analyse the properties of two models for the assessment of return to work after sickness certification, a manual one based on clinical judgement including non-measurable information (‘gut feeling’), and a computer-based one.Study population. All subjects aged 18 to 63 years, sickness-certified at a primary health care centre in Sweden during 8 months (n = 943), and followed up for 3 years.Methods. Baseline information included age, sex, occupational status, sickness certification diagnosis, full-time or part-time current sick-leave, and sick-leave days during the past year. Follow-up information included first and last day of each occurring sick spell. In the manual model all subjects were classified, based on baseline information and gut feeling, into a high-risk (n = 447) or a low-risk group (n = 496) regarding not returning to work when the present certificate expired. It was evaluated with a Cox’s analysis, including time and return to work as dependent variables and risk group assignment as the independent variable, while in the computer-based model the baseline variables were entered as independent variables.Results. Concordance between actual return to work and return to work predicted by the analysis model was 73%–76% during the first 28–180 days in the manual model, and approximately 10% units higher in the computer-based model. Based on the latter, three nomograms were constructed providing detailed information on the probability of return to work.Conclusion. The computer-based model had a higher precision and gave more detailed information than the manual model.
Highlights
Sickness absence is a major public health and economic problem in Sweden
In the manual model all subjects were classified, based on baseline information and gut feeling, into a high-risk (n = 447) or a low-risk group (n = 496) regarding not returning to work when the present certificate expired. It was evaluated with a Cox’s analysis, including time and return to work as dependent variables and risk group assignment as the independent variable, while in the computer-based model the baseline variables were entered as independent variables
Concordance between actual return to work and return to work predicted by the analysis model was 73%–76% during the first 28–180 days in the manual model, and approximately 10% units higher in the computer-based model
Summary
The study has been described in detail elsewhere [15]. It was performed in the city of Eskilstuna, Sweden, an industrial city, located 110 kilometres west of Stockholm, with 91,000 residents in 2004. In a previous publication based on the same data set as used here, the significant determinants for RTW were age at baseline, number of days of sick-leave during the year preceding baseline, sick-leave diagnosis, degree of sick-leave, and occupational status [15]. These determinants were used in this study. From the Cox’s analysis of the computer-based model, data were obtained showing proportion returning to work for combinations of age, number of sickleave days last year, and sick-leave diagnosis groups on day 28, day 90, and day 180 from baseline All tests were two-tailed, and the significance level was set at p < 0.05
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