Predicting long-term sickness absence with employee questionnaires and administrative records: a prospective cohort study of hospital employees

Objective: This study aimed to compare the utility of risk estimation derived from questionnaires and administrative records in predicting long-term sickness absence among shift workers. Methods This prospective cohort study comprised 3197 shift-working hospital employees (mean age 44.5 years, 88.0% women) who responded to a brief 8-item questionnaire on work disability risk factors and were linked to 28 variables on their working hour and workplace characteristics obtained from administrative registries at study baseline. The primary outcome was the first sickness absence lasting ≥90 days during a 4-year follow-up. Results The C-index of 0.73 [95% confidence interval (CI) 0.70–0.77] for a questionnaire-only based prediction model, 0.71 (95% CI 0.67–0.75) for an administrative records-only model, and 0.79 (95% CI 0.76–0.82) for a model combining variables from both data sources indicated good discriminatory ability. For a 5%-estimated risk as a threshold for positive test results, the detection rates were 76%, 74%, and 75% and the false positive rates were 40%, 45% and 34% for the three models. For a 20%-risk threshold, the corresponding detection rates were 14%, 8%, and 27% and the false positive rates were 2%, 2%, and 4%. To detect one true positive case with these models, the number of false positive cases accompanied varied between 7 and 10 using the 5%-estimated risk, and between 2 and 3 using the 20%-estimated risk cut-off. The pattern of results was similar using 30-day sickness absence as the outcome. Conclusions The best predictive performance was reached with a model including both questionnaire responses and administrative records. Prediction was almost as accurate with models using only variables from one of these data sources. Further research is needed to examine the generalizability of these findings

Chronic diseases as predictors of labour market attachment after participation in subsidised re-employment programme: a 6-year follow-up study

Background: Little is known about the work patterns of re-employed people. We investigated the labour market attachment trajectories of re-employed people and assessed the influence of chronic diseases on these trajectories.Methods: The study was based on register data of 18 944 people (aged 18–60 years) who participated in a subsidised re-employment programme in Finland. Latent class growth analysis with zero-inflated Poisson was used to model the labour market attachment trajectories over a 6-year follow-up time. Multinomial logistic regression was used to examine the associations between chronic diseases and labour market attachment trajectories, adjusting for age, gender, educational level, size of town and calendar year in subsidised re-employment programme.Results: We identified four distinct labour market attachment trajectories, namely: strengthening (a relatively stable attachment throughout the follow-up time; 77%), delayed (initial weak attachment increasing later; 6%), leavers (attachment declined with time; 10%) and none-attached (weak attachment throughout the study period; 7%). We found that severe mental problems strongly increased the likelihood of belonging in the leavers (OR 3.61; 95% CI 2.23 to 5.37) and none-attached (OR 3.41; 95% CI 1.91 to 6.10) trajectories, while chronic hypertension was associated with none-attached (OR 1.37; 95% CI 1.06 to 1.77) trajectory. The associations between other chronic diseases (diabetes, heart disease, asthma and arthritics) and labour market attachment trajectories were less evident.Conclusion:s Re-employed people appear to follow distinct labour market attachment trajectories over time. Having chronic diseases, especially mental disorders appear to increase the risk for relatively poor labour market attachment.</p