Objective: To examine how various predictors and subgroups of respondents contribute to the prediction of health care and productivity costs in a cohort of employees. Methods: We selected 1548 employed people from a cohort study with and without depressive and anxiety symptoms or disorders. Prediction rules, using the RuleFit program, were applied to identify predictors and subgroups of respondents, and to predict estimations of subsequent 1-year health care and productivity costs. RESULTS:: Symptom severity and diagnosis of depression and anxiety were the most important predictors of health care costs. Depressive symptom severity was the most important predictor for productivity costs. Several demographic, social, and work predictors did not predict economic costs. Conclusions: Our data suggest that from a business perspective it can be beneficial to offer interventions aimed at prevention of depression and anxiety. Copyright © 2014 by American College of Occupational and Environmental Medicine.
|Number of pages
|Journal of Occupational and Environmental Medicine
|Published - 2014