The Added Value of Collecting Information on @entity158 Experience When Predicting Time on Benefits for Injured Workers with Back XXXX .

@entity1 @entity615 @entity158
UNASSIGNED: Objectives Some injured workers with work-related, @entity615 experience a troubling course in return to work. A prediction tool was developed in an earlier study, using administrative data only. This study explored the added value of worker reported data in identifying those workers with @entity615 at higher risk of being on benefits for a longer period of time. Methods This was a cohort study of workers with @entity615 in 2005 in Ontario. Workplace Safety and Insurance Board (WSIB) data was used. As well, we examined the added value of @entity1 -reported prognostic factors obtained from a prospective cohort study. Improvement of model fit was determined by comparing area under the curve (AUC) statistics. The outcome measure was time on benefits during a first workers' compensation claim for @entity615 . Follow-up was 2  years. Results Among 1442 workers with WSIB data still on full benefits at 4  weeks, 113 were also part of the prospective cohort study. Model fit of an established rule in the smaller dataset of 113 workers was comparable to the fit previously established in the larger dataset. Adding worker rating of @entity158 at baseline improved the rule substantially (AUC  =  0.80, 95  % CI 0.68, 0.91 compared to benefit status at 180  days, AUC  =  0.88, 95  % CI 0.74, 1.00 compared to benefits status at 360  days). Conclusion Although data routinely collected by workers' compensation boards show some ability to predict prolonged time on benefits, adding information on experienced @entity158 reported by the worker improves the predictive ability of the model from 'fairly good' to 'good'. In this study, a combination of prognostic factors, reported by multiple stakeholders, including the worker, could identify those at high risk of extended duration on disability benefits and in potentially in need of additional support at the individual level.
