A Search Strategy to Identify Studies on the Prognosis of Work Disability: a Diagnostic Test Framework

Objective: Searching the medical literature for evidence on prognosis is an important aspect of evidence-based disability evaluation. To facilitate this, we aimed to develop and evaluate a comprehensive and efficient search strategy in PubMed, to be used by either researchers or practitioners and that will identify articles on the prognosis of work disability.

Methods: We used a diagnostic test analytic framework. First, we created a reference set of 225 articles on the prognosis of work disability by screening a total of 65,692 titles and abstracts from10 journals in the period 2000-2009. Included studies had a minimum follow-up of 6 months, participants in the age of 18-64 with a minimum sick leave of 4 weeks or longer or having serious activity limitations in 50% of the cases and outcome measures that reflect impairments, activity limitations or participation restrictions. Using text mining methods, we extracted search terms from the reference set and, according to sensitivity and relative frequency, we combined these into search strings.

Results: Both the research and the practice search filter outperformed existing filters in occupational health, all combined with the Yale-prognostic filter. The Work Disability Prognosis filter for Research showed a comprehensiveness of 90% (95% CI 86 to 94) and efficiency expressed more user-friendly as Number Needed to Read=20 (95% CI 17 to 34).

Conclusions: The Work Disability Prognosis filter will help practitioners and researchers who want to find prognostic evidence in the area of work disability evaluation. However, further refining of this filter is possible and needed, especially for the practitioner for whom efficiency is especially important.