Article type
Year
Abstract
Background: Searching the medical literature for evidence on prognosis is an important aspect of evidence-based disability evaluation.
Objective: To develop and evaluate a comprehensive and efficient search strategy in PubMed, to be used by either researchers or practitioners, to identify articles on the prognosis of work disability.
Methods: We used a diagnostic test analytic framework. Firstly we created a reference set of 225 articles on the prognosis of work disability by screening a total of 65,692 titles and abstracts from 10 journals from the period 2000 to 2009. The included studies had a minimum follow-up of six months, participants between the ages of 18 to 64 years, with a minimum sick leave period of four weeks or longer, or having serious limitations on activity in 50% of the cases and outcome measures that reflected 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% confidence interval (CI) 86 to 94) and efficiency, expressed in a more user-friendly fashion as the 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 is needed, especially for the practitioner for whom efficiency is especially important
Objective: To develop and evaluate a comprehensive and efficient search strategy in PubMed, to be used by either researchers or practitioners, to identify articles on the prognosis of work disability.
Methods: We used a diagnostic test analytic framework. Firstly we created a reference set of 225 articles on the prognosis of work disability by screening a total of 65,692 titles and abstracts from 10 journals from the period 2000 to 2009. The included studies had a minimum follow-up of six months, participants between the ages of 18 to 64 years, with a minimum sick leave period of four weeks or longer, or having serious limitations on activity in 50% of the cases and outcome measures that reflected 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% confidence interval (CI) 86 to 94) and efficiency, expressed in a more user-friendly fashion as the 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 is needed, especially for the practitioner for whom efficiency is especially important