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Retrieving randomized controlled trials from medline: a comparison of 38 published search filters
Article first published online: 29 OCT 2008
DOI: 10.1111/j.1471-1842.2008.00827.x
© 2008 The authors. Journal compilation © 2008 Health Libraries Group
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How to Cite
McKibbon, K. A., Wilczynski, N. L., Haynes, R. B. and for the Hedges Team (2009), Retrieving randomized controlled trials from medline: a comparison of 38 published search filters. Health Information & Libraries Journal, 26: 187–202. doi: 10.1111/j.1471-1842.2008.00827.x
Publication History
- Issue published online: 25 AUG 2009
- Article first published online: 29 OCT 2008
- Received 8 April 2008; Accepted 1 September 2008
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Abstract
Background: People search medline for trials of healthcare interventions for clinical decisions, or to produce systematic reviews, practice guidelines, or technology assessments. Finding all relevant randomized controlled trials (RCTs) with little extraneous material is challenging.
Objective: To provide comparative data on the operating characteristics of search filters designed to retrieve RCTs from medline.
Methods: We identified 38 filters. The testing database comprises handsearching data from 161 clinical journals indexed in medline. Sensitivity, specificity and precision were calculated.
Results: The number of terms and operating characteristics varied considerably. Comparing the retrieval against the single term ‘randomized controlled trials.pt.’ (sensitivity for retrieving RCTs, 93.7%), 24 of 38 filters had statistically higher sensitivity; 6 had a sensitivity of at least 99.0%. Four other filters had specificities (non retrieval of non-RCTs) that were statistically not different or better than the single term (97.6%). Precision was poor: only two filters had precision (proportion of retrieved articles that were RCTs) statistically similar to that of the single term (56.4%)—all others were lower. Filters with more search terms often had lower specificity, especially at high sensitivities.
Conclusion: Many RCT filters exist (n = 38). These comparative data can direct the choice of an RCT filter.