Updating Searches for Systematic Reviews

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dc.contributor.advisor Urquhart, Christine
dc.contributor.advisor Moher, David
dc.contributor.author Sampson, Margaret Joan
dc.date.accessioned 2009-12-03T10:06:42Z
dc.date.available 2009-12-03T10:06:42Z
dc.date.issued 2009
dc.identifier.uri http://hdl.handle.net/2160/3760
dc.description.abstract Introduction: This thesis examines methods for updating searches for systematic reviews of healthcare interventions. Systematic reviews endeavour to find and synthesize all relevant research as a basis for the practice of evidence-based medicine. They are more useful if they are complete and up-to-date. Materials and Methods: The sample was 93 meta-analyses in allopathic medicine. Newer randomized controlled trials (RCTs) were sought through MEDLINE searches, and were assessed for relevance by physicians. Two Boolean searches, two similarity searches and one non-database search approach were tested. The Boolean searches were based on a simple subject search paired with a filter selecting only RCTs from Abridged Index Medicus journals or with the balanced Clinical Query. The two similarity searches were Support Vector Machine (SVM) and a Related Article search of PubMed based on the three newest and three largest studies from the original review. Main Results: Clinical Query provided good recall but with large retrievals. Abridged Index Medicus RCT had smaller retrieval sizes and lower recall, but did detect many large studies. The Related Article search showed the highest recall. Recall with SVM was lower, but retrievals were smaller. RCTs that cited the systematic review being updated were also tested but identified only a small proportion of new evidence. Relative performance of the test searches was consistent regardless of whether the intervention was a drug, device or procedure. All searches showed variability across clinical areas, but Related Articles RCT showed the most consistency. The pairing of Related Article RCT and Clinical Query gave excellent recall of new relevant material. Conclusions: Meta-analysts can identify new evidence through a simple structured Boolean search paired with a related articles protocol. By building on the evidence base formed in the original review, related article searching may replace time-consuming nondatabase methods necessary in conducting original reviews. en
dc.description.sponsorship Agency for Healthcare Research and Quality (Contract No. 290-02-0021); Canadian Agency for Drugs and Technologies in Health en
dc.language.iso en en
dc.publisher Aberystwyth University en
dc.title Updating Searches for Systematic Reviews en
dc.type Text en
dc.publisher.department Information Studies en
dc.type.qualificationlevel doctoral en
dc.type.qualificationname PhD en
dc.type.publicationtype thesis or dissertation en


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