title: Taking advantage of the explosion of systematic reviews: an efficient MEDLINE search strategy.
abstract: BACKGROUND
  Systematic reviews of the literature are an important resource for clinicians. Unfortunately, the few published strategies for identifying these articles involve MEDLINE interfaces not widely available outside of academic medicine. In addition, the performance of these strategies is unknown.
  
  
  OBJECTIVE
  To develop and evaluate a search strategy for identifying systematic reviews by using a publicly available MEDLINE interface (PubMed).
  
  
  METHODS
  Diagnostic test assessment. DEFINITION OF SENSITIVITY: The proportion of recognized systematic reviews (indexed in the Cochrane Library's Database of Abstracts of Reviews of Effectiveness [DARE] or in ACP Journal Club) that are identified by the search strategy. DEFINITION OF POSITIVE PREDICTIVE VALUE: The proportion of articles identified in one of three sample searches (screening for colorectal cancer, thrombolytic therapy for venous thromboembolism, and treatment of dementia) that meet a minimum definition of systematic review.
  
  
  RESULTS
  Our PubMed search strategy identified 93 of 100 DARE-indexed systematic reviews, a sensitivity of 93% (95% CI, 86% to 97%). For the sample of systematic reviews drawn from ACP Journal Club (n = 103), the PubMed strategy achieved a sensitivity of 97% (CI, 91% to 99%). When the three sample search strings were used, approximately 50% of retrieved articles met our minimum definition of systematic review. In contrast, the similar precision of a PubMed search restricted to review-type articles (as indexed by MEDLINE) was less than 10%.
  
  
  CONCLUSIONS
  This search strategy identified most systematic reviews without over-whelming users with numerous false-positive results. A "single-click" filter based on this strategy is now available as part of the Clinical Queries feature of PubMed.
authors.affiliation: Department of Medicine, University of California, San Francisco, San Francisco, Calif., USA. Shojania@medicine.ucsf.edu
authors.forename: K G
authors.initials: KG
authors.lastname: Shojania
authors.forename: L A
authors.initials: LA
authors.lastname: Bero
mesh_terms: D019317:Evidence-Based Medicine; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D016239:MEDLINE; D015201:Meta-Analysis as Topic; D012196:Review Literature as Topic; D012680:Sensitivity and Specificity; D013358:Subject Headings; D014584:User-Computer Interface