title: Improving search efficiency for systematic reviews of diagnostic test accuracy: an exploratory study to assess the viability of limiting to MEDLINE, EMBASE and reference checking.
abstract: BACKGROUND
  Increasing numbers of systematic reviews evaluating the diagnostic test accuracy of technologies are being published. Currently, review teams tend to apply conventional systematic review standards to identify relevant studies for inclusion, for example sensitive searches of multiple bibliographic databases. There has been little evaluation of the efficiency of searching only one or two such databases for this type of review. The aim of this study was to assess the viability of an approach that restricted searches to MEDLINE, EMBASE and the reference lists of included studies.
  
  
  METHODS
  A convenience sample of nine Health Technology Assessment (HTA) systematic reviews of diagnostic test accuracy, with 302 included citations, was analysed to determine the number and proportion of included citations that were indexed in and retrieved from MEDLINE and EMBASE. An assessment was also made of the number and proportion of citations not retrieved from these databases but that could have been identified from the reference lists of included citations.
  
  
  RESULTS
  287/302 (95 %) of the included citations in the nine reviews were indexed across MEDLINE and EMBASE. The reviews' searches of MEDLINE and EMBASE accounted for 85 % of the included citations (256/302). Of the forty-six (15 %) included citations not retrieved by the published searches, 24 (8 %) could be found in the reference lists of included citations. Only 22/302 (7 %) of the included citations were not found by the proposed, more efficient approach.
  
  
  CONCLUSIONS
  The proposed approach would have accounted for 280/302 (93 %) of included citations in this sample of nine systematic reviews. This exploratory study suggests that there might be a case for restricting searches for systematic reviews of diagnostic test accuracy studies to MEDLINE, EMBASE and the reference lists of included citations. The conduct of such reviews might be rendered more efficient by using this approach.
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, S1 4DA, England. l.r.preston@shef.ac.uk.
authors.forename: Louise
authors.initials: L
authors.lastname: Preston
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, S1 4DA, England. c.carroll@shef.ac.uk.
authors.forename: Christopher
authors.initials: C
authors.lastname: Carroll
authors.affiliation: Department of Public Health and Pediatrics, University of Turin, Piazza Polonia, 94, 10125, Turin, Italy. pgardois@gmail.com.
authors.forename: Paolo
authors.initials: P
authors.lastname: Gardois
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, S1 4DA, England. s.paisley@shef.ac.uk.
authors.forename: Suzy
authors.initials: S
authors.lastname: Paisley
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, S1 4DA, England. e.kaltenthaler@shef.ac.uk.
authors.forename: Eva
authors.initials: E
authors.lastname: Kaltenthaler
mesh_terms: D016206:Databases, Bibliographic / Q000706:statistics & numerical data*; D003955:Diagnostic Tests, Routine / Q000706:statistics & numerical data*; D006801:Humans; D016239:MEDLINE / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D013673:Technology Assessment, Biomedical / Q000379:methods* / Q000706:statistics & numerical data*