Complementary approaches to searching MEDLINE may be sufficient for updating systematic reviews

Margaret Sampson, Berry de Bruijn, Christine Urquhart, Kaveh Shojania

Research output: Contribution to journalArticlepeer-review

16 Citations (SciVal)


To maximize the proportion of relevant studies identified for inclusion in systematic reviews (recall), complex time-consuming Boolean searches across multiple databases are common. Although MEDLINE provides excellent coverage of health science evidence, it has proved challenging to achieve high levels of recall through Boolean searches alone.

Study Design and Setting
Recall of one Boolean search method, the clinical query (CQ), combined with a ranking method, support vector machine (SVM), or PubMed-related articles, was tested against a gold standard of studies added to 6 updated Cochrane reviews and 10 Agency for Healthcare Research and Quality (AHRQ) evidence reviews. For the AHRQ sample, precision and temporal stability were examined for each method.

Recall of new studies was 0.69 for the CQ, 0.66 for related articles, 0.50 for SVM, 0.91 for the combination of CQ and related articles, and 0.89 for the combination of CQ and SVM. Precision was 0.11 for CQ and related articles combined, and 0.11 for CQ and SVM combined. Related articles showed least stability over time.

The complementary combination of a Boolean search strategy and a ranking strategy appears to provide a robust method for identifying relevant studies in MEDLINE.
Original languageEnglish
Pages (from-to)108-115
Number of pages8
JournalJournal of Clinical Epidemiology
Early online date11 Mar 2016
Publication statusPublished - 01 Oct 2016


  • information retrieval
  • systematic reviews
  • support vector machine
  • clinical query
  • PubMed similar articles
  • searches
  • updating


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