BACKGROUND: Physicians face challenges when searching PubMed for research evidence, and they may miss relevant articles while retrieving too many nonrelevant articles. We investigated whether the use of search filters in PubMed improves searching by physicians. METHODS: We asked a random sample of Canadian nephrologists to answer unique clinical questions derived from 100 systematic reviews of renal therapy. Physicians provided the search terms that they would type into PubMed to locate articles to answer these questions. We entered the physician-provided search terms into PubMed and applied two types of search filters alone or in combination: a methods-based filter designed to identify high-quality studies about treatment (clinical queries "therapy") and a topic-based filter designed to identify studies with renal content. We evaluated the comprehensiveness (proportion of relevant articles found) and efficiency (ratio of relevant to nonrelevant articles) of the filtered and nonfiltered searches. Primary studies included in the systematic reviews served as the reference standard for relevant articles. RESULTS: The average physician-provided search terms retrieved 46% of the relevant articles, while 6% of the retrieved articles were relevant (corrected) (the ratio of relevant to nonrelevant articles was 1:16). The use of both filters together produced a marked improvement in efficiency, resulting in a ratio of relevant to nonrelevant articles of 1:5 (16 percentage point improvement; 99% confidence interval 9% to 22%; p < 0.003) with no substantive change in comprehensiveness (44% of relevant articles found; p = 0.55). INTERPRETATION: The use of PubMed search filters improves the efficiency of physician searches. Improved search performance may enhance the transfer of research into practice and improve patient care.
BACKGROUND: Physicians face challenges when searching PubMed for research evidence, and they may miss relevant articles while retrieving too many nonrelevant articles. We investigated whether the use of search filters in PubMed improves searching by physicians. METHODS: We asked a random sample of Canadian nephrologists to answer unique clinical questions derived from 100 systematic reviews of renal therapy. Physicians provided the search terms that they would type into PubMed to locate articles to answer these questions. We entered the physician-provided search terms into PubMed and applied two types of search filters alone or in combination: a methods-based filter designed to identify high-quality studies about treatment (clinical queries "therapy") and a topic-based filter designed to identify studies with renal content. We evaluated the comprehensiveness (proportion of relevant articles found) and efficiency (ratio of relevant to nonrelevant articles) of the filtered and nonfiltered searches. Primary studies included in the systematic reviews served as the reference standard for relevant articles. RESULTS: The average physician-provided search terms retrieved 46% of the relevant articles, while 6% of the retrieved articles were relevant (corrected) (the ratio of relevant to nonrelevant articles was 1:16). The use of both filters together produced a marked improvement in efficiency, resulting in a ratio of relevant to nonrelevant articles of 1:5 (16 percentage point improvement; 99% confidence interval 9% to 22%; p < 0.003) with no substantive change in comprehensiveness (44% of relevant articles found; p = 0.55). INTERPRETATION: The use of PubMed search filters improves the efficiency of physician searches. Improved search performance may enhance the transfer of research into practice and improve patient care.
Authors: Salimah Z Shariff; Shayna A D Bejaimal; Jessica M Sontrop; Arthur V Iansavichus; Matthew A Weir; R Brian Haynes; Mark R Speechley; Amardeep Thind; Amit X Garg Journal: J Nephrol Date: 2011 Nov-Dec Impact factor: 3.902
Authors: A X Garg; A V Iansavichus; M Kastner; L A Walters; N Wilczynski; K A McKibbon; R C Yang; F Rehman; R B Haynes Journal: Kidney Int Date: 2006-10-11 Impact factor: 10.612
Authors: Amit X Garg; Arthur V Iansavichus; Nancy L Wilczynski; Monika Kastner; Leslie A Baier; Salimah Z Shariff; Faisal Rehman; Matthew Weir; K Ann McKibbon; R Brian Haynes Journal: BMJ Date: 2009-09-18
Authors: Nancy L Wilczynski; K Ann McKibbon; Stephen D Walter; Amit X Garg; R Brian Haynes Journal: J Am Med Inform Assoc Date: 2012-09-27 Impact factor: 4.497
Authors: Ainslie M Hildebrand; Arthur V Iansavichus; Christopher W C Lee; R Brian Haynes; Nancy L Wilczynski; K Ann McKibbon; Michelle A Hladunewich; William F Clark; Daniel C Cattran; Amit X Garg Journal: BMC Med Inform Decis Mak Date: 2012-06-06 Impact factor: 2.796