title: The art and science of searching MEDLINE to answer clinical questions. Finding the right number of articles.
abstract: The current medical environment makes information retrieval a matter of practical importance for clinicians. Many avenues present themselves to the clinician, but here we focus on MEDLINE by summarizing the current state of the art and providing an innovative approach for skill enhancement. Because new search engines appear rapidly, we focus on generic principles that can be easily adapted to various systems, even those not yet available. We propose an idealized classification system for the results of a MEDLINE search. Type A searches produce a few articles of high quality that are directly focused on the immediate question. Type B searches yield a large number of articles, some more relevant than others. Type C searches produce few or no articles, and those that are located are not germane. Providing that relevant, high-quality articles do exist, type B and C searches may often be improved with attention to search technique. Problems stem from poor recall and poor precision. The most daunting task lies in achieving the balance between too few and too many articles. By providing a theoretical framework and several practical examples, we prepare the searcher to overcome the following barriers: a) failure to begin with a well-built question; b) failure to use the Medical Subject Headings; c) failure to leverage the relationship between recall and precision; and d) failure to apply proper limits to the search. Thought and practice will increase the utility and enjoyment of searching MEDLINE.
authors.affiliation: University of Alabama at Birmingham, USA.
authors.forename: J J
authors.initials: JJ
authors.lastname: Allison
authors.forename: C I
authors.initials: CI
authors.lastname: Kiefe
authors.forename: N W
authors.initials: NW
authors.lastname: Weissman
authors.forename: J
authors.initials: J
authors.lastname: Carter
authors.forename: R M
authors.initials: RM
authors.lastname: Centor
mesh_terms: D015510:Clinical Medicine; D003200:Computer User Training; D019317:Evidence-Based Medicine; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D016247:Information Storage and Retrieval / Q000145:classification; D016239:MEDLINE / Q000458:organization & administration*; D010820:Physicians / Q000523:psychology; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013358:Subject Headings