Search filter precision can be improved by NOTing out irrelevant content
- PMID: 22195215
- PMCID: PMC3243169
Search filter precision can be improved by NOTing out irrelevant content
Abstract
Background: Most methodologic search filters developed for use in large electronic databases such as MEDLINE have low precision. One method that has been proposed but not tested for improving precision is NOTing out irrelevant content.
Objective: To determine if search filter precision can be improved by NOTing out the text words and index terms assigned to those articles that are retrieved but are off-target.
Design: Analytic survey.
Methods: NOTing out unique terms in off-target articles and testing search filter performance in the Clinical Hedges Database.
Main outcome measures: Sensitivity, specificity, precision and number needed to read (NNR).
Results: For all purpose categories (diagnosis, prognosis and etiology) except treatment and for all databases (MEDLINE, EMBASE, CINAHL and PsycINFO), constructing search filters that NOTed out irrelevant content resulted in substantive improvements in NNR (over four-fold for some purpose categories and databases).
Conclusion: Search filter precision can be improved by NOTing out irrelevant content.
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