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01.12.2012 | Research article | Ausgabe 1/2012 Open Access

BMC Medical Informatics and Decision Making 1/2012

Glomerular disease search filters for Pubmed, Ovid Medline, and Embase: a development and validation study

Zeitschrift:
BMC Medical Informatics and Decision Making > Ausgabe 1/2012
Autoren:
Ainslie M Hildebrand, Arthur V Iansavichus, Christopher WC Lee, R Brian Haynes, Nancy L Wilczynski, K Ann McKibbon, Michelle A Hladunewich, William F Clark, Daniel C Cattran, Amit X Garg
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​1472-6947-12-49) contains supplementary material, which is available to authorized users.
Ainslie M Hildebrand, Arthur V Iansavichus, Christopher WC Lee, R Brian Haynes, Nancy L Wilczynski, K Ann McKibbon, Michelle A Hladunewich, William F Clark, Daniel C Cattran and Amit X Garg contributed equally to this work.

Competing interests

We have no competing interests to declare.

Authors’ contributions

AMH, AVI, and AXG were involved in study design and drafting the manuscript. All authors participated in analysis and interpretation of data, intellectual content, draft revision, and approval of the final manuscript.

Abstract

Background

Tools to enhance physician searches of Medline and other bibliographic databases have potential to improve the application of new knowledge in patient care. This is particularly true for articles about glomerular disease, which are published across multiple disciplines and are often difficult to track down. Our objective was to develop and test search filters for PubMed, Ovid Medline, and Embase that allow physicians to search within a subset of the database to retrieve articles relevant to glomerular disease.

Methods

We used a diagnostic test assessment framework with development and validation phases. We read a total of 22,992 full text articles for relevance and assigned them to the development or validation set to define the reference standard. We then used combinations of search terms to develop 997,298 unique glomerular disease filters. Outcome measures for each filter included sensitivity, specificity, precision, and accuracy. We selected optimal sensitive and specific search filters for each database and applied them to the validation set to test performance.

Results

High performance filters achieved at least 93.8% sensitivity and specificity in the development set. Filters optimized for sensitivity reached at least 96.7% sensitivity and filters optimized for specificity reached at least 98.4% specificity. Performance of these filters was consistent in the validation set and similar among all three databases.

Conclusions

PubMed, Ovid Medline, and Embase can be filtered for articles relevant to glomerular disease in a reliable manner. These filters can now be used to facilitate physician searching.
Zusatzmaterial
Additional file 1:Appendix A: Division of 39 journals into development and validation sets. Appendix B: Methods used to determine article relevance to glomerular disease. (DOCX 90 KB)
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Literatur
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