Filtering Medline for a clinical discipline: diagnostic test assessment framework

Amit X. Garg · Arthur V. Iansavichus · Nancy L Wilczynski · Monika Kastner · L. A Baier · Salimah Z. Shariff +3 more

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Meta-analysis and systematic reviews Information Retrieval and Search Behavior Health Sciences Research and Education

Abstract

OBJECTIVE: To develop and test a Medline filter that allows clinicians to search for articles within a clinical discipline, rather than searching the entire Medline database. DESIGN: Diagnostic test assessment framework with development and validation phases. SETTING: Sample of 4657 articles published in 2006 from 40 journals. Reviews Each article was manually reviewed, and 19.8% contained information relevant to the discipline of nephrology. The performance of 1 155 087 unique renal filters was compared with the manual review. MAIN OUTCOME MEASURES: Sensitivity, specificity, precision, and accuracy of each filter. RESULTS: The best renal filters combined two to 14 terms or phrases and included the terms "kidney" with multiple endings (that is, truncation), "renal replacement therapy", "renal dialysis", "kidney function tests", "renal", "nephr" truncated, "glomerul" truncated, and "proteinuria". These filters achieved peak sensitivities of 97.8% and specificities of 98.5%. Performance of filters remained excellent in the validation phase. CONCLUSIONS: Medline can be filtered for the discipline of nephrology in a reliable manner. Storing these high performance renal filters in PubMed could help clinicians with their everyday searching. Filters can also be developed for other clinical disciplines by using similar methods.

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References

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