Carpenter, Christopher R

Fowler, Susan A

Rogers, Monica

Yaeger, Lauren H

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Washington University School of MedicineDigital Commons@BeckerBecker Library Publications and Presentations Becker Medical Library2013Validating a search filter for diagnostic sensitivityand specificitySusan A. FowlerWashington University School of Medicine in St. LouisLauren H. YaegerWashington University School of Medicine in St. LouisMonica RogersWashington University School of Medicine in St. LouisChristopher R. CarpenterWashington University School of Medicine in St. LouisFollow this and additional works at: http://digitalcommons.wustl.edu/becker_pubsThis Presentation Poster is brought to you for free and open access by the Becker Medical Library at Digital Commons@Becker. It has been acceptedfor inclusion in Becker Library Publications and Presentations by an authorized administrator of Digital Commons@Becker. For more information,please contact engeszer@wustl.edu.Recommended CitationFowler, Susan A.; Yaeger, Lauren H.; Rogers, Monica; and Carpenter, Christopher R., "Validating a search filter for diagnosticsensitivity and specificity." 2013 Medical Library Association Annual Meeting and Exhibition, Boston, Massachusetts. 2013. Paper 37.http://digitalcommons.wustl.edu/becker_pubs/37Validating a Search Filter for Diagnostic Sensitivity and Specificity  Susan A. Fowler, MLIS, Lauren H. Yaeger, MA, MLIS, Monica Rogers, MLIS, Christopher R. Carpenter, MD, MS  1. Create a pool. We used a thorough search strategy for adult septic arthritis created for a systematic review and limited the pool to the last five years in PubMed.       2. Create filter. We created a filter for DSS  by harvesting terms from standard indices and on-topic articles.  Run filter within pool. We ran our DSS filter within the Septic Arthritis pool in PubMed limited to the last five years.    Review results for filter and pool search results using the 2X2 table for DSS from…  About DSS Not About DSS DSS Search Results TP = 49 FP = 11 Pool FN = 123 TN = 642  Sensitivity (Recall) 49/49+123 = 79%  Specificity (Precision) 642/11+642 = 98% There are no clear step by step instructions on how to create or validate a search filter.   While we based our methods on Haynes, et al., we created our pool differently and it was much smaller. Haynes used articles in 160 journal titles for the year 2000 resulting in a pool of 49,028 articles. Our Septic Arthritis search was limited to the last 5 years and included 765 articles.    Our responsibilities represent the typical work load of an academic medical librarian and this project took three years, fitting it in where we could. Thus, it is not realistic to validate every search strategy created for systematic reviews.     Discussion Conclusion The DSS filter achieved 79% sensitivity and 98% specificity therefore it is an effective filter for locating articles on diagnostic sensitivity and specificity in PubMed.  Results TP = True Positive (DSS Filter search results that are truly about diagnostic sensitivity and specificity)  FP = False Positive (DSS Filter search results that are not about diagnostic sensitivity and specificity)    TN = True Negative (All search results that are not about diagnostic sensitivity and specificity)  FN = False Negative (All search results that are about  diagnostic sensitivity and specificity) 4. 3. Objective To create and validate a search filter for diagnostic sensitivity and specificity (DSS) in PubMed for use in systematic reviews.  Based on work by Haynes and the Hedges Team to validate the PubMed Clinical Query for Diagnosis.  Methods http://www.ncbi.nlm.nih.gov/books/NBK3827/#pubmedhelp.Clinical_Queries_Filters 

Validating a search filter for diagnostic sensitivity and specificity

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Validating a search filter for diagnostic sensitivity and specificity

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