Kidney Transplantation Search Filters for PubMed, Ovid Medline, and Embase

Lee, Christopher W.C.; Iansavichus, Arthur V.; Shariff, Salimah Z.; Wilczynski, Nancy L.; McKibbon, Ann; Rehman, Faisal; Garg, Amit X.

doi:10.1097/tp.0b013e318241987c

Cited by 9 publications

(16 citation statements)

References 6 publications

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“…Building on the same concepts our group has used to create novel high performance search filters for general nephrology and renal transplantation [15,18], we have succeeded in developing and validating search filters for glomerular disease that are highly sensitive and specific. All filters achieved a balance of at least 93.8% sensitivity and specificity.…”

Section: Discussionmentioning

confidence: 99%

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

Hildebrand

Iansavichus

Lee

et al. 2012

BMC Med Inform Decis Mak

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BackgroundTools 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.MethodsWe 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.ResultsHigh 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.ConclusionsPubMed, 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.

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Section: Discussionmentioning

confidence: 99%

“…More recently, topic-based search filters have started to emerge [15-17]. Within the area of nephrology, search filters already exist to retrieve renal information and articles relevant to kidney transplantation [15,18]. However, none of these filters were designed to enhance retrieval of articles relevant only to glomerular disease.…”

Section: Introductionmentioning

confidence: 99%

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

Hildebrand

Iansavichus

Lee

et al. 2012

BMC Med Inform Decis Mak

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“…This complements our work done to develop information filters for kidney transplantation (24) and general nephrology (3). Better access to dialysis information is important because dialysis patients have high morbidity and mortality, with high costs to health care systems.…”

Section: Strengths and Limitationsmentioning

confidence: 60%

Dialysis Search Filters for PubMed, Ovid MEDLINE, and Embase Databases

Iansavichus

Haynes

Lee

et al. 2012

Clinical Journal of the American Society of Nephrology

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SummaryBackground and objectives Physicians frequently search bibliographic databases, such as MEDLINE via PubMed, for best evidence for patient care. The objective of this study was to develop and test search filters to help physicians efficiently retrieve literature related to dialysis (hemodialysis or peritoneal dialysis) from all other articles indexed in PubMed, Ovid MEDLINE, and Embase.Design, setting, participants, & measurements A diagnostic test assessment framework was used to develop and test robust dialysis filters. The reference standard was a manual review of the full texts of 22,992 articles from 39 journals to determine whether each article contained dialysis information. Next, 1,623,728 unique search filters were developed, and their ability to retrieve relevant articles was evaluated.Results The high-performance dialysis filters consisted of up to 65 search terms in combination. These terms included the words "dialy" (truncated), "uremic," "catheters," and "renal transplant wait list." These filters reached peak sensitivities of 98.6% and specificities of 98.5%. The filters' performance remained robust in an independent validation subset of articles.Conclusions These empirically derived and validated high-performance search filters should enable physicians to effectively retrieve dialysis information from PubMed, Ovid MEDLINE, and Embase.

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“…By embedding the best evidence about searching into a predefined strategy, search filters seek to minimise variations and deficits in individuals’ searching knowledge and skills and can prevent ‘reinventing the wheel’ for commonly sought searches. Several studies have demonstrated search filter superiority in direct head‐to‐head comparisons with clinician subject specialist searches (Damarell & Tieman, ; Garg et al., ; Hildebrand et al., , ; Iansavichus et al., , , ; Lee, Iansavichus et al., ).…”

Section: Introductionmentioning

confidence: 99%

Topic search filters: a systematic scoping review

Damarell

May

Hammond

et al. 2018

Health Info Libraries J

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Background Searching for topics within large biomedical databases can be challenging, especially when topics are complex, diffuse, emerging or lack definitional clarity. Experimentally derived topic search filters offer a reliable solution to effective retrieval; however, their number and range of subject foci remain unknown. Objectives This systematic scoping review aims to identify and describe available experimentally developed topic search filters. Methods Reports on topic search filter development (1990‐) were sought using grey literature sources and 15 databases. Reports describing the conception and prospective development of a database‐specific topic search and including an objectively measured estimate of its performance (‘sensitivity’) were included. Results Fifty‐four reports met inclusion criteria. Data were extracted and thematically synthesised to describe the characteristics of 58 topic search filters. Discussion Topic search filters are proliferating and cover a wide range of subjects. Filter reports, however, often lack clear definitions of concepts and topic scope to guide users. Without standardised terminology, filters are challenging to find. Information specialists may benefit from a centralised topic filter repository and appraisal checklists to facilitate quality assessment. Conclusion Findings will help information specialists identify existing topic search filters and assist filter developers to build on current knowledge in the field.

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Kidney Transplantation Search Filters for PubMed, Ovid Medline, and Embase

Abstract: These kidney transplantation filters can now be used in Medline and Embase databases to improve clinician searching.

Cited by 9 publications

References 6 publications

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

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

Dialysis Search Filters for PubMed, Ovid MEDLINE, and Embase Databases

Topic search filters: a systematic scoping review

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