Development of an efficient search filter to retrieve systematic reviews from PubMed

Objective: Locating systematic reviews is essential for clinicians and researchers when creating or updating reviews and for decision-making in health care. This study aimed to develop a search filter for retrieving systematic reviews that improves upon the performance of the PubMed systematic revie...

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Autores principales:	José Antonio Salvador-Oliván, Gonzalo Marco-Cuenca, Rosario Arquero-Avilés
Formato:	article
Lenguaje:	EN
Publicado:	University Library System, University of Pittsburgh 2021
Materias:	search filter systematic reviews pubmed information retrieval search strategies Bibliography. Library science. Information resources Z Medicine R
Acceso en línea:	https://doaj.org/article/e83a7acfea2b4e569d38fd72a3c05795
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spelling	oai:doaj.org-article:e83a7acfea2b4e569d38fd72a3c057952021-11-22T20:41:00ZDevelopment of an efficient search filter to retrieve systematic reviews from PubMed1536-50501558-943910.5195/jmla.2021.1223https://doaj.org/article/e83a7acfea2b4e569d38fd72a3c057952021-11-01T00:00:00Zhttps://jmla.pitt.edu/ojs/jmla/article/view/1223https://doaj.org/toc/1536-5050https://doaj.org/toc/1558-9439Objective: Locating systematic reviews is essential for clinicians and researchers when creating or updating reviews and for decision-making in health care. This study aimed to develop a search filter for retrieving systematic reviews that improves upon the performance of the PubMed systematic review search filter. Methods: Search terms were identified from abstracts of reviews published in Cochrane Database of Systematic Reviews and the titles of articles indexed as systematic reviews in PubMed. Both the precision of the candidate terms and the number of systematic reviews retrieved from PubMed were evaluated after excluding the subset of articles retrieved by the PubMed systematic review filter. Terms that achieved a precision greater than 70% and relevant publication types indexed with MeSH terms were included in the filter search strategy. Results: The search strategy used in our filter added specific terms not included in PubMed’s systematic review filter and achieved a 61.3% increase in the number of retrieved articles that are potential systematic reviews. Moreover, it achieved an average precision that is likely greater than 80%. Conclusions: The developed search filter will enable users to identify more systematic reviews from PubMed than the PubMed systematic review filter with high precision.José Antonio Salvador-OlivánGonzalo Marco-CuencaRosario Arquero-AvilésUniversity Library System, University of Pittsburgharticlesearch filtersystematic reviewspubmedinformation retrievalsearch strategiesBibliography. Library science. Information resourcesZMedicineRENJournal of the Medical Library Association, Vol 109, Iss 4 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	search filter systematic reviews pubmed information retrieval search strategies Bibliography. Library science. Information resources Z Medicine R
spellingShingle	search filter systematic reviews pubmed information retrieval search strategies Bibliography. Library science. Information resources Z Medicine R José Antonio Salvador-Oliván Gonzalo Marco-Cuenca Rosario Arquero-Avilés Development of an efficient search filter to retrieve systematic reviews from PubMed
description	Objective: Locating systematic reviews is essential for clinicians and researchers when creating or updating reviews and for decision-making in health care. This study aimed to develop a search filter for retrieving systematic reviews that improves upon the performance of the PubMed systematic review search filter. Methods: Search terms were identified from abstracts of reviews published in Cochrane Database of Systematic Reviews and the titles of articles indexed as systematic reviews in PubMed. Both the precision of the candidate terms and the number of systematic reviews retrieved from PubMed were evaluated after excluding the subset of articles retrieved by the PubMed systematic review filter. Terms that achieved a precision greater than 70% and relevant publication types indexed with MeSH terms were included in the filter search strategy. Results: The search strategy used in our filter added specific terms not included in PubMed’s systematic review filter and achieved a 61.3% increase in the number of retrieved articles that are potential systematic reviews. Moreover, it achieved an average precision that is likely greater than 80%. Conclusions: The developed search filter will enable users to identify more systematic reviews from PubMed than the PubMed systematic review filter with high precision.
format	article
author	José Antonio Salvador-Oliván Gonzalo Marco-Cuenca Rosario Arquero-Avilés
author_facet	José Antonio Salvador-Oliván Gonzalo Marco-Cuenca Rosario Arquero-Avilés
author_sort	José Antonio Salvador-Oliván
title	Development of an efficient search filter to retrieve systematic reviews from PubMed
title_short	Development of an efficient search filter to retrieve systematic reviews from PubMed
title_full	Development of an efficient search filter to retrieve systematic reviews from PubMed
title_fullStr	Development of an efficient search filter to retrieve systematic reviews from PubMed
title_full_unstemmed	Development of an efficient search filter to retrieve systematic reviews from PubMed
title_sort	development of an efficient search filter to retrieve systematic reviews from pubmed
publisher	University Library System, University of Pittsburgh
publishDate	2021
url	https://doaj.org/article/e83a7acfea2b4e569d38fd72a3c05795
work_keys_str_mv	AT joseantoniosalvadorolivan developmentofanefficientsearchfiltertoretrievesystematicreviewsfrompubmed AT gonzalomarcocuenca developmentofanefficientsearchfiltertoretrievesystematicreviewsfrompubmed AT rosarioarqueroaviles developmentofanefficientsearchfiltertoretrievesystematicreviewsfrompubmed
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Development of an efficient search filter to retrieve systematic reviews from PubMed

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