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      Optimal database combinations for literature searches in systematic reviews: a prospective exploratory study

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          Abstract

          Background

          Within systematic reviews, when searching for relevant references, it is advisable to use multiple databases. However, searching databases is laborious and time-consuming, as syntax of search strategies are database specific. We aimed to determine the optimal combination of databases needed to conduct efficient searches in systematic reviews and whether the current practice in published reviews is appropriate. While previous studies determined the coverage of databases, we analyzed the actual retrieval from the original searches for systematic reviews.

          Methods

          Since May 2013, the first author prospectively recorded results from systematic review searches that he performed at his institution. PubMed was used to identify systematic reviews published using our search strategy results. For each published systematic review, we extracted the references of the included studies. Using the prospectively recorded results and the studies included in the publications, we calculated recall, precision, and number needed to read for single databases and databases in combination. We assessed the frequency at which databases and combinations would achieve varying levels of recall (i.e., 95%). For a sample of 200 recently published systematic reviews, we calculated how many had used enough databases to ensure 95% recall.

          Results

          A total of 58 published systematic reviews were included, totaling 1746 relevant references identified by our database searches, while 84 included references had been retrieved by other search methods. Sixteen percent of the included references (291 articles) were only found in a single database; Embase produced the most unique references ( n = 132). The combination of Embase, MEDLINE, Web of Science Core Collection, and Google Scholar performed best, achieving an overall recall of 98.3 and 100% recall in 72% of systematic reviews. We estimate that 60% of published systematic reviews do not retrieve 95% of all available relevant references as many fail to search important databases. Other specialized databases, such as CINAHL or PsycINFO, add unique references to some reviews where the topic of the review is related to the focus of the database.

          Conclusions

          Optimal searches in systematic reviews should search at least Embase, MEDLINE, Web of Science, and Google Scholar as a minimum requirement to guarantee adequate and efficient coverage.

          Electronic supplementary material

          The online version of this article (10.1186/s13643-017-0644-y) contains supplementary material, which is available to authorized users.

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          Most cited references17

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          Systematic reviews need systematic searchers.

          This paper will provide a description of the methods, skills, and knowledge of expert searchers working on systematic review teams. Systematic reviews and meta-analyses are very important to health care practitioners, who need to keep abreast of the medical literature and make informed decisions. Searching is a critical part of conducting these systematic reviews, as errors made in the search process potentially result in a biased or otherwise incomplete evidence base for the review. Searches for systematic reviews need to be constructed to maximize recall and deal effectively with a number of potentially biasing factors. Librarians who conduct the searches for systematic reviews must be experts. Expert searchers need to understand the specifics about data structure and functions of bibliographic and specialized databases, as well as the technical and methodological issues of searching. Search methodology must be based on research about retrieval practices, and it is vital that expert searchers keep informed about, advocate for, and, moreover, conduct research in information retrieval. Expert searchers are an important part of the systematic review team, crucial throughout the review process-from the development of the proposal and research question to publication.
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            The contribution of databases to the results of systematic reviews: a cross-sectional study

            Background One of the best sources for high quality information about healthcare interventions is a systematic review. A well-conducted systematic review includes a comprehensive literature search. There is limited empiric evidence to guide the extent of searching, in particular the number of electronic databases that should be searched. We conducted a cross-sectional quantitative analysis to examine the potential impact of selective database searching on results of meta-analyses. Methods Our sample included systematic reviews (SRs) with at least one meta-analysis from three Cochrane Review Groups: Acute Respiratory Infections (ARI), Infectious Diseases (ID), Developmental Psychosocial and Learning Problems (DPLP) (n = 129). Outcomes included: 1) proportion of relevant studies indexed in each of 10 databases; and 2) changes in results and statistical significance of primary meta-analysis for studies identified in Medline only and in Medline plus each of the other databases. Results Due to variation across topics, we present results by group (ARI n = 57, ID n = 38, DPLP n = 34). For ARI, identification of relevant studies was highest for Medline (85 %) and Embase (80 %). Restricting meta-analyses to trials that appeared in Medline + Embase yielded fewest changes in statistical significance: 53/55 meta-analyses showed no change. Point estimates changed in 12 cases; in 7 the change was less than 20 %. For ID, yield was highest for Medline (92 %), Embase (81 %), and BIOSIS (67 %). Restricting meta-analyses to trials that appeared in Medline + BIOSIS yielded fewest changes with 1 meta-analysis changing in statistical significance. Point estimates changed in 8 of 31 meta-analyses; change less than 20 % in all cases. For DPLP, identification of relevant studies was highest for Medline (75 %) and Embase (62 %). Restricting meta-analyses to trials that appeared in Medline + PsycINFO resulted in only one change in significance. Point estimates changed for 13 of 33 meta-analyses; less than 20 % in 9 cases. Conclusions Majority of relevant studies can be found within a limited number of databases. Results of meta-analyses based on the majority of studies did not differ in most cases. There were very few cases of changes in statistical significance. Effect estimates changed in a minority of meta-analyses but in most the change was small. Results did not change in a systematic manner (i.e., regularly over- or underestimating treatment effects), suggesting that selective searching may not introduce bias in terms of effect estimates. Electronic supplementary material The online version of this article (doi:10.1186/s12874-016-0232-1) contains supplementary material, which is available to authorized users.
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              Evaluation of a new method for librarian‐mediated literature searches for systematic reviews

              Objective To evaluate and validate the time of completion and results of a new method of searching for systematic reviews, the exhaustive search method (ESM), using a pragmatic comparison. Methods Single‐line search strategies were prepared in a text document. Term completeness was ensured with a novel optimization technique. Macros in MS Word converted the syntaxes between databases and interfaces almost automatically. We compared search characteristics, such as number of search terms and databases, and outcomes, such as number of included and retrieved references and precision, from ESM searches and other Dutch academic hospitals identified by searching PubMed for systematic reviews published between 2014 and 2016. We compared time to perform the ESM with a secondary comparator of recorded search times from published literature and contact with authors to acquire unpublished data. Results We identified 73 published Erasmus MC systematic reviews and 258 published by other Dutch academic hospitals meeting our criteria. We pooled search time data from 204 other systematic reviews. The ESM searches differed by using 2 times more databases, retrieving 44% more references, including 20% more studies in the final systematic review, but the time needed for the search was 8% of that of the control group. Similarities between methods include precision and the number of search terms. Conclusions The evaluated similarities and differences suggest that the ESM is a highly efficient way to locate more references meeting the specified selection criteria in systematic reviews than traditional search methods. Further prospective research is required.
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                Author and article information

                Contributors
                +31 10 7043785 , w.bramer@erasmusmc.nl
                mlrethlefsen@gmail.com
                jos@systematic-reviews.com
                o.franco@erasmusmc.nl
                Journal
                Syst Rev
                Syst Rev
                Systematic Reviews
                BioMed Central (London )
                2046-4053
                6 December 2017
                6 December 2017
                2017
                : 6
                : 245
                Affiliations
                [1 ]ISNI 000000040459992X, GRID grid.5645.2, Medical Library, Erasmus MC, , Erasmus University Medical Centre Rotterdam, ; 3000 CS Rotterdam, the Netherlands
                [2 ]ISNI 0000 0001 2193 0096, GRID grid.223827.e, Spencer S. Eccles Health Sciences Library, , University of Utah, ; Salt Lake City, Utah USA
                [3 ]ISNI 0000 0004 0450 3334, GRID grid.450936.d, Kleijnen Systematic Reviews Ltd., ; York, UK
                [4 ]ISNI 0000 0001 0481 6099, GRID grid.5012.6, School for Public Health and Primary Care (CAPHRI), , Maastricht University, ; Maastricht, the Netherlands
                [5 ]ISNI 000000040459992X, GRID grid.5645.2, Department of Epidemiology, Erasmus MC, , Erasmus University Medical Centre Rotterdam, ; Rotterdam, the Netherlands
                Article
                644
                10.1186/s13643-017-0644-y
                5718002
                29208034
                a071ef9d-e0c8-41a3-89e1-8add39c6123d
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 21 August 2017
                : 24 November 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100006108, National Center for Advancing Translational Sciences;
                Award ID: UL1TR001067
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Public health
                databases, bibliographic,review literature as topic,sensitivity and specificity,information storage and retrieval

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