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Design and implementation of Metta, a metasearch engine for biomedical literature retrieval intended for systematic reviewers.

ABSTRACT: Individuals and groups who write systematic reviews and meta-analyses in evidence-based medicine regularly carry out literature searches across multiple search engines linked to different bibliographic databases, and thus have an urgent need for a suitable metasearch engine to save time spent on repeated searches and to remove duplicate publications from initial consideration. Unlike general users who generally carry out searches to find a few highly relevant (or highly recent) articles, systematic reviewers seek to obtain a comprehensive set of articles on a given topic, satisfying specific criteria. This creates special requirements and challenges for metasearch engine design and implementation.We created a federated search tool that is connected to five databases: PubMed, EMBASE, CINAHL, PsycINFO, and the Cochrane Central Register of Controlled Trials. Retrieved bibliographic records were shown online; optionally, results could be de-duplicated and exported in both BibTex and XML format.The query interface was extensively modified in response to feedback from users within our team. Besides a general search track and one focused on human-related articles, we also added search tracks optimized to identify case reports and systematic reviews. Although users could modify preset search options, they were rarely if ever altered in practice. Up to several thousand retrieved records could be exported within a few minutes. De-duplication of records returned from multiple databases was carried out in a prioritized fashion that favored retaining citations returned from PubMed.Systematic reviewers are used to formulating complex queries using strategies and search tags that are specific for individual databases. Metta offers a different approach that may save substantial time but which requires modification of current search strategies and better indexing of randomized controlled trial articles. We envision Metta as one piece of a multi-tool pipeline that will assist systematic reviewers in retrieving, filtering and assessing publications. As such, Metta may find wide utility for anyone who is carrying out a comprehensive search of the biomedical literature.

SUBMITTER: Smalheiser NR

PROVIDER: S-EPMC4375844 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Design and implementation of Metta, a metasearch engine for biomedical literature retrieval intended for systematic reviewers.

Smalheiser Neil R NR Lin Can C Jia Lifeng L Jiang Yu Y Cohen Aaron M AM Yu Clement C Davis John M JM Adams Clive E CE McDonagh Marian S MS Meng Weiyi W

Health information science and systems 20140110

<h4>Background</h4>Individuals and groups who write systematic reviews and meta-analyses in evidence-based medicine regularly carry out literature searches across multiple search engines linked to different bibliographic databases, and thus have an urgent need for a suitable metasearch engine to save time spent on repeated searches and to remove duplicate publications from initial consideration. Unlike general users who generally carry out searches to find a few highly relevant (or highly recent ...[more]

PMID: 25825665

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Project description:BackgroundAlthough peer review is widely considered to be the most credible way of selecting manuscripts and improving the quality of accepted papers in scientific journals, there is little evidence to support its use. Our aim was to estimate the effects on manuscript quality of either adding a statistical peer reviewer or suggesting the use of checklists such as CONSORT or STARD to clinical reviewers or both.Methodology and principal findingsInterventions were defined as 1) the addition of a statistical reviewer to the clinical peer review process, and 2) suggesting reporting guidelines to reviewers; with "no statistical expert" and "no checklist" as controls. The two interventions were crossed in a 2x2 balanced factorial design including original research articles consecutively selected, between May 2004 and March 2005, by the Medicina Clinica (Barc) editorial committee. We randomized manuscripts to minimize differences in terms of baseline quality and type of study (intervention, longitudinal, cross-sectional, others). Sample-size calculations indicated that 100 papers provide an 80% power to test a 55% standardized difference. We specified the main outcome as the increment in quality of papers as measured on the Goodman Scale. Two blinded evaluators rated the quality of manuscripts at initial submission and final post peer review version. Of the 327 manuscripts submitted to the journal, 131 were accepted for further review, and 129 were randomized. Of those, 14 that were lost to follow-up showed no differences in initial quality to the followed-up papers. Hence, 115 were included in the main analysis, with 16 rejected for publication after peer review. 21 (18.3%) of the 115 included papers were interventions, 46 (40.0%) were longitudinal designs, 28 (24.3%) cross-sectional and 20 (17.4%) others. The 16 (13.9%) rejected papers had a significantly lower initial score on the overall Goodman scale than accepted papers (difference 15.0, 95% CI: 4.6-24.4). The effect of suggesting a guideline to the reviewers had no effect on change in overall quality as measured by the Goodman scale (0.9, 95% CI: -0.3-+2.1). The estimated effect of adding a statistical reviewer was 5.5 (95% CI: 4.3-6.7), showing a significant improvement in quality.Conclusions and significanceThis prospective randomized study shows the positive effect of adding a statistical reviewer to the field-expert peers in improving manuscript quality. We did not find a statistically significant positive effect by suggesting reviewers use reporting guidelines.

Dataset Information

Design and implementation of Metta, a metasearch engine for biomedical literature retrieval intended for systematic reviewers.

Publications

Design and implementation of Metta, a metasearch engine for biomedical literature retrieval intended for systematic reviewers.

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