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    Epistemonikos: a comprehensive database of systematic reviews for health decision-making

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    Author
    Rada, G; Perez, D; Araya-Quintanilla, F; Avila, C; Bravo-Soto, G; Bravo-Jeria, R; Canepa, A; Capurro, D; Castro-Gutierrez, V; Contreras, V; ...
    Date
    2020-11-30
    Source Title
    BMC Medical Research Methodology
    Publisher
    BMC
    University of Melbourne Author/s
    Capurro, Daniel
    Affiliation
    Computing and Information Systems
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Rada, G., Perez, D., Araya-Quintanilla, F., Avila, C., Bravo-Soto, G., Bravo-Jeria, R., Canepa, A., Capurro, D., Castro-Gutierrez, V., Contreras, V., Edwards, J., Faundez, J., Garrido, D., Jimenez, M., Llovet, V., Lobos, D., Madrid, F., Morel-Marambio, M., Mendoza, A. ,... Zilleruelo-Ramos, R. (2020). Epistemonikos: a comprehensive database of systematic reviews for health decision-making. BMC MEDICAL RESEARCH METHODOLOGY, 20 (1), https://doi.org/10.1186/s12874-020-01157-x.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/252796
    DOI
    10.1186/s12874-020-01157-x
    Open Access URL
    https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-020-01157-x
    Open Access at PMC
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708132
    Abstract
    BACKGROUND: Systematic reviews allow health decisions to be informed by the best available research evidence. However, their number is proliferating quickly, and many skills are required to identify all the relevant reviews for a specific question. METHODS AND FINDINGS: We screen 10 bibliographic databases on a daily or weekly basis, to identify systematic reviews relevant for health decision-making. Using a machine-based approach developed for this project we select reviews, which are then validated by a network of more than 1000 collaborators. After screening over 1,400,000 records we have identified more than 300,000 systematic reviews, which are now stored in a single place and accessible through an easy-to-use search engine. This makes Epistemonikos the largest database of its kind. CONCLUSIONS: Using a systematic approach, recruiting a broad network of collaborators and implementing automated methods, we developed a one-stop shop for systematic reviews relevant for health decision making.

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