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Development and validation of study filters for identifying controlled non-randomized studies in PubMed and Ovid MEDLINE.
Waffenschmidt, Siw; Navarro-Ruan, Tamara; Hobson, Nick; Hausner, Elke; Sauerland, Stefan; Haynes, R Brian.
Afiliação
  • Waffenschmidt S; Institute for Quality and Efficiency in Health Care, Cologne, Germany.
  • Navarro-Ruan T; Institute for Health Economics and Clinical Epidemiology, The University Hospital of Cologne, Cologne, Germany.
  • Hobson N; Health Information Research Unit, Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada.
  • Hausner E; Health Information Research Unit, Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada.
  • Sauerland S; Institute for Quality and Efficiency in Health Care, Cologne, Germany.
  • Haynes RB; Institute for Quality and Efficiency in Health Care, Cologne, Germany.
Res Synth Methods ; 11(5): 617-626, 2020 Sep.
Article em En | MEDLINE | ID: mdl-32472632
ABSTRACT
A retrospective analysis published by the German Institute for Quality and Efficiency in Health Care (IQWiG) in 2018 concluded that no filter for non-randomized studies (NRS) achieved sufficient sensitivity (≥92%), a precondition for comprehensive information retrieval. New NRS filters are therefore required, taking into account the challenges related to this study type. Our evaluation focused on the development of study filters for NRS with a control group ("controlled NRS"), as this study type allows the calculation of an effect size. In addition, we assumed that due to the more explicit search syntax, controlled NRS are easier to identify than non-controlled ones, potentially resulting in better performance measures of study filters for controlled NRS. Our aim was to develop study filters for identifying controlled NRS in PubMed and Ovid MEDLINE. We developed two new search filters that can assist clinicians and researchers in identifying controlled NRS in PubMed and Ovid MEDLINE. The reference set was based on 2110 publications in Medline extracted from 271 Cochrane reviews and on 4333 irrelevant references. The first filter maximizes sensitivity (92.42%; specificity 79.67%, precision 68.49%) and should be used when a comprehensive search is needed. The second filter maximizes specificity (92.06%; precision 82.98%, sensitivity 80.94%) and should be used when a more focused search is sufficient.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa / PubMed / Ferramenta de Busca Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa / PubMed / Ferramenta de Busca Idioma: En Ano de publicação: 2020 Tipo de documento: Article