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dc.contributor.authorTakkouche ., Bahi
dc.contributor.authorPrada Ramallal, Guillermo José
dc.contributor.authorTakkouche, B.
dc.contributor.authorFigueiras Guzmán, Adolfo
dc.date.accessioned2021-10-14T09:18:59Z
dc.date.available2021-10-14T09:18:59Z
dc.date.issued2019
dc.identifier.issn1471-2288
dc.identifier.otherhttps://www.ncbi.nlm.nih.gov/pubmed/30871502
dc.identifier.otherhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6419460/pdf/12874_2019_Article_695.pdf
dc.identifier.urihttp://hdl.handle.net/20.500.11940/15531
dc.description.abstractBACKGROUND: The availability of clinical and therapeutic data drawn from medical records and administrative databases has entailed new opportunities for clinical and epidemiologic research. However, these databases present inherent limitations which may render them prone to new biases. We aimed to conduct a structured review of biases specific to observational clinical studies based on secondary databases, and to propose strategies for the mitigation of those biases. METHODS: Scoping review of the scientific literature published during the period 2000-2018 through an automated search of MEDLINE, EMBASE and Web of Science, supplemented with manually cross-checking of reference lists. We included opinion essays, methodological reviews, analyses or simulation studies, as well as letters to the editor or retractions, the principal objective of which was to highlight the existence of some type of bias in pharmacoepidemiologic studies using secondary databases. RESULTS: A total of 117 articles were included. An increasing trend in the number of publications concerning the potential limitations of secondary databases was observed over time and across medical research disciplines. Confounding was the most reported category of bias (63.2% of articles), followed by selection and measurement biases (47.0% and 46.2% respectively). Confounding by indication (32.5%), unmeasured/residual confounding (28.2%), outcome misclassification (28.2%) and "immortal time" bias (25.6%) were the subcategories most frequently mentioned. CONCLUSIONS: Suboptimal use of secondary databases in pharmacoepidemiologic studies has introduced biases in the studies, which may have led to erroneous conclusions. Methods to mitigate biases are available and must be considered in the design, analysis and interpretation phases of studies using these data sources.
dc.rightsAtribución 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleBias in pharmacoepidemiologic studies using secondary health care databases: a scoping review
dc.typeArtigoes
dc.authorsophosFigueiras Guzmán, Adolfo
dc.authorsophosPrada Ramallal, Guillermo José
dc.authorsophosTakkouche ., Bahi
dc.identifier.doi10.1186/s12874-019-0695-y
dc.identifier.pmid30871502
dc.identifier.sophos30925
dc.issue.number1
dc.journal.titleBMC Medical Research Methodology
dc.organizationServizo Galego de Saúde::Estrutura de Xestión Integrada (EOXI)::Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS)
dc.page.initial536es
dc.rights.accessRightsopenAccess
dc.subject.keywordIDIS
dc.typefidesArtículo Científico (incluye Original, Original breve, Revisión Sistemática y Meta-análisis)
dc.typesophosArtículo de Revisión
dc.volume.number19


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