The same free-text search strategy was applied in the 3 databases: (clinical–data* OR health–data* OR medical–data* OR prescription–data* OR administrative–data* OR epidemiologic–data* OR health–claim* OR administrative–claim* OR insurance–claim* OR claims–data* OR health–record* OR medical–record*) AND (confounding OR bias* OR missing–data OR misclassification) AND (observational OR epidemiolog* OR pharmacovigilance OR challenge*) AND drug, from Januto January 1, 2018. To avoid duplicated results, in EMBASE and Web of Science we used the option that enables journals indexed in MEDLINE to be excluded. Data-sources and search strategyĪn automated search of bibliographic databases was performed, with an initial search in MEDLINE, subsequently supplemented by EMBASE and Web of Science. The protocol for this scoping review is available on request from the corresponding author. We performed and reported our study based on the methodological guidance for the conduct of a scoping review from the Joanna Briggs Institute and the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) Extension guideline for Scoping Reviews. In this type of review, unlike other systematic reviews, the application of quality filters is not an initial priority. We carried out a scoping review, which is a methodological strategy that enables the results of an exploratory research to be summarized. We then propose possible strategies to control the biases identified in the review. The aim of this study was thus to review the literature of the last two decades in which the authors highlight the existence of some type of bias in observational clinical studies based on secondary data sources, in order to identify the most common biases and explore the perception of this issue in the pharmacoepidemiologic field over time and across medical research disciplines. Ĭonsequently, many researchers recommend caution and warn against the high risk of introducing biases when using these databases. Indeed, the utilization of secondary databases entail not only the limitations specific to observational epidemiologic research but those inherent to these specific types of sources, as well as the social and ethical challenges related to data privacy and security. However, swift and easy access to this information may be deceptively simple. Contributing to this is the perception that clinical trials are not always useful for evaluation of therapies in real-world practice, particularly those providing limited safety data. This availability of data has increased the interest of pharmacoepidemiologists in using secondary databases as sources of data for research. One of these fields is the health sector, due to the availability of clinical and therapeutic data drawn from medical records and administrative databases used for billing and other fiscal functions related to the provision of patient care (i.e. In recent decades, with advances of computer technology and the exponential growth in the quantity of data available, new opportunities for research in many fields have emerged. Methods to mitigate biases are available and must be considered in the design, analysis and interpretation phases of studies using these data sources. Suboptimal use of secondary databases in pharmacoepidemiologic studies has introduced biases in the studies, which may have led to erroneous conclusions. 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. Confounding was the most reported category of bias (63.2% of articles), followed by selection and measurement biases (47.0% and 46.2% respectively). An increasing trend in the number of publications concerning the potential limitations of secondary databases was observed over time and across medical research disciplines. ResultsĪ total of 117 articles were included. 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. 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 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. However, these databases present inherent limitations which may render them prone to new biases. The availability of clinical and therapeutic data drawn from medical records and administrative databases has entailed new opportunities for clinical and epidemiologic research.
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