About this resource

    Type of resources
    Reading
    Education level(s)
    College / Upper Division (Undergraduates), Graduate / Professional
    Primary user(s)
    Student, Teacher
    Subject area(s)
    Life Science, Physical Science
    Language(s)
    English
    Cluster
    Replication Crisis and Credibility Revolution
    Last updated
    19 December 2024

    Building transparency and reproducibility into the practice of pharmacoepidemiology and outcomes research

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    Level College / Upper Division (Undergraduates), Graduate / Professional · For Student, Teacher · Language English

    Abstract

    Real-world evidence (RWE) studies are increasingly used to inform policy and clinical decisions. However, there remain concerns about the credibility and reproducibility of RWE studies. While there is universal agreement on the critical importance of transparent and reproducible science, the building blocks of open science practice that are common across many disciplines have not yet been built into routine workflows for pharmacoepidemiology and outcomes researchers. Observational researchers should highlight the level of transparency of their studies by providing a succinct statement addressing study transparency with the publication of every paper, poster, or presentation that reports on an RWE study. In this paper, we propose a framework for an explicit transparency statement that declares the level of transparency a given RWE study has achieved across 5 key domains: (1) protocol, (2) preregistration, (3) data, (4) code-sharing, and (5) reporting checklists. The transparency statement outlined in the present paper can be used by research teams to proudly display the open science practices that were used to generate evidence designed to inform public health policy and practice. While transparency does not guarantee validity, such a statement signals confidence from the research team in the scientific choices that were made.

    Keywords Transparency · Reproducibility · Real-World Evidence · Pharmacoepidemiology