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  • Clinical Data Validation

    Disambiguation: Clinical data validation means checking clinical data for correctness and completeness. Clinical database validation is making sure that clinical databases perform the functions required by regulations and guidances and is on another page.

    What is Clinical Data Validation?

    Data validation is a series of documented tests of the data with the goal of ensuring the quality and integrity of the data.

    More specifically, validation is usually concerned with checking four of the eight characteristics of good clinical data – these characteristics are from the first guidance and the first other reference listed below. The eight characteristics are:

    Data validation tests usually check the original, accurate, complete, and consistent aspects of the data.

    Why does Clinical Data need Validation?

    From a business perspective, the data are how the FDA, other regulators, and business partners evaluate the worth of the product. From an ethical perspective, clinical data affect treatment decisions, which affect patient health, and the patient population in question is virtually all of the United States and a significant fraction of the rest of the world. For both of these reasons, clinical data quality and integrity are critical.

    Despite this, few regulations talk about data validation directly. Instead, the regulations and guidances focus on requirements that the data handling systems must meet to ensure data quality and integrity. Regulations and guidances that do mention clinical data validation, or a part of the process, are listed below.

    What is the Validation Process?

    The general outline for data validation is listed below. However, the validation process is complex and dependent on the data captured, business and regulatory concerns, the data management software used, and several other factors, so there are many possible variations and options.

    Even after database lock, analysts may run further checks to determine if any changes are necessary in order to produce the analysis datasets.

    Regulations and Guidances

    Other References