Data integrity problems on the rise. Defined by the FDA as the “completeness, consistency, and accuracy of data … data should be attributable, legible, contemporaneously recorded, original or a true copy, and accurate,” data integrity processes require that there are mechanisms in place to prevent accidental and/or intentional unauthorized modification of the data.
Incorrect or false data related to product identity, quality, purity or potency has serious implications, which include patient injury, drug shortages, damage to corporate reputation, lost profits and both civil and criminal liability. More challenging to quantify is the impact of lost credibility with customers, employees and regulatory bodies.
Understanding individual quality systems is essential in evaluating the overall corporate approach to quality. The true test of a quality management system is how it works when things go wrong. A risk-based approach is appropriate for uncovering data integrity issues and the approach should be based on the perceived urgency, leadership’s commitment to quality and the role and remit of the individual making the assessment.
IQVIA takes a structured approach for characterizing and optimizing quality systems, there are five leading solutions for re-mediating and preventing data integrity problems:
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