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Getting to the bottom of data integrity
Safeguarding quality systems requires understanding the thinking that drives human behaviour

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MARTIN LUSH
President of NSF International’s
Health Sciences Pharma Biotech Division

In the pharmaceutical world, data integrity is fundamental to systems that ensure medicines are of the required quality. A global issue, data integrity is not restricted to one particular marketplace or region. It is also not a new issue—data integrity has been a problem for organizations for years and is not limited to the quality control (QC) labs.
Conventional wisdom has long held that documentation is enough to help ensure data integrity. But regulators have shown that breaches in data integrity can often stem from issues far deeper than the ability to file documents. Malicious intent, while it can exist, is extremely rare. This means most mistakes are preventable, and stem from behavior.

The Real Meaning of Data Integrity
The term data integrity, or DI, suggests basic accuracy or authenticity. DI issues should not be considered in isolation because in fact they are the symptom, not the cause. Education and the culture of supervision and management lie at the heart of these issues
Take these two examples of real training sessions that have two very different approaches to defining data integrity. The first emphasized DI’s ...




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