What does data integrity mean and how does it affect life sciences organisations?

To kick this off, data integrity can be applied to any type of data but for the purposes of this article we’ll focus on the integrity of data generated and held by life sciences organisations. It’s also worth pointing out that we could go into a lot more detail but we wanted this to provide an overview of this topic and how it relates to life sciences organisations specifically.  

In its broadest sense, data integrity refers to the accuracy, quality, and consistency of data. When stored over time and across multiple formats, data can become prone to degradation. 

Ensuring data integrity – and therefore its trustworthiness – is a constant, ongoing task.   

Why is data integrity so important?  

Data integrity is about much more than just checking files. It proves that the data that is being used is reliable – and for those looking to replicate or validate the results of a clinical trial, this is an essential requirement. 

Ensuring the accuracy and completeness of your clinical data is crucial for many reasons, including: 

• To enable interrogation 
• Prove the science of the research you have conducted 
• Provide robust and trustworthiness evidence behind your research findings  
• Enables appropriate decisions to be made. If data is untrustworthy, inaccurate, unreliable (etc.) inspectors are unable to verify that data in order to secure marketing approval. 

How can you manage records and data integrity? 

It’s safe to say that the majority of datasets and assets which will come under scrutiny will be digital.  

Join us for our next instalments where we’ll delve into data integrity and the role of the ALCOA principles and how data integrity and digital archiving are the perfect match.