The difference between data integrity & data quality in medical technology companies – and why you must care

Written by Rina Nir

The difference between data integrity & data quality in medical technology companies – and why you must care

Data is the lifeblood of any Life Sciences company – and trust is the heart.

For those of us that manage data, we cannot and will not allow drugs or medtech devices to be on the market unless we are certain about the integrity of the data that’s been associated with the research, development and production of those products.

This is, quite literally, a matter of life and death.

The shift in the management and storage of data into an electronic environment has particular challenges, as there are now masses of data that we don’t have control of — and recent trends make clear how critical it is we address this issue. The FDA reports for the last several years (from 2014 on) reveal a significant uptick of warning letters, with data integrity as the subject.. These include shared passwords, inability to verify data or audit trails, failure to review electronic data or contemporaneously recorded information, and so on.

If we are talking about the context of software or an application that is being marketed as a medical device, then it is incumbent on us that we do all we can to ensure that the correct procedures and processes are in place to create that software/application. That effort will support gaining the trust of regulators, and in turn, the public, who must have confidence that they’re buying efficacious, safe products.

To do so, you must understand the differences between data integrity and data quality in our industry, and create a common language for the gatekeepers that guide – and guard – them each.

What is data integrity & who’s in charge of it?

Data integrity has been an issue since ancient times, when information was first recorded on papyrus or in stone. What held true then remains to this day.

In order to ensure its veracity, data must be attributable, legible, contemporaneous, original (or if copied, unmanipulated), accurate, complete, consistent, enduring and available.

In medtech companies, it’s actually the quality managers who are focused on data integrity. These gatekeepers can be considered the protectors – the people whose job it is to ensure compliance so that their products are safe and efficacious.

What is data quality & who’s in charge of it?

While the focus of data integrity is to provide a value that can be both trusted now and in the future, the focus of data quality is to provide attributes that are related to the data value itself, such as context, metadata, and so on. This allows the data to be easily, efficiently and accurately sorted, searched, filtered and managed for use in a variety of contexts.

In medtech companies, the people who deal with the nuts and bolts of data, such as those who work in IT, engineering or process, are concerned with data quality. These gatekeepers can be considered the innovators — the people responsible for new software, features in medical devices and product releases.

The great communication divide

Data issues, like so many other business challenges, often are rooted in corporate culture.

It’s common for the leaders in a given organization to have a poor understanding of information technology. When an IT group is made responsible for all computing and software systems, and the people in that department don’t have an industry quality or compliance background, then data integrity is at risk.

Similarly, the quality units and other compliance stakeholders often have a poor understanding of how information systems work. This makes it extremely difficult for them to follow the data and work out the weak points.

Worse, this lack of understanding on both ends, between the innovators and the protectors, leads to a communication breakdowns, as neither speaks the other’s “language.”

How to bridge the data gap for greater success

Once you understand the difference between data integrity and data quality, then you can turn this common challenge into a massive opportunity to vastly improve business efficiencies. By introducing a language that innovators and protectors alike can speak, all elements of data can then be managed effectively – and compliantly.

In my opinion, the best way to bridge the gap is with a company-wide, paperless Computer Validation System that includes an integrated collaboration platform.

From my experience, the organizations that are more modern in their thinking and see their business as end-to-end are the winning companies of today, and I believe, in the future.

Those that struggle with old silos of capability, understanding and rigid job hierarchies — which unfortunately tend to be the bigger, more established companies — will be left behind.

The question is, will you help bridge the gap between the “protectors” and “innovators” in your company, and get the most efficiency in your business by understanding their language and what drives them, or will you just keep the same old traditional pharma hierarchies?

Thanks to Keith Williams for writing this article with reference to the Practical Solutions in CSV and SDLC for GXP & MedDev conference. (London, 3/10/2018)


Blog posts in this series:

  1. Ten Good Reasons to Use Jira for Your Quality Assurance Process
  2. Why Should Quality Assurance Be Difficult and Awkward? Take a Strategic View on Achieving Compliance (Focus on ISO 13485)
  3. Get Everybody Engaged With QA

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