Data integrity refers to the accuracy and consistency of data throughout the data life cycle and is the opposite of data loss. Businesses are essentially houses of cards and are only as robust as the data that drive their information, decisions, and value. For these reasons, it is important that data is recorded exactly as it was collected and that when recalled at a later date, it is the same as it was when it was originally collected and recorded. It is the goal that nothing changes the data, or induces errors, from data entry to the time of use
The FDA uses the acronym ALCOA to describe data integrity standards. By this acronym, data should be:
- Attributable – it should be clearly evident who observed and recorded the data, when it was observed and recorded, and what the subject of the data is.
- Legible – data should be easy to understand, permanently recorded, with original records and entries preserved for reference.
- Contemporaneous – data should be recorded as it was observed at the time it was executed.
- Original – Source data should be in its original form and accessible.
- Accurate – data should be free from errors and comply with an organization’s standard operating procedures.
As data have evolved from paper records to digital information, it has become important to develop new methods to assure data integrity. The following will help minimize data risk and ensure data integrity for your organization:
Ensure all computer systems are reliable
While it is an FDA regulation, 21 CFR Part 11 is a good guide to ensure that your electronic records are trustworthy, reliable, and equivalent to paper records.
Follow a software lifecycle
This usually applies to software development but even if you aren’t in the software development business, you should ensure your business software is current with best business practices in your industry.
Work with vendors to ensure your software produces a consistent product. Have them install, test your systems, and provide documentation that they meet best practices for your industry.
Implement audit trails
Automate and maintain records of data transactions with time and date stamps, identity of user, history of changes and deletions. This will ensure the trustworthiness of your data and will demonstrate the records have not been tampered with.
Limit system access
Require documented logins to computer and network systems. Ensure appropriate database access is controlled, managed, and documented.
Implement Quality Management Systems
Establish best practices and workflows with standard operating procedures to ensure repeatable methods.
Train all users on proper data management practices and maintain records of their training.
Conduct periodic internal audits
This will ensure, and will provide evidence, that all procedures have been followed and the data are accurate, therefore demonstrating data integrity.
There are several opportunities for mistakes to happen in the data acquisition and storage workflow. This could be from a manual data entry mistake or the storage of an improper data type. Take the steps to ensure data integrity in your organization to get the most value from your data and to provide the best service to your stakeholders.
I hope this post has provided you some insight into the importance of data integrity and how you can achieve it. If it has, please comment below. If you want to learn more, follow me on Twitter.