Data integrity refers to the accuracy, completeness, and consistency of data over its lifecycle, ensuring that it is not altered or destroyed in an unauthorized manner. In clinical trials, “data integrity” refers to the protection and preservation of the accuracy and reliability of the study data, from collection to analysis and reporting, to ensure the validity of the study results. This entails putting in place appropriate processes for data collection, storage, handling, and administration, as well as keeping an eye out for and averting any tampering or corruption of data, whether deliberate or unintentional.
Clinical trial data integrity risks can come from a wide range of sources and can significantly affect the validity and reliability of study outcomes.
Potential Risks of Data Integrity:
Following areas been identified as risk areas and are as follows,
- System Access to unauthorized users
- Lack of adequate training around data security and password policy
- System integration failures
- Computer applications/systems used in Clinical trial data handling are not compliant of 21 CFR Part 11
- Data deletion/changes to data points without corresponding explanation
- Data changes post completion of timepoints/milestones like Database lock/Interim analysis/Safety review.
- Inadequate measures in data transfers from one location to other any form/format.
- Data collected outside of noted protocol timepoints.
- Delayed reporting of data (missing the Data entry turnaround time)
- Data collection of bias induced patient assessments.
- Inaccurate date/timestamps due to technical malfunctions and
- device changes due to incorrect method of usage.
Ways to Improve Data Integrity:
Better Handling of Source Data:
- Source data should be considered primary data. The chain of custody for ensuring accuracy must always begin at the place that data is first created while maintaining a full history until it has expired and/or retired.
- Develop and implement clear and comprehensive Standard Operating Procedures (SOPs) for data collection, storage, management, and analysis.
- Implement checks and validations to ensure protocol required assessments are adequately performed.
- Proper training to all personnel involved in data collection, management, and analysis, to ensure that they are aware of their responsibilities and the importance of maintaining data integrity.
Enhanced Access Security:
- Measures should be taken to secure both physical and logical access.
- Given the constant and evolving threats to data, it’s important to implement physical security measures at all levels, including data centers, mobile devices, laptops, and desktops.
Better Data Control:
- Control measures to be implemented over who should access the data and defining the controls in procedures while accessing it.
- Control components like active directories, dynamic audit trails, and continuous encryption of data are regulated to help firms to protect electronic information and records.
By following these best practices and having a robust quality management system in place, organizations can effectively maintain the integrity of their clinical trial data and ensure the validity of their study results.
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