This blog covers the following topics:
- Understanding Duplicate Management
- Steps for Effective Duplicate Management
- Verifying Duplicates in Management
Table of Contents:
- Introduction
- Duplicates in databases
- Statistics on duplicates
- Identifying duplicates
- Key takeaways
- Conclusion
Introduction
In this comprehensive blog, we detail into the complexities of identifying and confirming duplicates within vast datasets.
We explore the possibilities associated with spotting duplicate files in a database.
Additionally, we highlight some nuanced considerations to keep in mind throughout the process.
Join us as we provide a thorough guide to effectively navigating this important aspect of data management.
Duplicates in Databases
- Duplicates are often possible in databases, resulting from human error and multiple reports for the same from various sources.
- This issue can have significant regulatory implications, making it essential for to know about duplicate identification.
- The duplication of cases is a critical data quality challenge that can severely impact signal analysis and lead to misleading clinical assessments.
We specialize in effective duplicate management, ensuring compliance with your regulatory requirements.
Statistics on Duplicates
Research suggests that duplicates may comprise as much as 5% of all reports.
Suspected report duplication is not evenly distributed; while most reports show no suspected duplicates, a small percentage contains several.
Higher rates of suspected duplicates observed in literature reports (11%) and reports involving fatal outcomes (5%), whereas reports from consumers and non-health professionals exhibit a lower rate of approximately 0.5%.
Identifying Duplicates
Managing duplicate reports typically involves two key steps: detection and confirmation of duplicates.
It is essential for every processor to know how to find duplicates.
Detection
Effectively searching for duplicates begins with entering the most relevant details one at a time.
- Duplicates can be identified even before a case is entered into the database.
- They can also be detected during periodic data reviews and the signal management process, where detailed analyses of cases are conducted.
The detection process involves narrowing down a large number of cases to zero by applying filters, which allows for the registration of new cases.
Duplicate searches rely on similarities in patient information, adverse reactions, and medicinal product data.
Different datasets may require different search criteria.
A simple table sorting reports by date of birth, age, sex, suspected or interacting medicinal products, adverse events, and country of incidence can effectively highlight potential duplicates.
Begin your search with the most relevant data, such as product name and country of incidence.
Remember that not all duplicates need to contain exact information. In many instances, added with new information, or certain details might be missing from the reports. For example, which could suggest a new event or a new administration of a drug.
Confirming Duplicates
Once potential duplicates are identified, manual confirmation by an assessor is essential.
A well-documented case, including a narrative, is necessary to determine if two cases are duplicates. Following a structured assessment, there are four possible outcomes:
- The case is not a duplicate.
- More information required.
- The case is a duplicate from a different sender.
- The case is a duplicate from the same sender.
Confirmation should be conducted by a knowledgeable assessor. To effectively compare similar reports:
- Avoid confirming duplicates based solely on limited information.
- Consider all available details from each individual report.
- If uncertainty arises, request follow-up information.
- Document all outcomes of the assessments.
Key Takeaways
Overlooking duplicates can lead to misleading information in signal detection systems.
Searching for duplicates involves narrowing down results by inputting relevant data.
Duplicates can be detected even before a case is entered into the database.
Known case identifiers relevant to duplicate detection should be systematically included in the ‘Other case identifiers in previous transmissions’ data element.
Conclusion
This guidance outlines the possibilities of identifying duplicates in a database, highlighting its importance for every data processor.
While you may be familiar with this process, we’ve presented it in a straightforward manner, including key nuances.
If you think we’ve overlooked anything important, please let us know so we can enhance this content. Thank you for reading!
Bibliography:
- Duplicate management and merging, n.d. Read the file
- EU Individual Case Safety Report (ICSR)1 Implementation Guide- Duplicates and merging, n.d. Read the file
- Kiguba, R., Isabirye, G., Mayengo, J., Owiny, J., Tregunno, P., Harrison, K., Pirmohamed, M., Ndagije, H.B., 2024. Navigating duplication in pharmacovigilance databases: a scoping review. BMJ Open 14, e081990. https://doi.org/10.1136/bmjopen-2023-081990
- Note for Guidance – EudraVigilance Human – Processing of safety messages and ICSRs: duplicates and merging, n.d. Read the file
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