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Validation Rules as a First Step for Data Quality: Pharmacovigilance Application in Portugal
Bárbara Costa1,2, Bruno Figueiredo2, Vera Pinheiro1,2,3
1CINTESIS, Faculty of Medicine, University of Porto, Portugal.
Studies in Health Technology and Informatics
|May 19, 2023
Summary
Improving patient safety through better tracking of Adverse Drug Reactions (ADRs) is vital. This study enhances the SIRAI application in Portugal with data validation rules and a scoring system to boost ADR monitoring effectiveness.
Area of Science:
- Pharmacovigilance and Drug Safety
- Health Informatics
- Data Quality Management
Background:
- Effective tracking and reporting of Adverse Drug Reactions (ADRs) are essential for safeguarding patient health.
- The SIRAI application in Portugal plays a key role in monitoring these events.
- Ensuring high data quality within pharmacovigilance systems is a recognized challenge.
Purpose of the Study:
- To enhance the data quality of the SIRAI application used for ADR reporting in Portugal.
- To develop and implement robust data validation rules.
- To create a scoring system for assessing individual records and the overall dataset quality.
Main Methods:
- Development of a comprehensive set of data validation rules tailored to ADR reporting.
- Implementation of a scoring mechanism to evaluate the quality of each ADR record.
- Creation of an aggregate scoring system to assess the overall quality of the SIRAI dataset.
Main Results:
- The implemented data validation rules identified and flagged potential data quality issues.
- The scoring system provided a quantifiable measure of data integrity for individual records and the dataset.
- Preliminary analysis indicated an improvement in the overall data quality of the SIRAI application.
Conclusions:
- The developed data validation rules and scoring system are effective in improving ADR data quality.
- Enhanced data quality in the SIRAI application will lead to more reliable pharmacovigilance and improved patient safety.
- This approach provides a scalable model for quality improvement in other pharmacovigilance systems.
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