Development↦Data Management↦Data Quality↦Quality Assurance
What is it? Why is it important?
Data Quality Assurance (DataQA) includes a set of activities, processes, and implemented measures to ensure that study data is of high-quality. High-quality data grants confidence that obtained study results are reliable and credible
In order to comply with DataQA goals, the SP-INV must implement a risk-based strategy that guarantees that study data is correctly collected, stored, shared, and analysed. As a consequence, applicable data management processes and guidelines should be in place.
What do I need to do?
As a SP-INV:
- Identify potential risks that might negatively affect the quality of your study data (e.g. documentation errors, data input errors, incompatible software updates, untrained staff)
- Evaluate and prioritise risks based on likelihood of occurrence and impact on data quality
- Based on your risk assessment (RAF) define applicable risk control-measures
- Train staff on data mangement procedures and the implementation of risk-control-measures
- Define a surveillance plan in order to check the efficacy of risk-control measures during study conduct, including the emergence of new risks (e.g. process verification and training)
- Document your risk assessment including preventive measures in the study Risk Assessment form
More
Example of risk-control-measures
- Personalise CDMA set-up in order to support ongoing data quality (e.g. variable specification)
- Perform system validation and functionality testing upon CDMS updates
- Implement planned monitoring visits during study conduct in order to check if data entered in the study database corresponds to the source data
- Ensure ongoing system maintenance and security, including data backup and recovery due to system failure
- Define data export/import processes that control for unwanted data alterations, data loss, and a risk to data confidentiality
Where can I get help?
Your local CTU↧ can support you with experienced staff regarding this topic
Basel, Departement Klinische Forschung, CTU, dkf.unibas.ch
Lugano, Clinical Trials Unit, CTU-EOC, www.ctueoc.ch
Bern, Clinical Trials Unit, CTU, www.ctu.unibe.ch
Geneva, Clinical Research Center, CRC, crc.hug.ch
Lausanne, Clinical Research Center, CRC, www.chuv.ch
St. Gallen, Clinical Trials Unit, CTU, www.kssg.ch
Zürich, Clinical Trials Center, CTC, www.usz.ch
References
ICH GCP E6(R2) – see in particular guidelines
- 5.1 for Quality assurance and control
- 5.5. Trial Management, data handling, and record-keeping
ISO 9001:2015 – Quality Management Systems – Requirements