What is it? Why is it important?

Quality Management includes a set of activities, processes, and implemented measures that ensure that study data is of high-quality.

Data quality:

  • Is within the responsibility of the SP-INV who must guarantee the quality of all collected study data (variables)
  • Depends on whether data was correctly documented, collected, handled and analysed. As a consequence, data handling processes and guidelines should be in place
  • Is important because it grants confidence that given study results are reliable and credible

When implementing data quality measures, a risk-based approach should be used.


A risk-based approach includes to:

  • Identify potential risks to data quality (e.g. documentation errors, data input errors, incompatible software updates, untrained staff responsible for data input)
  • Evaluate risks and their likelihood of occurrence, ability to be detected and expected impact on data quality
  • Based on risk evaluation prioritise risks and define risk control measures
  • Plan periodic risk reviews during study conduct so as to
    • Evaluate the ongoing efficiency of any implemented mitigating measures
    • Identify new risks

What do I need to do?

Means to ensure data quality include:

  • The identification of potential risks that might negatively affect your data, including strategies able to mitigate these risks
  • The introduction of respective processes and supporting documents (e.g. SOPs, WIs, checklists)
  • Establish responsibilities and train study staff on data handling procedures, mitigating measures and its ongoing effectiveness during study conduct
  • Means to personalise CDMS setup in order to support ongoig data quality
  • Monitor correct data collection, processing and handling procedures. Plan a risk-based monitoring strategy applicable to the study
  • As required perform system validation and functionality testing
  • Ensure ongoing system maintenance and security, including ongoing data backup and recovery due to system failure
  • Applicable archiving procedures

For more information refer to Quality and Risk and Monitoring in this Trial Guide.

Where can I get help?

Your local CTU can support you with experienced staff regarding this topic


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


  • CDMS – Clinical Data Management System
  • CTU – Clinical Trials Unit
  • ISO – International Organization for Standardization
  • SOP – Standard Operating Procedures
  • SP-INV – Sponsor-Investigator
  • WI – Working Instructions
Development ↦ Data Handling ↦ Data Quality ↦ Quality Management

Provides some background knowledge and basic definitions

Basic Protocol
Basic Statistics
Basic Monitoring
Basic Drug or Device
Basic Biobanking

Starts with a study idea

Ends after having assessed and evaluated study feasibility

Concept Protocol
Concept Statistics
Concept Drug or Device
Concept Biobanking

Starts with confidence that the study is feasible

Ends after having received ethics and regulatory approval

Development Protocol
Development Statistics
Development Drug or Device
Development Biobanking

Starts with ethics and regulatory approval

Ends after successful study initiation

Set-Up Protocol
Set-Up Ethics and Laws
Set-Up Statistics
Set-Up Quality and Risk
Set-Up Drug or Device
Set-Up Biobanking

Starts with participant recruitment

Ends after the last participant has completed the last study visit

Conduct Protocol
Conduct Statistics
Conduct Drug or Device
Conduct Biobanking

Starts with last study visit completed

Ends after study publication and archiving

Completion Protocol
Completion Statistics
Completion Drug or Device
Completion Biobanking
Current Path (click to copy): Development ↦ Data Handling ↦ Data Quality ↦ Quality Management

Please note: the Easy-GCS tool is currently under construction.