What is it? Why is it important?
Risk identification is based on:
- System level: informatics, SOPs, infrastructure, laboratory, available work space, resources such as time and personnel, etc.
- Study level: study design, target population, data collection, IC process, type of intervention such as randomisation and blinding, etc.
Implementing a risk-based QMS means to:
- Identify potential study risks
- Evaluate risks based on their likelihood of occurrence, ability to be detected and expected risk impact
- Prioritise risks, and define risk control measures proportionate to risk significance
- Communicate and train staff on risk prevention
- Review risk control measures in order to test its ongoing efficiency
- Document implemented risk control measures, potential deviations and improvement procedures
The SP-INV is responsible for the risk management of the study.
When writing the study protocol, an estimation of potential study risks and their risk control measures are defined. During study conduct and active handling of the study, risk adaptations might become necessary.
Consequently, risk identification and handling (evaluation & prioritisation, definition of control measures) is a continuous process, starting at the time of protocol writing and only ends upon study completion.
Newly identified risks during study set-up, development and conduct might potentially necessitate a protocol amendment.
What do I need to do?
- Identify the risks in your study, ask yourself:
- What can go wrong in my study?
- What could affect patient rights, safety, well-being?
- What could jeopardise data integrity, data quality?
- Document all identified risks and their management in the RAT
Examples of study risks or what can go wrong:
- Safety: non-compliant processes in the assessment and documentation of adverse events SAE, SUSAR
- Data protection: participant data becomes accessible to non-study staff
- Participant right: are not properly informed regarding study withdrawal or signing of IC
- Data quality: data incomplete, unusable for final analysis
- Analysis: statistics not applicable for data evaluation
- Design: feasibility is questionable resulting in poor compliance and incomplete dataset
- Biological material: lack of standardised processes for sample retrieval, handling and storage
- IMP/MD: lack of applicable storage conditions and access control
Use ‘lessons learned’ from previous studies. Previous risk experience can facilitate the risk identification of a planned study.
Where can I get help?
Your local CTU↧ can support you with experienced staff regarding this topic
Basel, Clinical Trials Unit, CTU, dkf.unibas.ch
Bellinzona, 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.ctc.usz.ch
ICH GCP E6(R2) – see in particular guidelines
- 5.0 Quality management
- 5.0.2 Risk identification
ISO 31000 – see in particular section
- Risk management: Principles and guidelines (access liable to costs)