May 16, 2012: 11.00am EDT, 17.00 CET, 20.30 IST
Clinical trial data must be of sufficient quality to evaluate study objectives. Data validation is the quality control process that ensures data is of sufficient quality and minimizes the risk of invalid or missing data at the time of analysis. Properly managed, data validation eliminates costly re-evaluation of data late in the clinical trial process. This webinar will define high quality data and discuss the data validation processes that produce high quality data. Data validation for both paper and EDC systems will be considered. Data validation will be examined at multiple stages from the edit checks embedded in the EDC system to the preparation of datasets for analysis. Specific examples of the data validation will be provided for each stage of the clinical data management process.
What You’ll Learn
Attendees will be able to:
1. Define the concept of high quality data.
2. Describe the stages of data validation.
3. Describe specific examples of data validation.
4. Explain the differences with respect to data validation between paper and EDC systems.
5. Explain how to implement data validation for a clinical trial.
Participants will understand the concept of high quality data, the stages of data validation and some specific examples of data validation for each stage.
Who Should Attend
Beginners to intermediate, CRAs and biostatisticians.
Individual: $300 members/$350 non-members
Participants are eligible to receive CEUs upon attendance and succesful completion of a web-based assesment within 30 days after the webinar. CEUs are not granted after the 30-day assesment deadline.
SCDM is authorized by IACET to offer 0.2 CEUs for this program.
Registration for this webinar is now closed.