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Archive: Using Data to Identify Risk Indicators in Risk-Based Monitoring
Course Description
This web seminar will provide centralized monitoring techniques for prioritizing sites and patients in need of on-site monitoring and education. These techniques are useful when using either a risk-based monitoring approach or 100% Source Data Verification, and include both a priori “risk indicators” and dynamic error detection during study execution. Emphasis will be placed on how monitors, data managers, and statisticians can work together to prioritize the data at highest risk of causing problems and prevent errors in the database. Novel techniques for identifying fraudulent data will also be addressed. When monitors, data managers, and statisticians apply these techniques, they will be able to implement a successful risk-based monitoring plan that is practical and cost-effective, while improving the overall quality of the data.
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Learning Objectives
- Prioritize investigators, patients, and individual records for on-site monitoring emphasis and education
- Differentiate between site-level and patient-level risk indicators and how to define each type
- Develop simple methods to find the most common type of errors in data
- Use data to dynamically adapt risk indicators during the study to find clinical study performance deficiencies
- Use data to identify fraudulent data
- Identify the information the statistician needs to know about the study to find errors more efficiently
- Identify the information the monitor needs to know about the data to prioritize the sites and patients for on-site monitoring
Who Should Attend
- Monitors who will assist in centralized monitoring
- Statisticians who will assist in centralized monitoring
- Data Managers
Instructor
Barbara Elashoff, M.S.
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Hold this course at your company! For more information, contact Naila Ganatra at +1 215.413.2471.