Are you being compliant with the regulatory expectations regarding the monitoring of your trials and specifically fraud/misconduct?
Fraudulent data checks are now required by the FDA as part of routine data checks. However, there can be many different methods used on many different types of data to identify fraud.
Shafi Consultancy have spent many years working with, and reviewing such methods and have developed statistical techniques used to identify fraudulent data on different types of data. We know which techniques can be successfully used on the different types of data. In our process the results can also be presented to our clients in many different formats, from charts and plots to analysis tables.
As fraudulent data check is something that must be done for each trial, our experienced team is ready to assist you in performing the checks, standardise the process across trials and to minimise the effort and costs involved in achieving this.
See our papers on Fraudulent Data:
Fraudulent Data Checks and How to Develop them
Fraudulent data detection in clinical trial using dynamic clustering
Why Look at
Because people’s lives and health will be at risk
To protect the rights and well-being of patients enrolled in a trial by verifying the authenticity of clinical trial data
To identify and address problems early to limit the serious implications by analyzing data quality
Maintain the research integrity in the public eye
Eligibility criteria e.g. age, medical history of the patients
Patient diary data
Repeated measurements e.g. blood pressure and laboratory data
Adverse events reporting
Assessment of medical compliance
Dates of assessment
Data collected on Weekends and National Holidays or outside of normal hours
Detection of Fraud at Clinical Sites
Check for Inliers and Outliers
Check for Incorrect dates: Mosaic Plots
Check for Under-reporting of Adverse Events: Scatter Plots, 2D and 3D.
Rounding of integers: Line and Scatter Plots
Last Digit Preference: Volcano Plots
Check for duplicate patients by comparing key data, including age, height, weight, vital signs and visit schedules. Box plots
can be used for these checks
We use a pool of template programs to identify fraud
Benefits of using us for fraud detection
Standardised analysis ensuring quality and consistency
Can be reproduced quickly and easily on an ongoing basis
Additional study-specific checks are always carried out
Manual data interrogation always performed on every run
Dedicated team specialized in fraudulent data checks