Your Easy Guide to Clinical Studies

Is the implementation of technology to automatically process data in order to convert it into more useful information or formats (e.g. age upon study start, BMI based on height and weight).

Data processing can be done before or once the data has been entered in the database. Still, automated processing might have an important advantage, as it excludes human calculation errors.

Automated processing requires:

• An electronic database
• Ability to program processing procedures (e.g. calculations, classification)
• Ability to perform applicable validations

Example

Calculation of creatinine clearance requires the input of raw data into an applicable formula (age, weight, serum creatinine, and gender). Upon automated data processing the creatinine clearance number is no longer raw data but automated processed data.

Based on data needed to answer your study question:

• Define which data (variables) must be obtained through automated processing
• Define which variables are needed for the automated processing
• Ask your data manager to program any required automated processing procedure(s)
• Include upper and lower limits to the outcome variable(s) in order to detect potential input errors
• As processed data must be carefully tested and validated, include a test phase to ensure automated data processing is correctly implemented
• Describe any automated processing in the DMP

References

ICH GCP E6(R2) – see in particular guideline

• 5.5 Trial management, data handling, and record-keeping