What is it? Why is it important?
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
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.
What do I need to do?
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
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 guideline
- 5.5 Trial management, data handling, and record-keeping