Development↦Data Handling↦Study Database Set-Up↦Variable Specification
What is it? Why is it important?
In order to reduce potential input errors in the study database (eCRF), variables can be specified with additional technical constraints or edit checks.
Input constraints include:
- Range: Limit potential input based on an upper and lower limiting value
- Format: Only allows input based on a pre-defined or standardised coding list, date format, lab value format (e.g. haemoglobin as g/l or g/dl)
- Length: Limits input to a maximum of characters or number digits
Navigation options can reduce input errors:
- Selection: Multiple choice, drop-down menus, radio buttons facilitate and guide staff during data entry
- Support: Pop-ups with information provided based on the selected input field
- Mandatory fields: A warning or error message is displayed in the event that:
- Incorrect data is entered
- Data is missing and must be entered prior to exiting the database. In the event data will remain missing, a code should be defined for this purpose
What do I need to do?
As a SP-INV, go through the list of selected study variables and for each variable define applicable technical requirements:
- Group variables in the Case Report Form (CRF) according to topic (e.g. lab data)
- Define who enters variables (e.g. study nurse, participant) and when it must be entered (e.g. baseline visit, study vist 2 and 4)
- Select appropriate metadata standards for coding your data (e.g. CDISC, CTCAE)
- For qualitative data, select appropriate categories (e.g. gender, male=1; female=2)
- Define selective conditions (e.g. show or hide variables under certain conditions)
For the database set-up:
- Define and document all technical requirements including its rational in collaboration with the data manager
- Upon database set-up include a test-phase(s) to ensure planned specifications and its navigation are implemented as intended
- Upon the successful completion of the test-phase, sign-off the study database to be released into the productive phase (e.g. input of real-life data)
A user-friendly and fit for purpose database (eCRF) will ensure that collected study data will be of high quality.
Where can I get help?
Your local CTU↧ can support you with experienced staff regarding this topic
Basel, Departement Klinische Forschung, CTU, dkf.unibas.ch
Lugano, 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.usz.ch
CDISC – Provides standards in the clinical research process
CTCAE – Common Terminology Criteria for Adverse Events
ICH GCP E6(R2) – see in particular guideline
- 5.5 Trial Management, data handling, and record-keeping