How to export clinical trial data for analysis
Your statistician needs clean, labelled datasets on a schedule. Plan formats, names and transfers at the build, and exports stop being a project.
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- Agree the export format and variable names with the statistician before the build.
- Export code lists and labels with the data, and keep the codes stable.
- Schedule transfers and log each one with its date and content.
- Map to CDISC SDTM when the study goes to the FDA or the PMDA.
Exporting clinical data means handing your statistician, safety team or partners a dataset they can analyse without guessing what each column holds. You get there by fixing names, formats and code lists at the build, then exporting on a schedule with a record of every transfer.
How to plan exports in 6 steps
- Agree the format. SAS datasets, CSV or Excel, one file per form or one per domain. Ask your statistician what their programs read.
- Name the variables at the build. Short, stable names such as AESTDTC or VSORRES save a mapping step later. Keep them unchanged after go-live.
- Export the metadata. Send labels, code lists and units with the data, so "1" in the sex column means the same thing in every transfer.
- Schedule the transfers. Set how often data leaves the EDC, to whom and through which channel, and write it in a data transfer agreement.
- Log each transfer. Keep the date, the cut-off, the files and the recipient. Inspectors will ask which data supported which analysis.
- Map to CDISC when needed. Studies submitted to the FDA or the PMDA need SDTM datasets. Collecting with CDASH-style names makes the mapping shorter.
Mistakes to avoid
- Codes that change between exports. A code list edited mid-study breaks every program downstream.
- Free text where a code would do. Your statistician cannot count free text.
- Exports sent by email. Use a secure channel and log it.
Exports in Datacapt
Datacapt exports the whole eCRF database at any time in CSV, Excel, PDF or SAS. The Excel export carries the item dictionary, option values, queries and missing-data codes on their own sheets, and Datacapt builds the eCRF on the CDISC ODM format. For automated transfers, the REST API pulls and pushes data in real time, with webhooks for event-driven actions and a test environment to check your integration first. Your data manager finds every variable name, type and code list in the item dictionary.
Keep reading
What is the difference between CDASH and SDTM?
CDASH standardises how you collect data on the CRF. SDTM standardises how you submit it to regulators. CDASH fields map to SDTM with little work.
Which format do statisticians prefer?
SAS datasets remain common in pharma, and R users read CSV or SAS files. Ask before the build.
Should exports include the audit trail?
Keep the audit trail available for inspection. Analysis datasets carry the current values, and you export the audit trail when an auditor or a partner asks for it.