Clinical research cohort preparation
Researchers repeatedly rebuild eligibility datasets from sources with different terminology and dates.
The challenge behind the workflow.
Researchers repeatedly rebuild eligibility datasets from sources with different terminology and dates.
Connect operational and research data with clear purpose, provenance, and access. Help teams prepare reliable evidence for service planning, quality review, research, and administration while keeping clinical judgment with qualified professionals.
Data to bring together
- Approved research extracts
- Terminology mappings
- Study definitions
Source systems are examples of the data required. Confirm connector availability, permitted access, refresh timing, and the authoritative owner before implementation.
How Genedata supports the work.
Configure one connected workflow, then reuse its mappings, definitions, and review process as the business grows.
- 01
Connect and prepare
Apply approved mappings and preserve the version of the study cohort definition.
Build the preparation as a reusable visual workflow or reviewed code, with explicit source mappings and validation checks. - 02
Investigate and validate
Identify missing evidence and produce candidate cohorts for research-team validation.
Keep shared definitions and source versions with the analysis so another team can reproduce the result. - 03
Publish and review
Deliver a versioned cohort dataset with lineage and review status.
Make the output available to the right people with appropriate access, ownership, and review evidence.
A research cohort preparation dataset
Make the next run easier.
Reusable cohort logic reduces repetitive extraction for subsequent approved studies.
Start from one approved example. Save the agreed mappings and definitions, publish the reviewed output, and let the next team follow the same evidence instead of rebuilding the preparation.
Measure your own improvement
Time to reproduce an approved cohort
Record a baseline before the pilot and compare like-for-like work afterward. Results depend on source quality, configuration, and adoption.Review and responsibility
Research authorities approve access, consent conditions, and final participant eligibility.
AI with professional judgment.
Use AI to organize evidence and draft summaries for review. Clinical interpretation, patient care, and research eligibility decisions remain with qualified professionals.
Try the workflow with your team.
Use representative, approved sample data. Agree the expected output and a review owner before extending the workflow to a live process.