Data Quality Overview
Query Lifecycle
Understand the query workflow from creation to resolution.
Creating Queries
How to raise data queries.
Responding to Queries
How site teams respond to queries.
Data Quality Workflow
The data quality process ensures accuracy:Query Types
Manual Queries
Raised by the study team:- Data clarification requests
- Correction requests
- Missing data inquiries
- Protocol deviation documentation
Field Change Queries
Auto-generated when field values change:| Type | Trigger |
|---|---|
| Confirmed Field Update | Change with confirmation |
| Override Field Update | Change overriding previous value |
Record Status with Queries
Queries affect record status:| Status | Description |
|---|---|
| Completed (Site) | No open queries |
| Queries in Progress | Has open queries |
| Verified (Study Team) | Queries resolved, data verified |
Roles in Data Quality
| Role | Capabilities |
|---|---|
| Data Reviewer (Study Team) | Review data, raise queries, verify records |
| Site Team (CRC, PI, etc.) | Respond to queries, update data |
| Reviewer | View queries (read-only) |
Query Metrics
Track data quality through metrics:| Metric | Description |
|---|---|
| Open Queries | Queries awaiting response |
| Query Rate | Queries per submitted record |
| Resolution Time | Average time to resolve queries |
| Query by Type | Distribution of query reasons |
Data Verification
After queries are resolved:Verification indicates the study team has reviewed and accepted the data. It does not imply clinical judgment.
Best Practices
Clear Query Text
Clear Query Text
Write queries that clearly explain what information is needed.
Timely Review
Timely Review
Review submitted data promptly to identify issues early.
Consistent Standards
Consistent Standards
Apply consistent review criteria across all sites.
Track Patterns
Track Patterns
Monitor query patterns to identify training needs.