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Smart Data Quality (SDQ) Protocol Deviations

Review query-based and non-query-based protocol deviations collaboratively inside SDQ — with duplicate detection and downstream CTMS integration.

 
Generative AI in Clinical Trial Planning, Management, and Analysis
ContextIQ

Protocol deviation management, without the duplicates

 

Rule-based Protocol Deviation (PD) management lets clinical reviewers and other roles review protocol deviations efficiently through collaborative workflows and modern UI components. The workflow covers both non-query-based and query-based deviations in one place.

Previously raised PDs are surfaced during review to prevent duplicates, and every change is logged to the audit trail — keeping PD management collaborative, de-duplicated, and inspection-ready.

Why teams choose Protocol Deviation management

Patient Insights
Dual workflow support

Identify query-based PDs from site responses, and create non-query-based PDs directly from the To-Do list, IRL, Discrepancy Management, and Missing Pages.

Drill Down
Duplicate prevention

Existing PDs are surfaced based on study context — subject, visit, and more — to stop duplicate entries.

 
 
Data Hub
Role-based review

Clinical reviewers, medical monitors, and data managers get tailored access with an inline review-and-approval interface.

Monitor site performance in real-time
CTMS integration and audit readiness

PD details are available via API for downstream systems like CTMS, with structured export for traceability.

Zero duplicates

Existing PDs surfaced before you create a new one
Query-based and non-query-based PDs managed together and synced to CTMS

How Protocol Deviation management works

PD management runs as a four-step workflow, from definition to dashboard review.

1
Define
Define PD-related checks and listings as part of the data review plan — as DQ checks or interactive review listings.
2
Implement
Program the checks and listings via the Co-Pilot, based on inputs from medical monitors and data managers.
3
Identify and Flag
In the non-query workflow, clinical reviewers mark records as PD during review; in the query workflow, a Data Discrepant = Yes flag on a closed query drives the PD.
4
Review on Dashboard
Clinical reviewers approve or reject PDs from an interactive dashboard that visualizes deviations by category and aging.
Built to prevent duplicates. Before a new PD is created, SDQ surfaces previously raised PDs for the same study context, so the same deviation isn’t logged twice across the query and non-query workflows.

Features

Patient Insights
PD definition and customization

Define PD checks and listings and add custom fields like PD Classification, Category, and free-text description.

Data Hub
Dual workflow support

Query-based and non-query-based PDs handled in one module.

Dashboards
Duplicate prevention

Existing PDs detected and surfaced by study context.

AWS Partner
Configurable PD controls

Enable or disable PDs at account or study level and add study-specific fields shown during review and CTMS sync.

Smart Data Quality (SDQ)
Interactive PD dashboard

Visualize PDs by status, navigate by category, and view summary metrics and aging.

Smart Data Quality (SDQ)
Seamless system integration

API access for downstream systems and structured export for audit readiness.

Office Workers

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