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Smart Data Quality (SDQ) Interactive Review Listings

Review pre-built or generative-AI–built data listings, drill into the records, raise queries, and assign tasks to teams and vendors — all inside SDQ.

SMART DATA QUALITY (SDQ) — INTERACTIVE REVIEW LISTINGS
SMART DATA QUALITY (SDQ) — INTERACTIVE REVIEW LISTINGS

Advanced data review, without the spreadsheets

Interactive Review Listings (IRL) gives study teams one place to perform advanced data review. Review Saama’s pre-built listings or create custom listings with generative AI, drill from aggregated views down to individual records, raise queries, and assign review tasks to team members and vendors — without exporting data to spreadsheets.

With enhanced aggregation, IRL supports grouping, aggregation, and pivoting as part of the listing workflow, so reviewers can spot trends and outliers across an entire study and still trace any signal back to the source record.

Why teams choose Interactive Review Listings

Smart Medical Coding 
One place for all listings

Manual review and advanced review happen together, removing tool-switching and reconciliation.

Smart Medical Coding 
Collaborate across teams and vendors

Describe the listing you need in plain language and a Co-Pilot drafts the underlying query.

 
Smart Medical Coding 
Collaborate across teams and vendors

Assign review tasks, add threaded comments, and track ownership in-app.

 
Smart Medical Coding 
Aggregate to see the signal

Row-level grouping, aggregation, and pivoting reveal patterns individual records hide.

One workspace

Listings, aggregation, queries, and tasks in one place
Pre-built and GenAI-built listings with drill-down and team assignment — no spreadsheet exports

How Interactive Review Listings works

Listings move through a controlled, permission-aware workflow from creation to review.

1
Start from a listing — or describe one

Open a pre-built listing or create a custom one by describing it to the Co-Pilot, which drafts the query logic for you.

2
Shape and validate

Build grouping and aggregation in the dry-run screen, then save and send the listing for testing before it reaches production.

3
Review, query, and assign

Reviewers drill from aggregated views to individual records, raise queries, and assign tasks to team members and vendors.

Aggregation with guardrails. Only users permitted to create listings can build aggregations, reducing the risk of introducing unblinding bias while still giving reviewers the trend views they need.
 

Features

Source to Submission (S2S)
Pre-built and custom listings

Use Saama’s library or build study-specific listings on demand.

Data Hub
GenAI-assisted authoring

Plain-language requests are converted into listing logic.

Dashboards
Grouping, aggregation, and pivot

Create aggregated views and drill back down to source records.

AWS Partner
Permission-controlled aggregation

Aggregation is limited to authorized listing creators.

Smart Data Quality (SDQ)
Task assignment

Distribute review work to teams and vendors with tracking.

Smart Data Quality (SDQ)
Threaded comments

Collaborate on findings directly on the listing.

Office Workers

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