Thursday, October 29, 2009

Quality Data Management at Clinical Study Sites

At a clinical study site, who is responsible for quality controlled data, data review and data discrepancy management? Well, the immediate answer is everyone. The responsibility for accurate data lies with a team, each team member responsible for a specific task.
The team members are:
  • Data Manager
  • Quality Data Controller (most often this task is outsourced to consultants)
  • Medical Monitor
  • Data Management Clinical Research Organization (CRO).

The impact of data discrepancy is pervasive, time consuming, laborious and far reaching. Procedural tasks and steps involved in quality data control and review at clinical study sites include:

  • Data Receipt and Entry
  • Data Review
  • Data Quality Control
  • Data Changes
  • Medical Coding
  • Electronic External Vendor Data
  • CRF and DCF Tracking
  • Quality Management
  • SOPs, WIs for Discrepancy Management and Tracking.

It is important to see into the future with respect to accurate data and clinical study databases. At the end of Clinical Phase 2 or beginning Phase 3 Clinical Studies, companies begin to consult with regulatory and clinical submission consultants or companies to create and develop the GIDB - "global integrated database". As a requirement, two GIDBs are developed, one for safety, Phases 1,2,3 and one for efficacy, Phases 2,3. The two GIDBs are developed from the pooling of all required clinical study databases performed during the clinical development and clinical submission time of the drug prior to filing. One discrepant datapoint will impact the data accuracy of thousands of globally integrated SAS programmed statistical tables, listings, graphs and figures. Finding that one discrepant datapoint is like finding a needle in the haystack - not a pretty job, costly and very time consuming, often impacting writing and filing timelines.

How to avoid?

Agree and adhere to process and procedures to ensure quality, accurate data at the clinical study level. Don't wait to find data discrepancies in the GIDB. Use quality data management early in the clinical development and clinical submission plan(s). Avoid data integrity issues early at the clinical study level.

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