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A cross-source, system-agnostic solution for clinical data review

Authors :
Fang Du
Michael A Farnum
Lalit Mohanty
Dimitris K. Agrafiotis
Mathangi Ashok
Victor S. Lobanov
Paul Konstant
Daniel Kowalski
Joseph Ciervo
Source :
Database: The Journal of Biological Databases and Curation
Publication Year :
2019
Publisher :
Oxford University Press (OUP), 2019.

Abstract

Assembly of complete and error-free clinical trial data sets for statistical analysis and regulatory submission requires extensive effort and communication among investigational sites, central laboratories, pharmaceutical sponsors, contract research organizations and other entities. Traditionally, this data is captured, cleaned and reconciled through multiple disjointed systems and processes, which is resource intensive and error prone. Here, we introduce a new system for clinical data review that helps data managers identify missing, erroneous and inconsistent data and manage queries in a unified, system-agnostic and efficient way. Our solution enables timely and integrated access to all study data regardless of source, facilitates the review of validation and discrepancy checks and the management of the resulting queries, tracks the status of page review, verification and locking activities, monitors subject data cleanliness and readiness for database lock and provides extensive configuration options to meet any study’s needs, automation for regular updates and fit-for-purpose user interfaces for global oversight and problem detection.

Details

ISSN :
17580463
Volume :
2019
Database :
OpenAIRE
Journal :
Database
Accession number :
edsair.doi.dedup.....f0f19a81ec29289e9cc30dcabc4fecc7