A cross-source, system-agnostic solution for clinical data review. (18th February 2019)

• Record Type: Journal Article
• Authors: Farnum, Michael A; Ashok, Mathangi; Kowalski, Daniel; Du, Fang; Mohanty, Lalit; Konstant, Paul; Ciervo, Joseph; Lobanov, Victor S; Agrafiotis, Dimitris K
• Is Part Of: Database. Volume 2019(2019)
• Publication Date: 2019-02-18
• Subjects: Biology -- Databases -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1093/database/baz017
• Languages: English
• ISSNs: 1758-0463

Abstract

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.