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A cross-source, system-agnostic solution for clinical data review
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, t...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6378235/ https://www.ncbi.nlm.nih.gov/pubmed/30773591 http://dx.doi.org/10.1093/database/baz017 |
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author | Farnum, Michael A Ashok, Mathangi Kowalski, Daniel Du, Fang Mohanty, Lalit Konstant, Paul Ciervo, Joseph Lobanov, Victor S Agrafiotis, Dimitris K |
author_facet | Farnum, Michael A Ashok, Mathangi Kowalski, Daniel Du, Fang Mohanty, Lalit Konstant, Paul Ciervo, Joseph Lobanov, Victor S Agrafiotis, Dimitris K |
author_sort | Farnum, Michael A |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6378235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63782352019-02-21 A cross-source, system-agnostic solution for clinical data review Farnum, Michael A Ashok, Mathangi Kowalski, Daniel Du, Fang Mohanty, Lalit Konstant, Paul Ciervo, Joseph Lobanov, Victor S Agrafiotis, Dimitris K Database (Oxford) Original Article 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. Oxford University Press 2019-02-18 /pmc/articles/PMC6378235/ /pubmed/30773591 http://dx.doi.org/10.1093/database/baz017 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Farnum, Michael A Ashok, Mathangi Kowalski, Daniel Du, Fang Mohanty, Lalit Konstant, Paul Ciervo, Joseph Lobanov, Victor S Agrafiotis, Dimitris K A cross-source, system-agnostic solution for clinical data review |
title | A cross-source, system-agnostic solution for clinical data review |
title_full | A cross-source, system-agnostic solution for clinical data review |
title_fullStr | A cross-source, system-agnostic solution for clinical data review |
title_full_unstemmed | A cross-source, system-agnostic solution for clinical data review |
title_short | A cross-source, system-agnostic solution for clinical data review |
title_sort | cross-source, system-agnostic solution for clinical data review |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6378235/ https://www.ncbi.nlm.nih.gov/pubmed/30773591 http://dx.doi.org/10.1093/database/baz017 |
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