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Classification of processes involved in sharing individual participant data from clinical trials
Background: In recent years, a cultural change in the handling of research data has resulted in the promotion of a culture of openness and an increased sharing of data. In the area of clinical trials, sharing of individual participant data involves a complex set of processes and the interaction of m...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861517/ https://www.ncbi.nlm.nih.gov/pubmed/29623192 http://dx.doi.org/10.12688/f1000research.13789.2 |
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author | Ohmann, Christian Canham, Steve Banzi, Rita Kuchinke, Wolfgang Battaglia, Serena |
author_facet | Ohmann, Christian Canham, Steve Banzi, Rita Kuchinke, Wolfgang Battaglia, Serena |
author_sort | Ohmann, Christian |
collection | PubMed |
description | Background: In recent years, a cultural change in the handling of research data has resulted in the promotion of a culture of openness and an increased sharing of data. In the area of clinical trials, sharing of individual participant data involves a complex set of processes and the interaction of many actors and actions. Individual services and tools to support data sharing are becoming available, but what is missing is a detailed, structured and comprehensive list of processes and subprocesses involved and the tools and services needed. Methods: Principles and recommendations from a published consensus document on data sharing were analysed in detail by a small expert group. Processes and subprocesses involved in data sharing were identified and linked to actors and possible supporting services and tools. Definitions adapted from the business process model and notation (BPMN) were applied in the analysis. Results: A detailed and comprehensive tabulation of individual processes and subprocesses involved in data sharing, structured according to 9 main processes, is provided. Possible tools and services to support these processes are identified and grouped according to the major type of support. Conclusions: The identification of the individual processes and subprocesses and supporting tools and services, is a first step towards development of a generic framework or architecture for the sharing of data from clinical trials. Such a framework is needed to provide an overview of how the various actors, research processes and services could interact to form a sustainable system for data sharing. |
format | Online Article Text |
id | pubmed-5861517 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-58615172018-04-04 Classification of processes involved in sharing individual participant data from clinical trials Ohmann, Christian Canham, Steve Banzi, Rita Kuchinke, Wolfgang Battaglia, Serena F1000Res Research Article Background: In recent years, a cultural change in the handling of research data has resulted in the promotion of a culture of openness and an increased sharing of data. In the area of clinical trials, sharing of individual participant data involves a complex set of processes and the interaction of many actors and actions. Individual services and tools to support data sharing are becoming available, but what is missing is a detailed, structured and comprehensive list of processes and subprocesses involved and the tools and services needed. Methods: Principles and recommendations from a published consensus document on data sharing were analysed in detail by a small expert group. Processes and subprocesses involved in data sharing were identified and linked to actors and possible supporting services and tools. Definitions adapted from the business process model and notation (BPMN) were applied in the analysis. Results: A detailed and comprehensive tabulation of individual processes and subprocesses involved in data sharing, structured according to 9 main processes, is provided. Possible tools and services to support these processes are identified and grouped according to the major type of support. Conclusions: The identification of the individual processes and subprocesses and supporting tools and services, is a first step towards development of a generic framework or architecture for the sharing of data from clinical trials. Such a framework is needed to provide an overview of how the various actors, research processes and services could interact to form a sustainable system for data sharing. F1000 Research Limited 2018-04-20 /pmc/articles/PMC5861517/ /pubmed/29623192 http://dx.doi.org/10.12688/f1000research.13789.2 Text en Copyright: © 2018 Ohmann C et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ohmann, Christian Canham, Steve Banzi, Rita Kuchinke, Wolfgang Battaglia, Serena Classification of processes involved in sharing individual participant data from clinical trials |
title | Classification of processes involved in sharing individual participant data from clinical trials |
title_full | Classification of processes involved in sharing individual participant data from clinical trials |
title_fullStr | Classification of processes involved in sharing individual participant data from clinical trials |
title_full_unstemmed | Classification of processes involved in sharing individual participant data from clinical trials |
title_short | Classification of processes involved in sharing individual participant data from clinical trials |
title_sort | classification of processes involved in sharing individual participant data from clinical trials |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861517/ https://www.ncbi.nlm.nih.gov/pubmed/29623192 http://dx.doi.org/10.12688/f1000research.13789.2 |
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