Classification of processes involved in sharing individual participant data from clinical trials [version 2; referees: 1 approved, 2 approved with reservations]
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...
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doaj-f83dc98c124548ffa019ae74178947982020-11-25T03:35:34ZengF1000 Research LtdF1000Research2046-14022018-04-01710.12688/f1000research.13789.215913Classification of processes involved in sharing individual participant data from clinical trials [version 2; referees: 1 approved, 2 approved with reservations]Christian Ohmann0Steve Canham1Rita Banzi2Wolfgang Kuchinke3Serena Battaglia4European Clinical Research Infrastructure Network (ECRIN), Düsseldorf, 40477, GermanyCanham Information Systems, Redhill, Surrey, RH1 6QH, UKMario Negri Institute of Pharmacological Research, Milan, 20156, ItalyCoordination Centre for Clinical Trials, Heinrich Heine University Dusseldorf, Dusseldorf, 40225, GermanyEuropean Clinical Research Infrastructure Network (ECRIN), Paris, 75013, FranceBackground: 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.https://f1000research.com/articles/7-138/v2 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Christian Ohmann Steve Canham Rita Banzi Wolfgang Kuchinke Serena Battaglia |
spellingShingle |
Christian Ohmann Steve Canham Rita Banzi Wolfgang Kuchinke Serena Battaglia Classification of processes involved in sharing individual participant data from clinical trials [version 2; referees: 1 approved, 2 approved with reservations] F1000Research |
author_facet |
Christian Ohmann Steve Canham Rita Banzi Wolfgang Kuchinke Serena Battaglia |
author_sort |
Christian Ohmann |
title |
Classification of processes involved in sharing individual participant data from clinical trials [version 2; referees: 1 approved, 2 approved with reservations] |
title_short |
Classification of processes involved in sharing individual participant data from clinical trials [version 2; referees: 1 approved, 2 approved with reservations] |
title_full |
Classification of processes involved in sharing individual participant data from clinical trials [version 2; referees: 1 approved, 2 approved with reservations] |
title_fullStr |
Classification of processes involved in sharing individual participant data from clinical trials [version 2; referees: 1 approved, 2 approved with reservations] |
title_full_unstemmed |
Classification of processes involved in sharing individual participant data from clinical trials [version 2; referees: 1 approved, 2 approved with reservations] |
title_sort |
classification of processes involved in sharing individual participant data from clinical trials [version 2; referees: 1 approved, 2 approved with reservations] |
publisher |
F1000 Research Ltd |
series |
F1000Research |
issn |
2046-1402 |
publishDate |
2018-04-01 |
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. |
url |
https://f1000research.com/articles/7-138/v2 |
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