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Challenges to complete and useful data sharing

Overview of attention for article published in Trials, February 2017
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Title
Challenges to complete and useful data sharing
Published in
Trials, February 2017
DOI 10.1186/s13063-017-1816-8
Pubmed ID
Authors

Lawrence Mbuagbaw, Gary Foster, Ji Cheng, Lehana Thabane

Abstract

Data sharing from clinical trials is one way of promoting fair and transparent conduct of clinical trials. It would maximise the use of data and permit the exploration of additional hypotheses. On the other hand, the quality of secondary analyses cannot always be ascertained, and it may be unfair to investigators who have expended resources to collect data to bear the additional burden of sharing. As the discussion on the best modalities of sharing data evolves, some of the practical issues that may arise need to be addressed. In this paper, we discuss issues which impede the use of data even when sharing should be possible: (1) multicentre studies requiring consent from all the investigators in each centre; (2) remote access platforms with software limitations and Internet requirements; (3) on-site data analysis when data cannot be moved; (4) governing bodies for data generated in one jurisdiction and analysed in another; (5) using programmatic data collected as part of routine care; (6) data collected in multiple languages; (7) poor data quality. We believe these issues apply to all primary data and cause undue difficulties in conducting analysis even when there is some willingness to share. They can be avoided by anticipating the possibility of sharing any clinical data and pre-emptively removing or addressing restrictions that limit complete sharing. These issues should be part of the data sharing discussion.

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Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 16%
Student > Master 4 13%
Student > Bachelor 3 10%
Student > Doctoral Student 2 6%
Student > Postgraduate 2 6%
Other 7 23%
Unknown 8 26%
Readers by discipline Count As %
Nursing and Health Professions 5 16%
Computer Science 5 16%
Social Sciences 3 10%
Medicine and Dentistry 3 10%
Biochemistry, Genetics and Molecular Biology 2 6%
Other 4 13%
Unknown 9 29%