Biomarker data visualisation for decision making in clinical trials

Alan Davies, Marisa Cunha, Kamilla Kopec-Harding, Paul Metcalfe, James Weatherall, Caroline Jay

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: To understand how visualization of biomarker data is used for decision making in clinical trials, and
identify problems with and suggest improvements to this process.
Methods: We carried out semi-structured interviews with 18 professionals involved in various aspects of developing
or using visualizations of biomarker data for decision making in clinical trials. We used an inductive
thematic analysis to identify implicit and explicit ideas within the data captured from the interviews.
Results: We identified 6 primary themes, including: how visualizations were used in clinical trials; the importance
of having a clear understanding of the underlying data; the purpose or use of the visualization, and the
properties of the visualizations themselves. The results show that participants’ ‘trust’ in the visualization depends
on access to the underlying data, and that there is currently no standard or straightforward way to support this
access.
Conclusions: Incorporating information about data provenance into biomarker-related visualizations used for
decision making in clinical trials may increase users’ trust, and therefore facilitate the decision making process.
Original languageEnglish
Pages (from-to)1-9
JournalInternational journal of medical informatics
Early online date25 Oct 2019
DOIs
Publication statusPublished - 2019

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