Biomarker data visualisation for decision making in clinical trials. (December 2019)

• Record Type: Journal Article
• Authors: Davies, Alan; Cunha, Marisa; Kopec-Harding, Kamilla; Metcalfe, Paul; Weatherall, James; Jay, Caroline
• Is Part Of: International journal of medical informatics. Volume 132(2019)
• Publication Date: 2019-12
• Subjects: Visualizations -- Biomarkers -- Clinical trials -- Interviews -- Thematic analysis -- Trust -- Provenance; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2019.104008
• Languages: English
• ISSNs: 1386-5056

Abstract

Highlights: Examination of issues surrounding visualisations generation and use by those visualising biomarker data for clinical trials. Exploration of the main themes and issues surrounding the application of visualisations for decision making. We look at the current processes and uses of such visualisations at various points in clinical trials. 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.