Finalist
Optimising Comprehension of a Complex Pharmacokinetic Dataset in Haemophilia: A Through Cognitive Psychology and Information Design
Summary of work
Peer-reviewed publication is the gold standard for data integrity and the bedrock of medical communications and education. However, it can also be a missed opportunity: publications are sometimes treated only as source material, rather than being developed to ensure they are effective learning tools in themselves. In particular, data visualisations are often formulaic and challenging to comprehend. There is a clear need to apply principles from cognitive psychology and information design, such as reducing extraneous cognitive load, managing intrinsic cognitive load, and optimising germane cognitive load, to improve data comprehension in a publication context.
In this project, for the first time, we applied an existing data comprehension design methodology (DCODE™) to develop high-impact figures and tables and improve comprehension of a complex pharmacokinetic rare disease dataset, within a Good Publication Practice-compliant process. Whilst we knew this was a tough communication challenge, because of the many required approvals, we achieved our ultimate goal of securing an oral presentation for an international congress, and publication in a peer-reviewed journal with a supporting patient lay summary. Furthermore, as of March 2021, the open-access publication of this dataset is the most-viewed article in its issue.
Judges’ comments
A really good entry, achieving a powerful translation of science into practice. The strategy and methods leveraged robust scientific principles of psychology and data analysis. Also mindful of compliance and measurability. Achieved influential extended reach with the dataset via congress and journal communications. An all-round sterling effort.
