Benchmarking Current Practices in Data Visualisation in HEOR, Identifying Gaps and Suggesting Improvements
Author(s)
Hriday K1, Srivastava T2
1ConnectHEOR, London, UK, 2ConnectHEOR, London, LON, UK
Presentation Documents
OBJECTIVES:
Data visualisation is a graphical depiction of data analysis using common graphics such as plots, charts, and infographics. In health economics and outcomes research (HEOR) studies, it is vital to interpret and communicate the study findings to multiple stakeholders. Data visualisation has the potential to express complicated data relationships and data-driven insights in an understandable manner. The study aims to understand the trend of usage of non-standard data visualisation in HEOR and suggest improvements within that.METHODS:
A targeted literature review was conducted using the PubMed database to identify original articles published in the last 10 years (between 1/1/2012 and 1/1/2022). Only studies with non-standard HEOR graphs were included.RESULTS:
Following screening of 173 records, 60 relevant articles were included. Of these, we observed occurrence of several unique non-standard HEOR charts, including relative density plot, horizontal tornado, stepwise tornado, spider plots, rankogram, enhanced KM plot, price acceptability curves, panel plots, contour plot, funnel plots, error bands, and sankey plot. Furthermore, MS-Excel was utilised 60% of the time to develop these graphs, followed by Prism (15%) and R (13%).CONCLUSIONS:
Recently, there has been substantial advancement in HEOR visualisation, however, the scope has been confined to improvements over traditional graphs. Storytelling through data visualisation is a profound research area in itself where any data table/matrix can be systematically classified into comparison, correlation, distribution, concept, geospatial or trend and each of these categories support plenty of charts for visualisation. New visualisations like bean charts, horizontal tornados, cycle plots, jitter plots along with traditional charts like Lorenz curve, box plots, bullet charts can have potential applications in HEOR studies. The advanced visualisation tools like Power BI, Tableau, R and python libraries like ggplot2, Plotly, Lattice, Matplotlib, Pandas open up options for creating whole new visualisations in HEOR that could be explored further.Conference/Value in Health Info
2022-11, ISPOR Europe 2022, Vienna, Austria
Value in Health, Volume 25, Issue 12S (December 2022)
Code
MSR29
Topic
Economic Evaluation, Methodological & Statistical Research, Study Approaches
Topic Subcategory
Cost-comparison, Effectiveness, Utility, Benefit Analysis, Literature Review & Synthesis
Disease
No Additional Disease & Conditions/Specialized Treatment Areas