StoryboardR: an R package and Shiny application designed to visualize real-world data from clinical patient registries

• Published in: JAMIA open Vol. 6; no. 1; p. ooac109
• Main Authors: Miller, David M, Shalhout, Sophia Z
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 01.04.2023
• Subjects: Application Notes; Visualization (Computers); REDCap; clinical informatics; data visualization; patient registries; Shiny app
• ISSN: 2574-2531; 2574-2531
• DOI: 10.1093/jamiaopen/ooac109

Abstract Objectives Tumor registries are a rich source of real-world data which can be used to test important hypotheses that inform clinical care. Exploratory data analysis at the level of individual subjects, when enhanced by interactive data visualizations, has the potential to provide novel insights and generate new hypothesis. Materials and Methods We created StoryboardR: an R package and Shiny application designed to visualize real-word data from tumor registries. Results StoryboardR facilitates the data visualization of real-word data from tumor registries captured in REDCap®. The output is an interactive timeline that allows for a visual interpretation of the relationship between potential prognostic and/or predictive biomarkers and outcomes. Conclusions StoryboardR is freely available under the Massachusetts Institute of Technology license and can be obtained from GitHub. StoryboardR is executed in R and deployed as a Shiny application for non-R users. It produces data visualizations of patient journeys from tumor registries. Lay Summary Tumor registries are a rich source of patient-level data that can lead to important clinical insights. When optimally executed, tumor registries capture highly structured real-world data which facilitates time-to-analysis and time-to-insight. While tumor registries can provide large data sets to test important hypotheses, exploratory data analysis (EDA) at the level of individual subjects can lead to novel insights and hypothesis generation. Visualizing patient-level data is a critical part of EDA. Good data visualizations can facilitate the digestion of complex information. Ideal data visualizations are simple to generate, make data easy to understand, and are visually appealing. Here, we present StoryboardR, an R package with a Shiny application front-end, which facilitates the visualization of real-world data from clinical registries captured in a REDCap®-based project. The functions of StoryboardR wrangle and transform data from REDCap®-based tumor registries to produce an interactive data visualization of the patient journey. StoryboardR is executed in R; however, the application is deployed via Shiny to enhance the user interface for non-R users.