Developing an R Shiny Interactive Dashboard to Increase Interpretability of Data
Channel: R Consortium
Date: 20/07/2023

Christian Lee, Medical Student at Anne Burnett School of Medicine at Texas Christian University

The landscape of medical residency applications is ever-changing. While there exist several large tables of data across various websites, they are often disjointed, unnecessarily complex, and do not adequately capture longitudinal trends. To address this, Med Stats, an interactive tool built with R Shiny, was developed to improve accessibility and interpretability of residency match data to enable informed discussions and decision-making. Users can select their metrics of interest and explore the data in the context of other specialties and over time. This includes applicant-level information such as exam scores and number of publications, and specialty-level information such as the number of positions offered and the number of applicants. In addition, the tool serves as a central hub for residency-related data because it is built on aggregated datasets from multiple sources. Overall, Med Stats provides an example of how R Shiny can enhance the usage, sharing, and interpretability of data, surpassing the limitations of static tables and periodic publications.

PDF: https://static.sched.com/hosted_files/rmed2023a/15/R%20Medicine%202023.pdf 

Main Sections 

0:00 Introduction
0:56 Annual reports on residency data are useful but cumbersome
1:45 Limitations 
3:07 How R and Shiny can help
3:54 Med Stats - App demo
8:00 Wrap up and Q&A 

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