This interactive dashboard explores health insurance coverage patterns across Chicago's census tracts, examining relationships between uninsured rates and socioeconomic factors. The analysis combines spatial mapping with statistical visualization to reveal patterns of healthcare access inequality across Chicago from 2019-2023.
Here is the link to the dashboard: https://kohanchen.shinyapps.io/final-project-Kohaningithub/
- Interactive choropleth map showing uninsured rates, hardship index, and median income
- Socioeconomic factor analysis with scatter plots and trend lines
- Income and hardship level disparity analysis using box plots
- Medicaid coverage analysis examining the relationship with hardship index
- Comprehensive interpretations and key findings for each visualization
- R version 4.0.0 or higher
- RStudio (recommended for running Shiny apps)
install.packages(c(
"shiny",
"shinydashboard",
"tidyverse",
"sf",
"leaflet",
"viridis",
"htmltools",
"janitor",
"plotly",
"DT",
"scales"
))
The analysis uses Chicago health insurance and demographic data from 2019-2023:
- Chicago Health Insurance Coverage Data (included in data)
- Chicago Census Tract Boundaries (TIGER/Line Shapefiles) (included in data)
- Clone this repository
- Install required R packages (listed above)
- Open app.R in RStudio
- Click 'Run App' or use
runApp()
in the R console
- app.R: Main Shiny application code, can be used to reproduce the dashboard, run by clicking 'Run App' or using
runApp()
in the R console - data: Contains all required datasets
- analysis: Contains analysis paper Health Insurance Coverage Disparities in Chicago: A Visual Analysis.pdf
The dashboard is organized into several tabs:
- Overview: Introduction and key findings
- Interactive Map: Explore spatial patterns
- Socioeconomic Factors: Examine correlations
- Disparities Analysis: Investigate inequalities
- Medicaid Coverage: Analyze safety net impact
Kohan Chen
This project is licensed under the MIT License - see the LICENSE file for details