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Chicago Health Insurance Coverage Analysis

Project Description

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/

Features

  • 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

Requirements

  • R version 4.0.0 or higher
  • RStudio (recommended for running Shiny apps)

Required R Packages

install.packages(c(
  "shiny",
  "shinydashboard",
  "tidyverse",
  "sf",
  "leaflet",
  "viridis",
  "htmltools",
  "janitor",
  "plotly",
  "DT",
  "scales"
))

Data Sources

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)

Setup Instructions

  1. Clone this repository
  2. Install required R packages (listed above)
  3. Open app.R in RStudio
  4. Click 'Run App' or use runApp() in the R console

Project Structure

Usage

The dashboard is organized into several tabs:

  1. Overview: Introduction and key findings
  2. Interactive Map: Explore spatial patterns
  3. Socioeconomic Factors: Examine correlations
  4. Disparities Analysis: Investigate inequalities
  5. Medicaid Coverage: Analyze safety net impact

Author

Kohan Chen

License

This project is licensed under the MIT License - see the LICENSE file for details

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