This project, conducted by Team Asthma, utilizes Synthea-generated datasets to mirror Medicaid and Medicare patients, focusing on asthma-related analysis. The findings and methodologies are detailed through R Markdown, which integrates R and SQL for a comprehensive data analysis experience.

The repository contains the following file:

• Final_Project_Team_Asthma_code.Rmd - An R Markdown document that includes all analyses, visualizations, and findings related to asthma. It incorporates SQL queries for data manipulation and analysis.

To run the R Markdown file with integrated SQL queries, you will need R, RStudio, and appropriate SQL database connection packages installed on your computer. Here’s how to set up your environment:

1. Install R:

   • Download and install R from The Comprehensive R Archive Network (CRAN).

2. Install RStudio:

   • Download and install RStudio from RStudio's official website.

3. Install Required R and SQL Packages:

   • Open RStudio and install the required packages by running the following commands in the R console:

     install.packages(c("tidyverse", "lubridate", "ggplot2", "dplyr", "knitr", "DBI", "RSQLite"))

   • Ensure you replace RSQLite with the package that matches your SQL database system, such as RMySQL, RODBC, or others.

To view and run the analysis:

1. Open RStudio.
2. Go to File > Open File and select the Final_Project_Team_Asthma_code.Rmd file.
3. Run the R Markdown file by clicking on Knit or use the shortcut Ctrl + Shift + K to generate a document that includes both content and output, such as plots and SQL query results.

Contributions to this project are welcome. Here are some ways you can contribute:

• Enhancing the analysis through more complex SQL queries or R scripts.
• Improving visualizations and data interpretations.
• Updating and maintaining the SQL database connections.

• Aizhan Uteubayeva

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

• Thanks to all the data providers and supporters of asthma research.
• Special thanks to our academic and industry mentors who guided this project.
• Acknowledgment to the Synthea team for providing a realistic synthetic data generator used to mirror Medicaid and Medicare patient data.