This repository contains the code, data, and instructions necessary to analyze the Healthcare Payments Data (HPD) Healthcare Measures dataset. The dataset includes three main categories: Health Conditions, Utilization, and Demographics. Below is a breakdown of the repository structure and the purpose of its contents:
code/
: Contains all R scripts used in the project.01_data_processing.R
: Generates clean data (specifies only Medi-Cal Payers)02_make_heatmap.R
: Code for creating the heatmap showing correlations between long-term illnesses and healthcare usuage rates.03_make_table.R
: Code for creating the table comparing different long-term illnesses in California based on the reporting year, the age range and the sex of the patient.
data/
: Contains raw and cleaned datasets used in the project.measures_descriptions_refresh.csv
: Descriptions of the different measures.measures_data_refresh_(edited)2024
.csv: Csv file only including long term illness in California
figure/
: Contains all generated figures for the report.Overall Long-Term Illnesses and Healthcare Usuage Rates.png
: Heatmap of correlations between long-term illnesses and healthcare usuage rates.Long-Term_Illnesses_Table.rds
: Table visualizing different long-term illnesses in California based on the reporting year, the age range and the sex of the patient.
Final_Project_McMillion.Rmd
: R Markdown file used to create the final report.Makefile
: Automates the generation of the final report.
The report provides:
- A heatmap visualizing correlations between long-term illnesses and healthcare usuage rates.
- A table comparing different long-term illnesses in California based on the reporting year, the age range and the sex of the patient.
The code for creating the required table is located in 03_make_table.R
. The correlation matrix is computed and displayed in the report.
The code for creating the required heatmap is located in 02_make_heatmap.R
. The script generates a heatmap showing correlations between long-term illnesses and healthcare usuage rates.
Follow these steps to generate the report:
- Clone the repository:
git clone https://github.com/DanielleMcMillion/DATA550-Final-Project.git cd DATA550-Final-Project