CMS-MS-Finder

A simple project to download, process, and analyze CMS (Centers for Medicare & Medicaid Services) claims data for Multiple Sclerosis (MS) patients.

Overview

The included scripts perform the following steps:

1. Download CMS claims data (in zip files) from the CMS website(https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/SynPUFs/DESample01).
2. Extract the data (CSV files) from the zip files.
3. Load the CSV files into a SQLite database.
4. Performs data transformations using SQL on the loaded data.
5. Creates and persists new tables with the transformed data.

Prerequisites

To run this project, you will need Python 3.6+ installed on your system. Additionally, the following Python libraries are required:

• pandas
• requests
• sqlalchemy
• tqdm

Setup

To set up the project, follow these steps:

1. Clone this repository.git clone https://github.com/IrvicRodriguez/CMS-MS-Finder

2. Create a virtual environment. python -m venv venv You can name the virtual environment differently.

3. Activate the virtual environment. On MacOs or Linux use: source venv/bin/activate on Windows use: venv\Scripts\activate.

4. Install the required packages from the requirements.txt file using pip install -r requirements.txt.

Running the script

After setting up the project, you can run the main.py script to execute the pipeline using: python main.py.

This script will download the necessary data files, process them, and store the results in the SQLite database (cms_data.db). Be aware run time is based on local system. For example the scripts takes around 10 to 15 Minutes of runtime (Example times come from Intel 3.6GHz quad-core Mac with 64GB's of RAM).

File Structure

• main.py: The main script that executes the data processing pipeline.
• config.py: Contains the specific zip file URLs to download from CMS for the rest of the scripts to work.
• downloader.py: Contains the function download_and_extract_data for downloading and extracting data files.
• db_loader.py: Contains the function load_data_to_db for loading CSV data into the SQLite database.
• transformations.py: Contains the function create_and_persist_transformations for creating and persisting data transformations in the database.
• requirements.txt: Contains needed packages to install in the environmennt running.
• data: Folder that contains data file locally after download of zipfiles

Each file contains comments that explain the purpose of each function and how the code works.