mobile-clinic-reporter

The Sun Bus is a non-profit mobile dermatology clinic providing free cancer screenings across various US cities. Our project aims to build a reporting tool that helps The Sun Bus analyse screening data, identify trends in diagnoses and generate both city-specific and cumulative reports.

Objectives

Correlate screening events (city) with county-level data and rural/urban classification (using MUI).

Generate the following statistics: Number of suspicious lesions diagnosed, Distribution of cases by region and rurality, Patients with multiple diagnoses, Allow continuous integration of new screening event data, Produce individual city reports and an evolving cumulative summary, Provide geographic data visualisations.

Datasets

EHR data: patient demographics, visit date, diagnosis information. The data has been generated based off of patient-anonymized data collected by The Sun Bus. City-county mapping: US cities and their corresponding counties (from: https://simplemaps.com/data/us-cities). Medically Underserved Index (MUI): rural/urban classification by county (from: https://data.hrsa.gov/tools/data-explorer). Tools: Python, GitHub for version control, Markdown for documentation

Target Users

Sun Bus Team (healthcare providers and analysts who require streamlined and up-to-date reports from mobile dermatology screenings), as well as other mobile clinics who can modify and use the tool for their benefit.

What you need to run this program

Option 1: Launch with Binder

In order to run the program directly from your browser no prerequisites are required on your local machine. Click on the button, then after the program loads run the cell in order to execute the program. The output files are not saved but may be downloaded manually. They can be accesed via the binder file explorer (upper left corner folder icon) the files take a short time to appear after the program runs.

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Option 2: Running on your local machine requires:

• Any code editor or terminal that supports Python
• Python installed (version 3.7+ recommended)
• The required libraries (see requirements.txt)
• The following files (located in the Data folder):
  • EHR_clinic_data.csv
  • MUA_DATA_2025.csv
  • US_City_County_Data.csv
  • us-states.json

Instructions: Dowload and extract the project zip. Then, simply run the main_pipeline.py in your code interpreter. The "Summary_Report" spreadsheet will be saved in the same directory as the executed script and the charts and maps will be saved saved in the generated "plots" directory.

Authors

Refer to members.txt file.