ER Patient Analysis

What are the common trends and patterns amongst our ER patients? How many patients came to the ER? What are the demographics of our patients? Where are our patients from? What can this tell us?

This is an analysis of Emergency Room patients focusing on patient volume, patient insurance, and patient demographics in February 2023. Using Python's Jupyter Notebook and packages such as Pandas, NumPy, and MatPlotLib, I cleaned and analyzed a data set with over 18,000 rows of patient data, and dynamically reported my findings using Tableau Dashboards.

Dashboards

Methodology

Understanding the data
- I pulled everything into Python to observe and manipulate the data easily
- I filtered and queried the data to understand it better - asking questions like:
  - “How many patients are in the dataset?”
  - “What does each column tell us about the patient?”
  - “Which columns are relevant to my analysis and which aren’t?”
  - “Are there missing values in the data?”
  - “Are there any obvious typos or misinformation in the data?”
Cleaning and creating uniformity in the data
- Observed and handled data with missing values
- Aggregated and generalized related data
- Created new columns with relevant information
- Reformatted to handle rows with any typos, misinformation, etc.
Observing and Analyzing the data
- Created short visualizations in Python to observe the data more clearly
- Identified relevant trends and patterns
- Looked for outliers and strange data
- Checked to make sure that everything makes sense
Creating a Framework and Outline
- Created general outline in Python using charts, graphs, and formulas
- Performed several queries and extracted important information to later be reported such as:
  - “How many patients check in and out of the hospital each day?”
  - “What are the top 5 Insurance Payers?”
  - “How many patients live out of state?”
  - “If a patients needed an interpreter, what languages did they prefer?”
Reporting in Tableau through Dashboards
- Selected visualizations that I wanted to include from the outline
- Created interactive charts in Tableau, displaying patient trends
- Created several Dashboards with different themes to report patient trends dynamically

Insights

- Why are men coming to the ER less than women?
  - Men came to the ER significantly less than women in February 2023. It would be interesting to see if this is a persistent trend and how we can encourage more men to use our ER services if so.