Emergency Department Simulation
An interactive Streamlit simulation of patient flow through an emergency department, used to explore where overcrowding and delays actually come from.
The problem
Emergency departments face overcrowding, long wait times and resource misallocation, but it's hard to see which lever — arrival rate, staffing, waiting-room capacity — is actually the bottleneck without testing changes on real patients.
Why it mattered
Lets someone adjust arrival rates, capacity and resources and see the effect on patient flow before anything changes in the real department.
Topics
Built with
Engineering
A discrete simulation engine written in Python tracks patients through each stage of an ED visit — arrival, waiting, treatment, exit — while a Streamlit interface lets you adjust arrival rate, waiting-room capacity, and available resources and watch the effect on flow in real time.
Model
This isn’t a predictive model — it’s a simulation. The value is in being able to change one variable at a time (staffing, capacity, arrival rate) and see where the queue actually builds up, which is hard to reason about from intuition alone.
Deployment
Runs as a hosted Streamlit app — try it directly rather than reading about it.
Results
The simulation surfaces where bottlenecks form under different staffing and capacity assumptions. Specific efficiency percentages aren’t published here — they weren’t tied to a documented, reproducible test scenario, so they’re left out rather than restated without that backing.
Lessons
Simulating a system is a different skill from modelling one: the interesting part wasn’t the code that moves a “patient” from one state to the next, it was deciding what to hold fixed and what to expose as a variable so the tool actually answers a useful question.