Simulation of Patient Flow in Healthcare with SimPy and Power Bi

Challenge Background

In England, over 7.5 million people are waiting for hospital treatment or therapy. Demand exceeds hospital capacity, and the burden of the disease worsens as the waiting list gets longer.

The Problem

Diagnostics are a constraint in accessing treatment. Healthcare planners need the capacity to simulate patient flow and forecast demand. SimPy is a process-based discrete-event simulation package based on standard Python.    

An open-source simulation model with one-shot optimization capability deployed to a web interface would deliver a valuable tool for healthcare planners. Furthermore, a free simulation environment would enable better collaboration between healthcare systems and the generation of anonymous synthetic data. 

Goal of the Project

Leverage the SimPy library and Power Bi to develop an embedded web simulation service. Generate synthetic data and deploy to a URL-end point to capture run data for future ML training models.  

Project Timeline

What you'll learn

Leverage the SimPy library and Power Bi to develop an embedded web simulation service. Generate synthetic data and deploy to a URL-end point to capture run data for future ML training models.