Skip to content

jonah-ernest/simio-hospital-ward-simulation

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

18 Commits
 
 
 
 
 
 

Repository files navigation

Hospital Ward and ICU Flow Simulation

This repository contains a discrete-event simulation study modeling patient flow through hospital wards and intensive care units (ICUs). The project analyzes congestion, diversion policies, and capacity utilization using Simio and scenario-based experimentation.

The work was completed in Fall 2022 as part of a Systems Modeling and Simulation course.


Project Overview

Hospitals must balance fluctuating patient arrivals with limited inpatient and ICU capacity. This project builds a detailed simulation model to examine:

  • Patient arrival patterns and routing decisions
  • Ward and ICU service-time distributions
  • Queueing behavior and bed utilization
  • Diversion thresholds under congestion
  • Scenario comparisons across operating policies

Multiple experimental scenarios were run to evaluate how changes in capacity, thresholds, and demand affect throughput and waiting times.


Files and Folders

  • Hospital_Ward_ICU_Simulation_Report.pdf
    Final written report describing assumptions, model structure, experiments, and findings.

  • simio/hospital_flow_simio.spfx
    The complete Simio project file. Download and open this file in Simio to run the model.

  • simio/project-files/
    Extracted project contents included for transparency and version control.


Running the Model

To explore the simulation:

  1. Install the Simio desktop application.
  2. Download simio/hospital_flow_simio.spfx.
  3. Open the file directly in Simio.
  4. Use the experiment panels to run scenarios and view results.

Large experiment output files were excluded from the repository to keep it lightweight. Summary results are provided in the report.


Methods and Techniques

  • Discrete-event simulation
  • Queueing analysis
  • Scenario experimentation
  • Capacity planning
  • Diversion-threshold evaluation
  • Healthcare operations modeling

Tools and Technologies

  • Simio (desktop simulation environment)
  • Experiment Manager and scenario runner
  • Input modeling and distribution fitting (R and Excel)
  • CSV/XLSX exports for analysis

About

Time-series forecasting of energy stock prices using Holt’s exponential smoothing, regression models, and sensitivity analysis.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors