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Patient Flow Simulator

The Patient Flow Simulator is a Python application designed to simulate patient flows using Camunda BPMN diagrams and the SpiffWorkflow library.

Structure

  • runner.py: Entry point for running the application, contains the number of patients to be put through.
  • playbook.py: Defines procedures related to a patient visit including registration, triage, and visit areas.
  • simulation.py: Handles the simulation of patient flows, including assigning triage levels and managing doctors' schedules. Contains the configuration for the number of doctors, nurses, etc. during the simulation.
  • generator.py: Generates random data or scenarios for the simulation. (TO BE EXPANDED)

Dependencies

  1. Python3.x

  2. SpiffWorkflow:

    • Handles BPMN workflows, Camunda parsing, and user tasks.

  3. Standard Python Libraries:

    • random: For generating random values.
    • threading: For concurrent execution.
    • os: For OS-related tasks.
    • time: For time-based tasks.
    • csv: To work with CSV files.
    • json: For JSON data manipulation.
    • string: For common string operations.

Setup and Execution

  1. Ensure you have all dependencies installed.
  2. Run runner.py to start the simulation.

Notes

  • The simulation uses BPMN diagrams (Visit.bpmn and EDAsIs.bpmn) for the patient flow logic.
  • Adjust parameters in the respective Python files to modify the simulation's behavior.

Citation Information

  • The simulator has been publicized in the following paper. If you wish to use it for your own research, please cite the following paper (under publication as of 2023-08-23): Zoltán Szabó, Dr. Emőke Adrienn Hompot, Dr. Vilmos Bilicki. "Patient Flow Analysis with a Custom Simulation Engine" Acta Cybernetica -- under publication --

  • The ED model is based on the excellent work of Antonio Di Leva and Emilio Sulis: Antionio Di Leva, and Emilio Sulis. "A business process methodology to investigate organization management: a hospital case study." WSEAS Transactions on business and economics (2017): 100-109.