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Optimizing PICU Resource Management: A Data-Driven Discrete Event Simulation Approach for Capacity and Flow Modeling.

Alireza Akhondi-Asl1,2,3, Michael L McManus1,2,3, Peter C Laussen4

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Summary
This summary is machine-generated.

This study developed a discrete event simulation (DES) model to optimize hospital patient flow and resource use. The model accurately predicted outcomes when accounting for downstream unit capacity, crucial for effective hospital operations.

Keywords:
capacity planningdiscrete event simulationhospital resource allocationoperations managementpatient flow

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Area of Science:

  • Healthcare Operations Research
  • Biomedical Informatics
  • Systems Engineering

Background:

  • Hospitals require advanced tools for optimizing resource utilization and patient flow.
  • Data-driven insights are essential for improving hospital management.
  • Existing models may not fully capture the complexities of multiunit patient flow.

Purpose of the Study:

  • To develop and evaluate a flexible, data-driven discrete event simulation (DES) model.
  • To optimize capacity utilization and patient flow in a multiunit hospital system, focusing on the Pediatric Intensive Care Unit (PICU) and downstream units.
  • To provide a tool for enhancing hospital operational decision-making.

Main Methods:

  • Retrospective discrete-event simulation modeling and validation study.
  • Utilized historical patient admission data from a quaternary referral hospital (Boston Children's Hospital, January 2012 - February 2025).
  • Validated the model against a real-world PICU expansion scenario.

Main Results:

  • The DES model accurately predicted post-expansion PICU length of stay and capacity utilization when downstream unit capacities were incorporated.
  • Simulations highlighted the critical impact of downstream bottlenecks on overall patient flow and resource utilization.
  • The model demonstrated utility for capacity planning and optimizing new service line scheduling using synthetic data.

Conclusions:

  • The open-source DES model effectively simulates patient flow across multiple hospital units.
  • It offers a powerful, flexible tool for administrators to optimize hospital operations and resource allocation.
  • The model is transferable and adaptable to various healthcare systems and scenarios.