Design and validation of a critical care simulation model

Area of Science:

• Healthcare Management
• Operations Research
• Health Systems Engineering

Background:

• Rising healthcare costs and restrictive reimbursement policies necessitate accurate critical care bed capacity planning.
• Existing bed-sizing models lack the complexity to reflect current critical care environments and haven't been validated with real-world data.

Purpose of the Study:

• To develop and validate a simulation model for optimizing critical care bed allocation.
• To address the limitations of current critical care bed-sizing methodologies.

Main Methods:

• Development and validation of a discrete-event simulation model using GPSS/H software.
• Incorporation of patient flow through operating rooms, post-anesthesia recovery, intensive care units (ICUs), and stepdown units.

Main Results:

• A validated simulation model capable of accurately representing patient flow and resource utilization within critical care settings.
• The model provides a tool for hospital administrators to determine optimal critical care bed numbers.

Conclusions:

• Simulation modeling offers a robust approach to critical care bed capacity planning.
• Validated models can improve resource allocation and potentially reduce healthcare costs.