Modeling the critical care pathway for cardiothoracic surgery

Area of Science:

• Healthcare Operations Research
• Surgical Workflow Optimization
• Patient Flow Management

Background:

• The West of Scotland Heart and Lung Centre faced challenges with increasing waiting times and patient cancellations due to high demand and unpredictable patient arrivals and lengths of stay (LOS).
• Limited resources, particularly High Dependency Unit (HDU) beds, exacerbated these issues, impacting the efficiency of cardiothoracic surgery services.

Purpose of the Study:

• To investigate the effectiveness of an enhanced scheduling strategy and resource reallocation in reducing patient cancellations and improving patient flow.
• To identify the primary bottlenecks within the cardiothoracic surgery process using simulation modeling.

Main Methods:

• Discrete Event Simulation (DES) was employed to model patient pathways and resource utilization.
• Patients were categorized into six types based on condition and LOS, with historical data used to create LOS distributions for the simulation.
• The model was validated against actual hospital observations to ensure accuracy.

Main Results:

• The simulation accurately reflected real-world observations and identified High Dependency Unit (HDU) bed usage as the critical bottleneck.
• Enhancing the schedule to level daily patient arrivals to HDUs decreased cancellations by 20%.
• Combining schedule enhancement with minor capacity reallocations achieved a reduction in cancellations exceeding 60%.

Conclusions:

• Discrete Event Simulation is a valuable tool for analyzing and optimizing complex healthcare systems like cardiothoracic surgery.
• Strategic scheduling adjustments and targeted capacity reallocations, particularly concerning HDU beds, are crucial for mitigating patient cancellations and improving operational efficiency.