Workflow optimisation for multimodal imaging procedures: a case of combined X-ray and MRI-guided TACE

Area of Science:

• Radiology and Medical Imaging
• Operations Research
• Health Systems Engineering

Background:

• Multimodal image-guided procedures (MIGP) are increasingly complex.
• Optimizing workflow in MIGP is crucial for efficiency and patient care.
• Current workflows may present bottlenecks, leading to delays.

Purpose of the Study:

• To develop and apply a discrete event simulation (DES) framework for workflow optimisation of MIGP.
• To identify and evaluate alternatives for improving workflow efficiency in combined X-ray and MRI-guided procedures.
• To quantify the potential reduction in waiting times for transarterial chemoembolisation (TACE) patients.

Main Methods:

• A discrete event simulation (DES) model was developed using data from 59 transarterial chemoembolisation (TACE) procedures.
• A ranking and selection optimisation algorithm was employed to assess proposed workflow alternatives.
• Performance metrics focused on minimizing waiting times and improving overall workflow.

Main Results:

• Analysis revealed an average waiting time of 20.68 minutes between angiography and MRI in 71.19% of cases.
• Fourteen workflow alternatives were evaluated to improve efficiency.
• An optimized alternative was identified, potentially reducing waiting times in the angiography suite by up to 48.74%.

Conclusions:

• Discrete event simulation (DES) provides a cost-effective method for analysing and optimizing MIGP workflows.
• The study successfully identified workflow bottlenecks and proposed effective solutions for multimodal TACE procedures.
• Simulation-based analysis can significantly reduce patient waiting times and improve resource utilization in clinical radiology.