Measured effects of user and clinical engineer training using a queuing model.

Area of Science:

• Biomedical Engineering
• Operations Research
• Healthcare Management

Background:

• Clinical engineering departments manage numerous work orders for medical devices.
• Efficient management of these work orders is crucial for patient safety and operational continuity.
• Existing methods for measuring work order performance may lack precision.

Purpose of the Study:

• To propose and validate a queuing model for calculating key performance indicators in clinical engineering.
• To assess the impact of the queuing model on work order metrics such as count, turnaround, response, and service time.
• To evaluate the model's effectiveness in a real-world hospital environment.

Main Methods:

• A queuing model was developed as a measurement tool for clinical engineering work orders.
• The model was simulated using ARENA 3.01 software in a 600-bed hospital.
• Real work order data from 2002 was collected and compared against simulation predictions.

Main Results:

• The queuing model demonstrated a significant reduction in nonscheduled work order indicators.
• Response time decreased from 27 to 0.56 hours; turnaround time reduced from 27.48 to 1.13 hours.
• The monthly backlog of repair orders decreased from 22 to 4, and simulated vs. real values showed less than 5% difference.

Conclusions:

• The proposed queuing model is an effective tool for optimizing clinical engineering work order management.
• Implementation led to substantial improvements in efficiency and reduced operational delays.
• The model accurately predicted outcomes and highlighted the benefits of user and CE training.