How many operating rooms are needed to manage non-elective surgical cases? A Monte Carlo simulation study

Area of Science:

• Healthcare Operations Research
• Medical Simulation
• Queuing Theory Applications

Background:

• Long wait times for urgent and emergency surgery are a significant patient concern.
• Optimizing operating room (OR) resources is crucial for minimizing patient delays.
• Queuing theory and computer simulation offer methods to determine optimal OR numbers.

Purpose of the Study:

• To develop a computer program using Monte Carlo simulation.
• To determine the optimal number of operating rooms (ORs) needed.
• To minimize patient wait times while optimizing resource allocation for non-elective surgeries.

Main Methods:

• Utilized institutional patient arrival data and surgical procedure lengths.
• Applied Monte Carlo simulation to a tertiary-care academic medical center.
• Analyzed OR needs for day/evening (0600-2200) and night (2200-0600) shifts.

Main Results:

• Simulating 4 ORs (day/evening) and 3 ORs (night) yielded acceptable wait times.
• Emergency cases (surgery within 2h) had a median wait of 0 min (mean 19 min).
• Urgent cases (surgery within 8-12h) had a median wait of 34 min (mean 136 min).

Conclusions:

• Monte Carlo simulation effectively guides decisions on balancing surgical resources.
• The model helps optimize OR allocation for both elective and non-elective procedures.
• This simulation approach can improve efficiency in surgical scheduling and patient flow.