Using simulation to determine the need for ICU beds for surgery patients

Background

As the need for surgical ICU beds at the hospital increases, the mismatch between demand and supply for those beds has led to the need to understand the drivers of ICU performance.

Method

A Monte Carlo simulation study of ICU performance was performed using a discrete event model that captured the events, timing, and logic of ICU patient arrivals and bed stays.

Results

The study found that functional ICU capacity, ie, the number of occupied ICU beds at which operative procedures were canceled if they were known to require an ICU stay, was the main determinant of the wait, the number performed, and the number of cancellations of operative procedures known to require an ICU stay. The study also found that actual and functional ICU capacity jointly explained ICU utilization and the mean number of patients that should have been in the ICU that were parked elsewhere.

Conclusion

The study demonstrated the necessity of considering actual and functional ICU capacity when analyzing surgical ICU bed requirements, and suggested the need for additional research on synchronizing demand with supply. The study also reinforced the authors' sense that simulation facilitates the evaluation of trade-offs between surgical management alternatives proposed by experts and the identification of unexpected drawbacks or opportunities of those proposals.