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Canadian Journal of Anesthesia 48:A16 (2001)
© Canadian Anesthesiologists' Society, 2001

Abstracts - Monday June 11 15:45 p.m. - 17:45 p.m.

CAPACITY MODELING OF EMERGENCY SURGERY

David P. Archer, MD, Tim K.K. Tang, MD and Ian R. Staveley, CA

Department of Anesthesia, Foothills Medical Center, 1403 29th Street N.W., Calgary, Alberta, T2N 2T9

INTRODUCTION

We examined the efficacy of queuing theory to predict the frequency of backup team activation for emergency surgery in a tertiary care regional trauma center. Queuing theory is applied to problems in operations research such as the number of switches required to handle incoming calls at a switchboard. Only two variables are required to apply queuing theory: the rate of arrival ({lambda}) of new patients and the duration of surgery.1

METHODS

The OR database from March 31,1999 to April 1, 2000 was searched for cases with start times between 2330 and 0730 to determine the start and finish times. We calculated the mean arrival rate of patients for the year ({lambda}) (total number of patients/number of nighttime hours), and the median service rate (µ) (1/ median duration of surgery). The probabilities of no patient (P0), one patient (P1), and more than one patient (P>=2) in the OR were calculated from P0=1-8/µ, P1= P0({lambda}/µ) and P>=2= 1-(P0+ P1) respectively.1 The number of backup team activations was predicted from P>=2 x total number of patients.1 The database was directly searched for cases during the same time period that had overlapping times.

RESULTS

Results are shown in the TableGo. Case durations followed a Poisson distribution. There were 28% fewer backup team activations observed (33) than would be predicted (46) using queuing theory.


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DISCUSSION

The difference between the queuing theory predicted and observed number of backup team activations is probably due to the effects of triage. Predictions based upon queuing theory may approximate the situation that would occur if all patients had to be accommodated in the operating suite immediately. Queuing theory may be useful in health resource management.

REFERENCES

1 Tucker JB, Barone JE, Cerere J, Blabey RG, Rha C-K. J Trauma 1999; 46: 71[Medline]





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