Search PubMed⌕ Search

PubMed · 9932686

Using queueing theory to determine operating room staffing needs.

Abstract

BACKGROUND: To meet American College of Surgeons criteria, Level I and II trauma centers are required to have in-house operating room (OR) staff 24 hours per day. According to the number of emergency cases occurring, hospitals may have varying needs for OR staffing during the night shift. Queueing theory, the analysis of historic data to provide optimal service while minimizing waiting, is an objective method of determining staffing needs during any time period. This study was done to determine the need to activate a backup OR team during the night shift at a designated, verified Level II trauma center. METHODS: The basic queueing theory formula for a single-phase, single-channel system was applied to patients needing the services of the OR. The mean arrival rate was determined by dividing the number of actual cases by 2,920 hours in a year (8 hours per night x 365). The mean service rate is determined by averaging the length of the actual cases during the period studied. Using the mean arrival rate and the mean service rate, the probability of two or more patients needing the OR at the same time was determined. This probability was used to reflect the likelihood of needing to activate the backup OR team. Simulation was then used to calculate the same probability and validate the results obtained from the queueing model. RESULTS: All OR cases (n = 62) beginning after 11 PM and before 7 AM from July 1, 1996, through June 30, 1997, were analyzed. During the study period, the average arrival rate (A) was one patient every 5.9 days (0.0212 patient every hour), with an average service rate (mu) of 80.79 minutes per patient (0.7427 patients per hour). According to queueing theory, lambda = 0.0212 patients per hour, mu = 0.7427 patients per hour, lambda/mu = 0.0285, the probability of no patients being in the system (P0) = 0.9714, P1 = 0.0278, P> or =2 = 1 - (0.0278 + 0.9714) = 0.0008. The probability of two or more cases occurring simultaneously on the night shift is less than 0.1%. CONCLUSION: In our institution, activation of a second OR team is unnecessary when the first team is busy with a case on the night shift because the likelihood of two cases occurring concurrently is less than one in a thousand. Queueing theory can be a valuable tool to use in determining the staffing needs of many hospital departments. Trauma centers should apply this mathematical model in optimizing the use of their operational resource.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J B Tucker, J E Barone, J Cecere, R G Blabey, C K Rha. 1999. Using queueing theory to determine operating room staffing needs.. https://doi.org/10.1097/00005373-199901000-00012

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Groundwater-surface water interaction and its role on TCE groundwater plume attenuation.

A field investigation of a TCE plume in a surficial sand aquifer shows that groundwater-surface water interactions strongly influence apparent plume attenuation. At the site, a former industrial facility in Connecticut, depth-discrete monitoring along three cross-sections (transects) perpendicular to groundwater flow shows a persistent VOC plume extending 700 m from the DNAPL source zone to a mid-size river. Maximum TCE concentrations along a transect 280 m from the source were in the 1000s of microg/L with minimal degradation products. Beyond this, the land surface drops abruptly to a lower terrace where a shallow pond and small streams occur. Two transects along the lower terrace, one midway between the facility and river just downgradient of the pond and one along the edge of the river, give the appearance that the plume has strongly attenuated. At the river, maximum TCE concentrations in the 10s of microg/L and similar levels of its degradation product cis-DCE show direct plume discharge from groundwater to the river is negligible. Although degradation plays a role in the strong plume attenuation, the major attenuation factor is partial groundwater plume discharge to surface water (i.e. the pond and small streams), where some mass loss occurs via water-air exchange. Groundwater and stream mass discharge estimates show that more than half of the plume mass discharge crossing the first transect, before surface water interactions occur, reaches the river directly via streamflow, although river concentrations were below detection due to dilution. This study shows that groundwater and surface water concentration measurements together provide greater confidence in identifying and quantifying natural attenuation processes at this site, rather than groundwater measurements alone.

Connecticut↗