Management by constraints: considering patient volume when adding medical staff to the emergency department.
BACKGROUND
The emergency department is one of the hospital's busiest facilities and is frequently described as a bottleneck. Management by constraint is a managerial methodology that helps to focus on the most critical issues by identifying such bottlenecks. Based on this theory, the benefit of adding medical staff may depend on whether or not physician availability is the bottleneck in the system.


OBJECTIVE
To formulate a dynamic statistical model to forecast the need for allocating additional medical staff to improve the efficacy of work in the emergency department, taking into account patient volume.


METHODS
The daily number of non-trauma admissions to the general ED was assessed for the period 1 January 1992 to 1 December 1995 using the hospital computerized database. The marginal benefit to shortening patient length of stay in the ED by adding a physician during the evening shift was examined for different patient volumes. Data were analyzed with the SAS software package using a Gross Linear Model.


RESULTS
The addition of a physician to the ED staff from noon to midnight significantly shortened patient LOS: an average decrease of 6.61 minutes for 80-119 admissions (P < 0.001). However, for less than 80 or more than 120 admissions, adding a physician did not have a significant effect on LOS in the ED.


CONCLUSIONS
The dynamic model formulated in this study shows that patient volume determines the effectiveness of investing manpower in the ED. Identifying bottleneck critical factors, as suggested by the theory of constraints, may be useful for planning and coordinating emergency services that operate under stressful and unpredictable conditions. Consideration of patient volume may also provide ED managers with a logical basis for staffing and resource allocation.
Rotstein
Zeev
Z
Department of Medical Management, Sheba Medical Center, Tel Hashomer, Israel. zeevr@post.tau.ac.il
Wilf-Miron
Rachel
R
Lavi
Bruno
B
Seidman
Daniel S
DS
Shahaf
Poriah
P
Shahar
Amir
A
Gabay
Uri
U
Noy
Shlomo
S
D000704:Analysis of Variance; D003201:Computers; D004636:Emergency Service, Hospital / Q000458:organization & administration* / Q000706:statistics & numerical data; D005544:Forecasting; D006801:Humans; D007557:Israel; D007902:Length of Stay; D008505:Medical Staff, Hospital / Q000706:statistics & numerical data*; D013997:Time Factors