System dynamic modeling: an alternative method for budgeting.
OBJECTIVE
To construct, validate, and simulate a system dynamic financial model and compare it against the conventional method.


METHODS
The study was a cross-sectional analysis of secondary data retrieved from the National Health Security Office (NHSO) in the fiscal year 2004. The sample consisted of all emergency patients who received emergency services outside their registered hospital-catchments area. The dependent variable used was the amount of reimbursed money. Two types of model were constructed, namely, the system dynamic model using the STELLA software and the multiple linear regression model. The outputs of both methods were compared.


RESULTS
The study covered 284,716 patients from various levels of providers. The system dynamic model had the capability of producing various types of outputs, for example, financial and graphical analyses. For the regression analysis, statistically significant predictors were composed of service types (outpatient or inpatient), operating procedures, length of stay, illness types (accident or not), hospital characteristics, age, and hospital location (adjusted R(2) = 0.74). The total budget arrived at from using the system dynamic model and regression model was US$12,159,614.38 and US$7,301,217.18, respectively, whereas the actual NHSO reimbursement cost was US$12,840,805.69.


CONCLUSIONS
The study illustrated that the system dynamic model is a useful financial management tool, although it is not easy to construct. The model is not only more accurate in prediction but is also more capable of analyzing large and complex real-world situations than the conventional method.
Srijariya
Witsanuchai
W
Social and Administrative Pharmacy Unit, Department of Pharmacy, Faculty of Pharmacy, Mahidol University, Bangkok, Thailand. witsanuchai@hotmail.com
Riewpaiboon
Arthorn
A
Chaikledkaew
Usa
U
D002017:Budgets; D003430:Cross-Sectional Studies; D004632:Emergency Medical Services / Q000191:economics*; D005260:Female; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D016014:Linear Models; D008297:Male; D018803:Models, Economic; D011237:Predictive Value of Tests; D012984:Software; D013785:Thailand