Simulation-Assisted Metamodeling and Performance Analysis of a Healthcare Center

Young Hoon Lee, Farrukh Rasheed, Sun Hoon Kim, Kyung Sup Kim, Hyunbo Cho, and Sooyoung Kim


Simulation, Regression , Decision Making, Modeling Healthcare Services, Operation Management


A simulation model of patient throughput in the community healthcare center (CHC) is developed to appraise imperative variables of interest and to examine how each variable effect desired performance measures. To blend analytical methods’ mathematical supremacy with the modeling-ability of simulation, meta-modeling approach is applied to abridge simulations’ computational burden. A single meta-model represents a single performance measure. For any system, the solution found using a single metamodel representing a specific performance measure i.e. system throughput may be sub-optimal having detrimental effect on other crucial performance measures i.e. resource utilization, work-in-process, lead times etc. if not considered during analysis. Thus, it’s emphasized in this research to develop all possible met-models representing all the crucial performance measures individually for the purpose of overcoming aforesaid drawback i.e. chances of finding/implementing a sub-optimal solution. The eminent advantage: the final solution using above-mentioned technique will qualify itself as a real optimal solution no short in terms of all crucial performance measures for the system. Obviously, this technique will be helpful for management to predict the impact of selected independent factors on daily service levels, will serve as suggestion models for day-to-day decisions assistance, resources pro-active management and utilization, extrapolation etc. to maintain desired service levels.

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