Simulation - Using Simulation to Reduce Length of Stay in Emergency Departments
•Object of the study – a medium to large hospital in the southeast
•Simulation software – MedModel
•10 steps in the project
•Identify the process to be simulated
•Define the goals and objectives of the study
•Formulate and define model
•Collect data
•Build the model
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Hospital emergency departments are having to cope with increasing pressures from competition, reimbursement problems and healthcare reform. The hospital’s customers are less willing to accept long waits in any department, but especially in the Emergency department.
Simulation was done for a hospital where the average patient waiting time in the emergency department was 157 minutes, significantly greater than the acceptable average of 120 minutes.

MedModel is a healthcare industry-specific simulator package with some advantages over other products.  These advantages include the ability to capture and release resources, the use of pathway networks to allow resources to walk up and down hallways and through doors, and graphical interactions.

The first step was to identify the process. In this case, the process was patient flow through Emergency Services. The study would focus on all the steps occurring from the time the patient entered the emergency department until the patient was released, admitted to ward or transferred to another department

The objective was to reduce the patient’s length of stay. Each alternative could be tested on-screen and evaluated for effectiveness.

The model should be planned and defined upfront, with the data collection requirements thoughout and scheduled in advance. Failure to take the time to design the model is one of the biggest reasons for projects not being completed on time.

The need to have a central database of information about patient visits became apparent. The type of data needed for the study was the same data that is needed over and over again to track progress and for assessment of current trends. 14 categories of patients were identified, flow charts were made for each type.

The model included 17 resources, 4 entities, 29 shifts, 6 result files, 20 variables, 20 attributes, 1 array, 8 subroutines, 12 macros, 8 function tables, 2 distribution tables, 11 arrival cycle tables and patient processing and routing logic

(McGuire, 1994).