San Diego State University Emergency Room Paper

Build Model 7.1 (The Emergency Room simulation with four different
patient types) as presented in the ppt slides and the screencast video
above. Make sure your model incorporates and addresses patient
priorities. Create experiments with response variables, add model properties and/or extend the model to answer following questions:

Q1) How much time does “Routine” patients spent in this system?

Q2) How much time does “Routine” patients spent waiting in the ED queue?

Q3)
We would like to keep average “Routine” patient wait time in ED queue
below 30 minutes. What is the minimum capacity in the ED needed to
attain that target?

Note: Run your model for 1100 days with a warm-up time of 100 days for 25 replications.

Submit:
Your Simio model file and a response document (word document) to the
listed questions. Clearly present the evidence with screenshots from
your model and experiments in terms of how you got to the reported
results. Discuss your findings. Your Simio model file should also
include the experiments reported in your response document.

Hint: Here is one approach how to accomplish Q2 (for computing the routine wait time):

1. I create a tally statistic element to capture Routine patient wait time.

2. I also create a model entity state to capture wait time for Routine entities

3. When an entity enters the ED I run an add-on process. (I choose the process trigger “before processing” option)

4. Within the add-on process I include the following:

4.1 I check whether the arriving entity is a routine patient. (You
can use a “Decide” step from the standard process library)

4.2 If it is, then I compute the time between the current simulation
time and the time when model entity was created and I use an Assign step
this time to assign this value to the model entity state I created
earlier

4.3 Use a tally step to assign the model entity value to the tally statistic I created earlier

5. Use the tally statistic in the experiment window to get the average value reported.