The results table contains statistical tools, including
mean, standard deviation, minimum and maximum
numbers, and confidence interval (currently set at
90% confidence). A confidence interval is used to determine
how accurate the model is and how much
variation there would be if the model were run many
times. A small confidence interval means there is
little variation between replications, and thus the
model can be seen as accurate.
In each scenario, the model was run for one day
from 8:00 a.m. to 7:00 p.m. Two of the scenarios
used a patient arrival rate of 13 patients per hour.
In Figure 7, the average length of stay for the urine
collection process can be seen; the average length of
stay for a patient was 101 minutes. The confidence
interval is (98, 105), so the team can conclude with
90% confidence that a patient’s clinic stay is between
98 and 105 minutes.
Figure 8 shows the patients’ length of stay at a
clinic where a urine collection is not performed; in
this scenario, the average length of stay for a patient
was 78 minutes. The confidence interval is (74, 83),
so the team can conclude with 90% confidence that
a patient’s length of stay in the hospital is between
74 and 83 minutes.
Figures 9 and 10 show the amount of time patients
spend in the waiting room and, as before, the
clinic hours were from 8:00 a.m. to 7:00 p.m. Figure
9 depicts the amount of time spent in a waiting
room for a patient who is seeing a physician and is
required to provide a urine sample. The average time
a patient spends in the waiting room in this scenario