Before we do the questions, let's check the preliminaries (unless you'd rather skip to question 2):
What is lambda?
(For these answers, use hours as the units of time.)
What is mu?
What is M?
What is rho?
To calculate the answers to questions 2, 3, and 4, you need to first
calculate the the probability that, at any particular time, no one will
be in the system. What is that probability of 0 in the system?
Next you need Lq, because the other quantities' formulas are based on
it. What did you get for Lq?
Now you're ready to do the problems.
2. What is the average number of patients in the ER
(waiting or being served?)
3. What is the average length of time that a patient spends from the
time they enter the ER to the time they leave?
4. The waiting area is separate from the examining/treatment room. How
many chairs should there be in the waiting area to reduce the probability
that someone will have no chair to less than 0.01? (No fractions of chairs,
5. Suppose the hospital has announced, as part of a TQM policy, that
it will discount each patient's bill by $6.00 per hour that the patient
waits in the ER waiting area. How much will this discount cost the hospital
per hour on the average? (Note that patients get paid only for waiting time, not for service time.
Also note that patients get paid proportionally for fractions of hours spent waiting.)
6. Suppose a physician costs $30 per hour. If the $6.00 per hour waiting
penalty is in effect, does it pay to add the second physician? You must
compare the situation when you have one physician with the situation when
you have two.
7. Regardless of the answer to question 6, which gives
you shorter waits overall, one ER with two physicians or two separate ER's
with one physician in each one, each serving half as many patients on the
average? Based on this comparison alone, is it better to have centralized
or decentralized ER facilities in a city?
Help with question 7: The rest of the applets lead you through answering question 7. Use them if you would like help with that question.
Back to question 7.