University Health Services Case Study

1. With the help of process flow diagrams, compare the pre-triage and the post-triage systems in terms of total system time and total waiting times. Is the new system an improvement over the old? 2. Look at the patient arrival rates and compare them to the available MD and NP capacity. An hour-by-hour or day-by-day analysis will show some interesting patterns. Based on what you have learned about waiting lines and utilization, comment on the current assignment fitness between supply and demand?   |  |  |Patients waiting |Patients waiting |  |  |  |  | |  |  |67% |33% |MD |NP |Availability |  |Patients per hour treated |  | |  |Arrival |MD |NP |Beg of HR |Serviced |End of HR |Beg of HR |Serviced |End of HR |MD |NP |MD |NP | |8am – 9am |18. 2 |12. 194 |6. 006 | – | 6. 19 | 6. 01 | – | 3. 66 | 2. 35 |2. 0 |2 |3. 0927835 |1. 8292683 | |9am – 10am |17. 6 |11. 792 |5. 808 | 6. 01 | 7. 73 | 10. 07 | 2. 35 | 7. 32 | 0. 84 |2. 5 |4 |  |  | |10am – 11am |16. 8 |11. 56 |5. 544 | 10. 07 | 14. 85 | 6. 48 | 0. 84 | 7. 32 | (0. 93) |4. 8 |4 |  |  | |11am – 12 noon |15. 2 |10. 184 |5. 016 | 6. 48 | 9. 90 | 6. 77 | (0. 93) | 7. 32 | (3. 24) |3. 2 |4 |  |  | |12 noon – 1pm |11. 8 |7. 906 |3. 894 | 6. 77 | 8. 04 | 6. 63 | (3. 24) | 4. 57 | (3. 91) |2. 6 |2. 5 |  |  | |1pm – 2pm |16. 9 |11. 323 |5. 577 | 6. 63 | 8. 66 | 9. 29 | (3. 91) | 4. 7 | (2. 91) |2. 8 |2. 5 |  |  | |2pm – 3pm |16. 2 |10. 854 |5. 346 | 9. 29 | 10. 52 | 9. 63 | (2. 91) | 7. 32 | (4. 88) |3. 4 |4 |  |  | |3pm – 4pm |15. 9 |10. 653 |5. 247 | 9. 63 | 12. 37 | 7. 91 | (4. 88) | 7. 32 | (6. 95) |4 |4 |  |  | |4pm – 5pm |11. 6 |7. 772 |3. 828 | 7. 91 | 8. 35 | 7. 34 | (6. 95) | 4. 57 | (7. 70) |2. 7 |2. 5 |  |  | |5pm – 6pm |2. 8 |1. 876 |0. 924 | 7. 34 | 3. 9 | 6. 12 | (7. 70) | 3. 66 | (10. 43) |1 |2 |  |  | | An hour by hour analysis shows that there is an excess demand for MDs (positive numbers) and excess supply of NPs (negative numbers). Also, demand is not aligned with supply at the beginning of each day as arrival rates are highest between 8:00am – 10:00am yet the supply (MD’s on staff) is at the lowest for the day – at just 2 and 2. 5. Currently, there is not a strong correlation between supply and demand as proper staffing levels are not assigned to accommodate demand needs on an hour by hour basis.

Demand clearly calls for highest staffing levels at the beginning of the day and then right after the lunch hour whereas the availability of MDs and NPs is all over the board throughout the day. Also, NPs are underutilized as there are no patients waiting after 11:00am while MDs are a bottleneck as they have too many patients waiting for them throughout the day. In addition, day of the week needs to play a factor in staffing levels as the first half of the week is clearly busier than the second. 3. A desired outcome of the new triage system is to off-load work from MDs onto NPs.

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How cost-effective is this strategy, considering the different service rates of MDs and NPs? (Use salary data given in case. Make necessary assumptions. ) This strategy is cost effective given the hourly rates of NPs compared to those of MDs. However, the current process does not effectively leverage that as they are not off-loading enough patients to NPs given the wait times for MDs. Essentially, they need to find a way to move more patients to the NP queue. One way to do this would be by expanding upon the 13 categories currently deemed treatable by an NP.

Also, they need to make sure the triage nurses are assigning patients to NPs (if eligible) vs. NP or MD in order to free up MD’s queue. 4. Assuming 5 MDs on duty at an average (each with a service rate of 3. 1 patients per hour) and that all patients (143 per day) see an MD, calculate the effect of a 4% increase in the arrival rate on the expected wait time in queue: Wq (use Queuing Formulas, assume uniform arrival across 10 working hours per day, note that it’s a multiple server system drawing from a single line – M/M/S). Comment on this effect. 5. If you were a healthcare administrator such as Ms.

Angel, how would your staffing decisions be different if your customers were college students versus business executives? Justify your answer. If our customers were college students versus business executives our staffing decisions would differ in that we would operate under the assumption that college students are typically more tolerant of longer wait times as their schedules are more flexible than those of executives. Also, college students may not be as concerned about the quality and personal care received by a specific MD (who is familiar with their medical history) as executives might be.

That said, we would operate more cost effectively by keeping our MD levels to a minimum and routing all eligible visits through NPs. In addition, we would not allow walk-in requests to see a specific MD as college audience would not find as much value in this as an executive might. Lastly, if you are a college student, you will likely use the most convenient walk-in clinic to you – the one right on the campus (even if they have longer wait times) while executives have many more options. So, there will be many more competing clinics that executives could go to in order to wait less and get better and personal care from an MD of their choice. . Why are “walk-in appointments” a problem if the students asking for specific providers are willing to wait longer? What should Ms. Angell do about them, if anything? Ms. Angell could either increase the cost of a visit to a specific MD (to discourage this practice) or eliminate this option altogether in order to free up more MDs and reduce wait times for other patients which would increase customer satisfaction for majority of patients at the cost of potentially losing the 24. 5% who do request seeing a specific MD. . What other actions, if any, would you recommend to Ms. Angell? Try to classify your actions in three categories: (1) managing capacity, (2) managing demand, and (3) managing the waiting experience. a) Capacity: Proper staffing levels – assigned according to arrival rates each day of the week and each hour of the day. This should optimize capacity and reduce waiting times. b) Demand: Control demand by assigning certain day of the week or time of the day when walk-in requests for a specific MD would be honored.

Or, assign walk-in request times to each MDs daily schedule – limiting it to only 1-2 hours per day. Offer special discounts or advertise low waiting times to patients with non-emergency visits during Thursdays and Fridays or towards and of each day when there is most capacity. c) Waiting: This can be improved by controlling the demand as suggested above. Also, triage nurses need to control the number of patients they put in the MD queue by always placing them in the NP queue if their diagnosis falls under one those that can be treated by an NP.