Queuing questions

Queuing questions

Case: Massachusetts General Hospital’s Pre-admission Testing Area (PATA)

McCarty, Kelsey, Gallien, et al. (2012, January 3). Massachusetts General Hospital’s Pre-admission Testing Area (PATA). MIT Sloan School of Management. Case: 11–116. Retrieved from https://mitsloan.mit.edu/LearningEdge/operations-management/PATA/Pages/default.aspx

If the hyperlink above does not work directly (you do not need to register to MIT site), please copy the link below to your browser to open the case page directly: https://mitsloan.mit.edu/LearningEdge/operations-management/PATA/Pages/default.aspx

The Pre-Admission Testing Area (PATA) is an outpatient clinic at Massachusetts General Hospital responsible for conducting preoperative assessments of surgical patients prior to their procedures. Set in June 2009, this case study describes the conditions of this busy outpatient clinic prior to a process improvement effort by a collaborative team of MIT Sloan students and faculty and MGH clinicians and administrative staff. It also examines the complete PATA experience from both the patient and provider perspective. The importance of improving PATA is emphasized through a description of how this relatively small clinic has a very large downstream effect on the MGH operating rooms and the entire perioperative care system.

You are required to review the entire case study information available at the reference above and write a paper based on the suggested case questions below.

  1. Construct a process flow diagram of the PATA visit from a patient’s perspective. Calculate the capacity and utilization rate at each step in the process.
  2. Use capacity analysis tools (build-up diagrams or/and queuing) to decide if and where there is a bottleneck in the clinic. If a bottleneck does indeed exist, how long do patients wait as a result of the bottleneck? (As an approximation, assume that all appointment slots were filled and patients arrived on time.)
  3. Evaluate the three Task Force diagnoses – not enough time between appointments, not enough rooms, not enough physicians. Are these diagnoses valid? If so, are they primary contributors to long patient wait times? Why or why not?
  4. What factors contribute to variability in PATA process flow and what control, if any, does the clinic have to eliminate it?
  5. What changes would you recommend to improve PATA?
  • Use the information provided in the Background readings. Please do any additional research as necessary.
  • Review the information in PATA case study and become familiar with the products and processes.
  • There is no set response to the case questions, so do not hesitate to think outside the box.
  • It is essential to provide a well-written paper with detailed analysis.

READ the information provided by the resources and references on the Background page. Understand the theory and concept of process management and productivity improvement.

NOTE: Cite the references in the Background, as well as additional references you use in your Case paper.

The report should be at least 5–6 pages

Background Reading:

Global Text Project (2017), Operations management: Special topic: supply chain management. OpenStax CNX. Retrieved from: https://cnx.org/contents/EEichvM_@5/Operations-management-What-is-

Global Text Project (2017), Operations management: The input/output transformation model. OpenStax CNX. ‎Retrieved from https://cnx.org/contents/_yBkSAt4@4/Operations-management-The-inpu

McCarty, Kelsey, Gallien, et al. (2012, January 3). Massachusetts General Hospital’s Pre-admission Testing Area (PATA). MIT Sloan School of Management. Case: 11–116. Retrieved from https://mitsloan.mit.edu/LearningEdge/operations-management/PATA/Pages/default.aspx Note – Copy link in your browser for going directly to the reading.

Pink, Daniel H.(2001, August 31) Who Has the Next Big Idea? Fast Company Magazine, Retrieved from https://www.fastcompany.com/43595/who-has-next-big-idea

How the U.S. Dept. of Labor measure productivity. (2017). U.S. Dept. of Labor, Bureau of Labor Statistics. Retrieved from http://www.bls.gov/bls/productivity.htm