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.

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.

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.
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.)
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?


 

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