SURGICAL PROCESS ANALYSIS

In October 2007, Phil was engaged by the Sir Mortimer B. Davis Jewish General Hospital, a major hospital that is affiliated with McGill University, to analyze and improve its surgical processes. Specific goals included:

• Identifying time that could be used to perform additional surgeries.

  To do so, it was necessary to determine the time left in the schedule of the nursing teams. Unfortunately, the surgical information system used to track surgeries did not track the nursing team that performed each surgery. Thus it was not directly possible to identify the time available to each surgical team to perform additional surgeries.

  To address this, Phil developed a simulation model that, using actual surgery data, assigned each surgery to surgical teams; using that simulation model he was then able to identify blocks of time large enough to perform additional surgeries.

• Determining the number of intensive care unit beds needed for surgical patients.

  Due to an insufficient number of ICU beds, the hospital had previously had to cancel numerous surgeries due to a lack of available ICU beds. To determine the number of needed ICU beds, Phil built a simulation model that experimentally measured surgery waiting times, surgery cancellations, ICU bed utilization, and ICU bed overflow, for several different bed levels. Phil's next step on this project is to try to both increase ICU utilization and decrease cancellations via improved surgical block scheduling.

• Building and using a simulation based optimization model to help plan and manage a new pre-surgical screening clinic.

For a new pre-surgical screening clinic where patients go through a semi-customized set of services, Phil built a simulation based optimization model to help minimize physician idle time, space, excessive patient waiting time, and nurse, blood taker, EKG technician, pharmacist and administrative staff overtime. In addition to the model being used for determining capacity requirements, the model also optimized patient arrival times and staff arrival, break and lunch times.
• Determining the requirements for sigmoidoscopy flexscope sterilization machines.

  To preclude long patient delays while the flexscopes were being sterilized, Phil build a simulation that determined the average and worst case delays that could be expected for different numbers of sterlilization machines.