Institution: University of Utah, Department of Anesthesiology Faculty Mentors: Derek Sakata, MD and Joseph Falk Background: Many hard-working and intelligent researchers seek to define, understand, and optimize operating... [ view full abstract ]
Institution: University of Utah, Department of Anesthesiology
Faculty Mentors: Derek Sakata, MD and Joseph Falk
Background: Many hard-working and intelligent researchers seek to define, understand, and optimize operating room (OR) metrics. The many factors at play have been well characterized. They include operating room fixed and variable costs, surgeon preferences, protocols for how operating rooms are scheduled, and human variables, such as scheduling and managing human resources. Our institution faces the same challenges with OR optimization as has been elsewhere defined. We have several different OR theaters, each of which has their own challenges; some with the “empty” syndrome, consisting of underutilized resources struggling to fill available OR time and others with the “overfilled” syndrome, consisting of many surgeries extending beyond regular hours and the perception that more rooms are needed. Our purpose was initially borne out of a conflict that arose between our OR coordinator and surgeons when trying to move OR cases around to perceivably increase OR efficiency. The desire was to try and quantify the effects of moving an OR case from one room to another to enable the coordinator to say, for example, “if we move this case from X to Y, then the cost savings would be Z, or another fill-in-the-blank negotiating tool. Hence, we set out to create a software tool that could integrate existing cost data and interface with the OR schedule in real-time to allow a scheduler or coordinator the ability to prospectively understand the effects of how they particularly schedule cases, to not only improve the key metrics of cost saving, but to also be more equipped to answer questions that inevitably arise during the process.
Methods: Using a prototype version of our software tool, we retroactively used our software to quantify cost savings, utilization percent changes, as well as the burden of schedule change to surgeons as we analyzed what we determined to be a typical month at one of our ambulatory surgical centers. This analysis also served the purpose of us testing and refining our software tool. Using the software, we moved cases around to increase utilization being defined as OR time used in comparison to time available. We also moved cases from block times if block time was utilized less than 25%.
Results: Utilization improved from 53.1% to 87.9% and cost savings per change ranged from $300-2000, with the average being above $500. Surprisingly, the burden to surgeons for schedule change was minimal.
Conclusions: In this application of the software and subsequent shorter analyses, the substantial benefit to optimally moving cases around is obvious. We realize it a bit idealistic to suggest this tool can always be perfectly applied. We do, however, feel that this tool can be highly valuable to schedulers, surgeons and staff by providing data as to how each moving case not only affects one room, but the entire OR, as well, and may help provide buy-in power for surgical members who may traditionally opposed to having fluid OR scheduling.
