V. Tiwari1, D. Penson1, W. Sandberg1 1Vanderbilt University Medical Center,Nashville, TN, USA
Introduction: In Academic Medical Centers, surgical specialties are allocated operating room (OR) capacity, which they in turn split among individual surgeons. Surgeons thus get the coveted access to first-case placement priority in their OR(s). This bi-level capacity disaggregation gives surgeons certainty and control over their schedules; however, it restricts access of those ORs to other surgeons, often leading to underutilization. It also makes meaningful interpretation of service-level OR utilization challenging. We developed a method to rank surgeons’ based on their use of OR time. We use the ranking to recommend to service chiefs which surgeons need more or less OR capacity.
Methods: Data Envelopment Analysis (DEA) is a non-parametric mathematical optimization technique to rank peers based on their technical efficiency in converting multiple inputs (or resources) into multiple outputs (or performance measures). DEA assigns a score between one (most efficient individual) and zero (those deemed least DEA efficient). We developed four input variables (total unique days in OR, number of days starting one OR with first-case, as well as with two ORs, and number of total first-starts), which each reflect in some manner the amount of capacity consumed by a surgeon. We developed four output measures that each reflect how well the ORs were used each day that the surgeon started OR(s) with a first case. We used 1 year of data and repeated the analysis four times, once for each quarter, to rank each of the 175 surgeons. Analysis was conducted using Microsoft MS-Excel and the open source DEA software OSDEA.
Results: Surgeons’ rank between quarters remained consistent, implying stable practice patterns, at least in the short-term. DEA finds those surgeons more technically efficient that run their ORs to much later in the day (that is, higher utilization); even if they have lower overall surgical case volumes, but consume relatively fewer resources (that is, fewer first-starts). In addition, the surgeons that start two ORs with first-cases tended to have lower DEA efficiency scores. This is because these surgeons usually had high OR utilization in just one of their ORs and finished the other OR around noon, while not producing substantially higher overall surgical case volume as compared to those surgeons that just started one OR but used it well. The method also helped identify those (usually younger faculty) surgeons that do not have an assigned OR (lower resource consumption), but often were able to get a first-case start through the released-room policy. This DEA technique thus aids in the natural selection of surgeons that should get (or lose) OR time.
Conclusion: We developed a method that objectively assists surgical service chiefs in reallocating capacity among surgeons. The technique compares an individual’s performance relative to their peers with respect to how efficiently the individual converts a set of inputs into outputs.