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Tracking Operative Experience and Competency of Plastic Surgery Trainees Using a Novel Protocol-Based Software Platform
Steven M. Sultan MD, Katie E. Weichman MD, Oren M. Tepper MD, Evan S. Garfein MD
Background:
Surgical education is built on an apprenticeship model. As it stands today, training in almost any surgical subspecialty involves observing a set of required operative procedures. It is assumed on the basis of this mandated exposure that a resident is competent to independently perform the procedures that they have observed. Given the various restrictions placed upon trainees’ workload and the significant curtailing of their operative independence this assumption is often incorrect. To better assess operative competency we have designed a novel software platform that tracks meaningful participation in all index cases in plastic surgery.
Methods:
The Accreditation Council for Graduate Medical Education’s operative minimums criteria for plastic surgery was used as a guide to create a set of protocols for index operations. The protocols were then loaded onto a proprietary software platform (Sigma Surgical, New York, NY) that allows them to be accessed in the operating room. The steps for each procedure are displayed throughout on either a web-based platform or via a user interface designed by a third-party (Stryker, Inc., Kalamazoo MI). The software is used to record who completed each step in the procedure and how long each step took to complete. The records are compiled in longitudinal fashion by individual residents and serve as enhanced case-logs. The logs are then reviewed on a bi-yearly basis and used to identify individual strengths, weaknesses and deficits in exposure.
Results:
The first phase of this educational initiative has focused on collecting data in ten of the most commonly performed procedures at our institution. To this end, the Sigma Surgical software platform has been well integrated into the workflow in the operating rooms at the hospitals in which our residents rotate. We compared the data sets generated on this new platform to traditional case-logs and found the current case-log system over-estimates the educational value of these cases for some residents. Data collection is ongoing as more protocols are added continually to the platform.
Conclusions:
Comparing traditional case logs to the enhanced logs generated by the Sigma Surgical platform has demonstrated that traditional logs may overestimate the preparedness of residents to perform all aspects of a given procedure. Dividing the cases into level-appropriate steps will ensure that residents meet requisite technical milestones and graduate capable of independently performing all steps of index operations in a timely fashion. We believe that this model can be applied easily to other Plastic Surgery programs and other surgical specialties as well.