Letter: Learning Curves for Robot-Assisted Pedicle Screw Placement: Analysis of Operative Time for 234 Cases

摘要

To the Editor: We read with great interest the recent article by Jiang et al.1 The authors present a single-center experience discussing the learning curve for robot-assisted pedicle screw placement.1 Here, they present the results from 234 individual cases using robot-assisted technology for placement of pedicle screws. Of great interest to us, the authors focus on the learning curve for incorporating this technology into their practice. This report demonstrates a reduction in operative time of just over 44 minutes from the first case to last and an inflection point of 67 cases to reach “mastery.” The results driven discussions of the surgical learning curve for spinal robotics, like other new technologies, have been recently published.2 We believe the current work deserves particular attention because it demonstrates the continual improvement of the “expert” surgeon. Traditional studies on the surgical learning curve are heavily focused on a small number of early cases. As a result, the focus is primarily on overcoming initial barriers to adoption, including speed and safety. Given this, focus is often away from the important “right tail” of the learning curve, where speed and safety surpass the existing techniques and patient outcomes are optimized. ADOPTING ROBOTICS IN THE MODERN OPERATING ROOM As academic spine surgeons operating at teaching hospitals, we have had the pleasure of witnessing new technology enhance our ability to treat modern spine patients. In the past 4 years, both of our centers have incorporated spinal robotics into our operating rooms, with an accumulated experience of more than 200 cases. In addition to being witness to the benefits of spinal robotics, we have also witnessed the challenges of adopting this new technology. The addition of a new robotics platform to our operating rooms was initially, and not unexpectedly, disruptive. There are some pearls to mitigate this disruption. First, the surgeon must work with the OR staff, including circulators, radiology technologists, scrub techs, industry partners, and anesthesia to design new workflow patterns in the operating room. As noted in the cited work, this invariably can lead to frustrations and temporary inefficiencies. Second, as a new technology is introduced to a system, there will be glitches and unforeseen technological challenges. These will require patience for both the surgeon and surgical team alike but will resolve over time. Third, consistent utilization of the new technology will optimize workflow quicker. The entire team must be committed to incorporating the technology in as many indicated cases as possible. Waiting for the “complex” or “perfect” case will likely lead to frustrations and continued inefficiencies. We have witnessed our own learning curves with robotic technology. In our experience, most technological and workflow challenges are faced in the surgeon's first 15–20 cases. INFLECTION POINT OF ROBOTICS IN NEUROSURGERY The authors uniquely used the term “inflection point” in the learning curve. They used cumulative sum analysis to determine the point of mastery for robot-assisted surgery. This same technique has also been used in other surgical fields. Critically, although a surgeon may be competent with the technology far before this point, it is here that there are major gains in efficiency in the operation, above and beyond a previous technique or technology. Furthermore, it is quite likely that previous exposure to navigation technology, including nonrobotic navigation, will only enhance a surgeon's ability to adopt this technology quickly and safely. The fate of this technology will ultimately rest in the hands of modern trainees. Early exposure to both navigation and robot-assisted technology is vital for young surgeons to prepare for practice and quickly add robotics into their practice. This exposure can translate into a more rapid ascension to the “expert” stage of the learning curve, where advantages occur for the