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

Kelly Jiang, Carly Weber-Levine, Nicholas Theodore

Year
2024
Citations
1

Abstract

To the Editor: We thank Smith et al for their recognition of our work and the insights their commentary provides on adopting robotics in spine surgery.1,2 A number of surgeons have documented the initiation of a robotic program at their institution, demonstrating favorable outcomes in accuracy and decreasing operative times.3,4 However, as Smith et al note, the majority of learning curve literature focuses on the first few cases when challenges with the technological setup and workflow inefficiencies significantly affect operative time. To date, the learning curve literature has largely reflected the startup investment required to integrate the new technology. As robot use in spine surgery becomes increasingly common, the relevant learning curve will no longer focus on the initial phase of integrating a new robotic device into the operative workflow. It will instead shift toward reflecting the training of a surgeon to operate with existing robotic technology. The true learning curves for operative time and patient outcomes are likely shorter than what has been reported in the literature, with the advantages of robotic surgery even greater than what is currently recognized. This idea is supported by existing literature that demonstrates shorter learning curves for trainees when there is another surgeon experienced with robot use at their institution.5 As robotic platforms may enhance the performance of less experienced trainees to produce increasingly comparable outcomes with that of senior surgeons, the adoption of robotics in spine surgery may lead to the achievement of better patient outcomes and shorter operative times earlier in a surgeon's career.

Keywords

Learning curveRoboticsWorkflowMedicineArtificial intelligenceRobotic surgeryRobotSurgeryMedical physicsComputer science

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