Generating Operative Workflows for Vestibular Schwannoma Resection: A Two-Stage Delphi's Consensus in Collaboration with the British Skull Base Society. Part 1: The Retrosigmoid Approach.

Objective  An operative workflow systematically compartmentalizes operations into hierarchal components of phases, steps, instrument, technique errors, and event errors. Operative workflow provides a foundation for education, training, and understanding of surgical variation. In this Part 1, we present a codified operative workflow for the retrosigmoid approach to vestibular schwannoma resection. Methods  A mixed-method consensus process of literature review, small-group Delphi's consensus, followed by a national Delphi's consensus, was performed in collaboration with British Skull Base Society (BSBS). Each Delphi's round was repeated until data saturation and over 90% consensus was reached. Results  Eighteen consultant skull base surgeons (10 neurosurgeons and 8 ENT [ear, nose, and throat]) with median 17.9 years of experience (interquartile range: 17.5 years) of independent practice participated. There was a 100% response rate across both Delphi's rounds. The operative workflow for the retrosigmoid approach contained three phases and 40 unique steps as follows: phase 1, approach and exposure; phase 2, tumor debulking and excision; phase 3, closure. For the retrosigmoid approach, technique, and event error for each operative step was also described. Conclusion  We present Part 1 of a national, multicenter, consensus-derived, codified operative workflow for the retrosigmoid approach to vestibular schwannomas that encompasses phases, steps, instruments, technique errors, and event errors. The codified retrosigmoid approach presented in this manuscript can serve as foundational research for future work, such as operative workflow analysis or neurosurgical simulation and education.
Competing Interests: Conflict of Interest J.C. receives research grants and consultancy fees from Medtronic (Dublin, Ireland). J.C. is the associate medical director of CMR surgical (Cambridge, United Kingdom). D.S. is a shareholder in Odin Vision Ltd. (London, United Kingdom) and is an employee of Digital Surgery (London, United Kingdom). H.L.H., H.J.M., C.H.K., and W.M. are supported by the Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London. D.Z.K. is supported by an National Institute for Health and Care Research (NIHR) Academic Clinical Fellowship. H.J.M. is also funded by the NIHR Biomedical Research Centre at University College London. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or nonfinancial interest (such as personal or professional relationships, affiliations, knowledge, or beliefs) in the subject matter or materials discussed in this manuscript.
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