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Introduction: American Board of Orthopaedic Surgery/American Council on GraduateMedical Education Residency Review Committee training requirements have necessitated the need for the adoption of simulation education into existing programmatic requirements. Current guidelines focus only on interns at a potentially significant cost to programs; both in total dollar amount and time. Methods: The authors aim to provide a model that can maximize utility for all resident levels, manage cost by maximizing the use of cadaveric material, and allow integration of varied industry support. Results: The Oregon Health & Science University Orthopaedic education program has developed a high-fidelity training curriculum that (1) is applicable to both junior and senior residents (2) has minimized the cost per resident with the reuse of cadaveric specimens and (3) has nurtured partnerships with industry stakeholders to reduce bias in training by collaborating with most major industry representatives. Conclusion: The simulation curriculum outlined in this manuscript may serve as a reference for other programs and institutions to develop their own residency educational curriculum models.
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OBJECTIVE: Cadaveric and dry 3D model-based simulation training is a valuable educational tool for neurosurgical residents. Such simulation training is an opportunity for residents to hone technical skills and decision-making and enhance their neuroanatomy knowledge. The authors describe the growth and development of the Oregon Health & Science University Department of Neurological Surgery resident-focused, hands-on, spine-simulation surgery courses and provide details of course evaluations, layout, and setup. METHODS: A four-part spine surgical simulation series, including two human cadaveric and two dry 3D model-based courses, was created to provide resident spine procedure training. Residents participated in the spine simulation series (2017-2021) and completed annual course curriculum and anonymous post-course evaluations. Evaluations included both Likert scale items and free-text responses. Responses to Likert scale items were analyzed in Python. Free-text responses were quantified using the Valence Aware Dictionary for Sentiment Reasoner. Descriptive statistics were calculated and plotted using Python's seaborn and matplotlib library modules. RESULTS: The analysis included 129 spine (occipitocervical, thoracolumbar, and spine model fusion I and II) simulation course evaluations. Likert responses demonstrated high average responses for evaluation questions (4.67 ± 0.90 and above). The average compound sentiment value was 0.58 ± 0.28. CONCLUSIONS: This is the first time Likert responses and sentiment analysis have been used to demonstrate how neurosurgical residents positively value a hands-on spine simulation training. Simulation is an essential component of neurosurgical resident education training. The authors encourage other neurosurgical education programs to develop and leverage spine simulation as a teaching tool.