2058 Assessing Functional Neurosurgery Training: ACGME Case Minimums Versus Surgical Autonomy

INTRODUCTION: The Accreditation Council for Graduate Medical Education (ACGME) relies on case minimums as a standard competency indicator, set by expert opinion rather than individual resident performance. Exploring individual metrics may better tailor training needs. METHODS: Data from neurosurgery residents at Duke University on five functional procedures (deep brain stimulation (DBS), epilepsy vagal nerve stimulation (VNS), percutaneous spinal cord stimulator placement (SCS), internal pulse generator implantation (IPG), and epilepsy stereo electroencephalography (SEEG)) were analyzed. We determined the number of cases required to achieve competency for the 1st and 2nd time, with competency defined as being graded by attending surgeons at the highest autonomy level in the SAP. Results were analyzed with descriptive statistics. RESULTS: Median case volumes for achieving competency were: DBS 11, 12 (ACGME min. 10); VNS 3, 6.5 (min. 10); SCS 5, 6.5 (min. 10); IPG 3.5, 5 (min. 10); SEEG 2.5, 3.5 (min. 10). Notably, individual variance in competency levels and rate of progression was observed. CONCLUSIONS: Except for DBS, all procedures required fewer cases to reach competency than ACGME standards suggest, indicating that case complexity and learning curves vary significantly across subspecialties. A competency-based approach, recognizing individual progression, could enhance surgical training efficacy and improve assessment of resident surgical autonomy upon graduation. Future studies should explore long-term outcomes of competency-based training to validate these findings further.

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Publication Details

Journal
Neurosurgery
Published
2025-03-14
DOI
https://doi.org/10.1227/neu.0000000000003360_2058
Primary Topic
Surgical Simulation and Training
Type
article
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article

2058 Assessing Functional Neurosurgery Training: ACGME Case Minimums Versus Surgical Autonomy

Rajeev Dharmapurikar, Stephen C. Harward, Dennis A. Turner, Pranav Warman et al.
Neurosurgery
Surgical Simulation and Training
article

2058 Assessing Functional Neurosurgery Training: ACGME Case Minimums Versus Surgical Autonomy

Rajeev Dharmapurikar, Stephen C. Harward, Dennis A. Turner, Pranav Warman, Vishal Venkatraman, Derek G. Southwell, Michael M. Haglund, Katrina Hon, Alexander Suarez, MACM Shivanand P. Lad
article en

Abstract

INTRODUCTION: The Accreditation Council for Graduate Medical Education (ACGME) relies on case minimums as a standard competency indicator, set by expert opinion rather than individual resident performance. Exploring individual metrics may better tailor training needs. METHODS: Data from neurosurgery residents at Duke University on five functional procedures (deep brain stimulation (DBS), epilepsy vagal nerve stimulation (VNS), percutaneous spinal cord stimulator placement (SCS), internal pulse generator implantation (IPG), and epilepsy stereo electroencephalography (SEEG)) were analyzed. We determined the number of cases required to achieve competency for the 1st and 2nd time, with competency defined as being graded by attending surgeons at the highest autonomy level in the SAP. Results were analyzed with descriptive statistics. RESULTS: Median case volumes for achieving competency were: DBS 11, 12 (ACGME min. 10); VNS 3, 6.5 (min. 10); SCS 5, 6.5 (min. 10); IPG 3.5, 5 (min. 10); SEEG 2.5, 3.5 (min. 10). Notably, individual variance in competency levels and rate of progression was observed. CONCLUSIONS: Except for DBS, all procedures required fewer cases to reach competency than ACGME standards suggest, indicating that case complexity and learning curves vary significantly across subspecialties. A competency-based approach, recognizing individual progression, could enhance surgical training efficacy and improve assessment of resident surgical autonomy upon graduation. Future studies should explore long-term outcomes of competency-based training to validate these findings further.

NeurosurgeryVol. 71(Supplement_1)
Openalex Percentile: Top 92%
Surgical Simulation and Training
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