INTRODUCTION: A robust system for classifying the technical complexity of surgical procedures has many applications, including optimization of hospital and surgeon-level surgical performance evaluations, reimbursement, and hospital resource utilization. However, little work has been done to distinguish surgical complexity from patient- and disease-associated surgical risk. METHODS: Through a scoping review of the literature, we identified surgical subspecialty complexity classification systems which were purposed to quantify the technical complexity of a procedure and were validated with prospective or retrospective patient data. RESULTS: We identified six validated surgical complexity classification systems and determined the methodology which most accurately determines surgical complexity is the level of training or expertise necessary to perform a procedure as determined by expert consensus. However, the existing literature largely validates complexity classification systems by their ability to predict morbidity and mortality which are measures of surgical risk. CONCLUSIONS: A surgical complexity classification system distinct from, but used in parallel with, surgical risk has significant potential for process improvement. While the technical demands of a surgical procedure may be associated with measures of surgical risk, we propose that surgical complexity is a process measure, best represented in the literature by the level of training/expertise necessary to perform a procedure as determined through expert consensus.