Objective Measurement of the Learning Curve in Live Laparoscopic Surgery: A Scoping Review of Methods

Abstract

Objective This scoping review aims to provide an overview of the methodology used when defining the learning curve (LC) in live laparoscopic surgery. Design This review was performed in line with the Preferred Reporting Items for Systematic Reviews and Meta Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. English-language articles were included systematically using Boolean operators for search string combinations. Selected studies were qualitatively analyzed for LC measurement methodology, including statistical approaches. Additional analysis was undertaken by grouping LC metrics into intrinsic, surrogate, and outcome-based. Setting Only original publications in the English language were included. No date restrictions were applied. Eligible studies were those that measured LC in laparoscopic cases (i.e., not simulation studies) regardless of their surgical specialty. Robotic-assisted laparoscopic operations were also included. Articles analyzing non-laparoscopic procedures were not included. Results A total of 87 articles were extracted for review. The majority (45/87) were conducted within general surgery alongside gynecology, vascular, pediatrics, and urology. A total of 50 studies analyzed the LC for a new technology or novel technique. Multiple metrics were used to quantify LC, with the most common being operative time ( n = 75), followed by complications ( n = 31). Only 3 studies exclusively used intrinsic performance measures for LC analysis. There was significant heterogeneity in the statistical analysis and description of LC. The majority of studies (51/87) grouped cases temporally. Nineteen studies used a Cumulative Sum (CUSUM) statistical analysis. Conclusions Measurement of the LC in live laparoscopic surgery has significant potential for training and appraisal of new techniques. Currently, the time-intensive nature of LC measurement limits its widespread adoption. However, newer techniques used alongside real-time measurement of metrics within the OR may overcome this. Future work should focus on identifying metrics that can be transferred between procedures to allow comparability and standardized statistical analysis.