Characterizing individual trainee learning curves in surgical training: Challenges and opportunities

• Published in: The surgeon (Edinburgh) 2023-10, Vol.21 (5), p.285-288
• Main Authors: Toale, C., O'Byrne, A., Morris, M., Kavanagh, D.O.
• Format: Article
• Language: English
• Subjects: Assessment; Competency-based education; Learning curves; Performance of procedures; Residency education; Surgery
• ISSN: 1479-666X; 2405-5840
• DOI: 10.1016/j.surge.2022.11.003

The surgical learning curve is an observable and measurable phenomenon. In the era of competency-based approaches to surgical training, monitoring the trajectory of individual trainee competence attainment could represent a meaningful method of formative and summative assessment. While technology can assist this approach, a number of significant barriers to the implementation of such assessment methods remain, including: accurate data collection, standard setting, and reliable assessment. Translating individual learning curve data into quantifiable case minimum targets in training poses further difficulties, and may not be possible for all procedures, particularly those that are less frequently performed and assessed. In spite of these challenges, significant benefits could be realized through an individualized approach to competency assessment using trainee learning curve data. Tracking competence acquisition against criterion-referenced standards could allow for targeted training and remediation, conforming with modern theories of adult education and empowering trainees to take control of their own learning. Learning curve data could also be used to assess the effects of educational interventions such as simulation-based training on subsequent competence acquisition rates. Ultimately, the individual learning curves of trainees could be used to inform personalised decisions regarding entrustment, credentialing, and certification, allowing training programmes to move beyond minimum operative experience targets as a crude proxy measure of competence.