Measuring the surgical ‘learning curve’: methods, variables and competency
- To describe how learning curves are measured and what procedural variables are used to establish a ‘learning curve’ (LC).
- To assess whether LCs are a valuable measure of competency.
Patients and Methods
- A review of the surgical literature pertaining to LCs was conducted using the Medline and OVID databases.
- Variables should be fully defined and when possible, patient-specific variables should be used. Trainee's prior experience and level of supervision should be quantified; the case mix and complexity should ideally be constant.
- Logistic regression may be used to control for confounding variables.
- Ideally, a learning plateau should reach a predefined/expert-derived competency level, which should be fully defined.
- When the group splitting method is used, smaller cohorts should be used in order to narrow the range of the LC.
- Simulation technology and competence-based objective assessments may be used in training and assessment in LC studies.
- Measuring the surgical LC has potential benefits for patient safety and surgical education. However, standardisation in the methods and variables used to measure LCs is required.
- Confounding variables, such as participant's prior experience, case mix, difficulty of procedures and level of supervision, should be controlled.
- Competency and expert performance should be fully defined.