Measuring the surgical ‘learning curve’: methods, variables and competency

Authors

  • Nuzhath Khan,

    1. MRC Centre for Transplantation, King's College London, King's Health Partners, Department of Urology, Guy's Hospital, London, UK
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  • Hamid Abboudi,

    1. MRC Centre for Transplantation, King's College London, King's Health Partners, Department of Urology, Guy's Hospital, London, UK
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  • Mohammed Shamim Khan,

    1. MRC Centre for Transplantation, King's College London, King's Health Partners, Department of Urology, Guy's Hospital, London, UK
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  • Prokar Dasgupta,

    1. MRC Centre for Transplantation, King's College London, King's Health Partners, Department of Urology, Guy's Hospital, London, UK
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  • Kamran Ahmed

    Corresponding author
    1. MRC Centre for Transplantation, King's College London, King's Health Partners, Department of Urology, Guy's Hospital, London, UK
    • Correspondence: Kamran Ahmed, MRC Centre for Transplantation, King's College London, Guy's Hospital, St Thomas Street, London SE1 9RT, UK.

      e-mail: k.ahmed@imperial.ac.uk

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Abstract

Objectives

  • 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.

Results

  • 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.

Conclusions

  • 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.

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