Content area
Full Text
When learning a new procedure, performance tends to improve with experience, and graphically plotting performance against experience produces a learning curve. 1 - 5 Clinicians inexperienced in a procedure are said to be on the early phase of their learning curve with improvements expected with increasing experience. This concept applies across the full spectrum of medical specialities and procedures; however, with the advent of technically demanding minimally invasive techniques, it is surgery in particular where there are specific and potentially dramatic implications. The clinical importance of this was brought into stark relief by the General Medical Council inquiry into the Bristol Paediatric Surgical Unit, which stated that patients should not be exposed to surgeons operating during the early phase of their learning curves. 6
In this article we aim to describe the historical time line of the learning curve concept, address the common misnomer that steep learning curves are associated with difficult and complex procedures, suggest methods by which surgical learning curves may be constructed, and describe their relevance to modern medical training.
MEASURING OUTCOMES
In 1936, TP Wright, an aeronautical engineer, published the first description of a learning curve. 7 His thesis was that speed or efficiency of airplane component production increased, and cost decreased, as the experience and skill of the workforce increased. In industry, measures of performance are often obvious-for example, production time, costs, and quality control. However, it is more difficult to assess a clinicians' performance. Measures of learning related to a surgical technique fall into two categories: measures of surgical process, and measures of patient outcome. Surgical process measures include operative factors such as operative time, blood loss, and technical adequacy of resection for cancer surgery-margin involvement and lymph node yield. Patient outcomes include postoperative factors such as analgesia requirement, transfusion requirement, duration of stay in high dependency or intensive care, length of stay in hospital, morbidity rates, mortality rates, and cumulative survival. Process outcomes are generally easier to analyse and therefore more commonly used, though they are only indirectly related to patient outcomes. 1
In 1979, Luft et al 8 reported a possible relationship between volume of clinical work and outcomes, but despite other supporting studies, controversy remains regarding the importance of the complexity of the condition, the...