Page 59 - World Journal of Laparoscopic Surgery

The Impact of the Learning Curve in Laparoscopic Surgery

Amongst the latter that is the characteristics of the surgeon randomize until they are proficient in a technique but then once
the learning curve may depend on the manual dexterity of the convinced of its worth argue that it is too late to randomize.
individual surgeon and the background knowledge of surgical However the best way to address the problem is to have a
anatomy. The type of training the surgeon has received is also statistical description of the learning curve effect within a trial
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important as training on inanimate trainers and animal tissue and various methods can then be used. Example Bayesian
has been shown to facilitate the process of learning. The slope hierarchical model. 5
of the curve depends on the nature of the procedure and
frequency of procedures performed in specific time period. IMPLICATIONS FOR PRACTICE AND TRAINING
Many studies suggest that complication rates are inversely In the current era of evidence based medicine enthusiasm for
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proportional to the volume of the surgical workload. However laparoscopic surgery is rapidly gaining momentum. There is an
rapidity of learning is not significantly related to the surgeons immense amount of literature showing advantages of minimal
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age, size of practice or hospital setting. Another important access surgery and acceptance by the public. The learning
factor that affects the learning curve is the supporting surgical curve for many procedures has been documented. 18,19,20 As far
team. A recent observational study 14 to investigate the as training is concerned, the introduction of laparoscopic
incidence of technical equipment problems during laparoscopic techniques in surgery led to many unnecessary complications.
procedures reported that in 87% of procedures one or more This led to the development of skills laboratories involving use
incidents with technical equipment or instruments occurred. of box trainers with either innate or animal tissues but lacks
Hence improvement and standardization of equipment combined objective assessment of skill acquisition. Virtual reality
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with incorporation of check lists to be used before surgery has simulators have the ability to teach psychomotor skills. However
been recommended.
it is a training tool and needs to be thoughtfully introduced into
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STATISTICAL EVALUATION OF LEARNING CURVES the surgical training curriculum. A recent prospective
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randomized controlled trial showed that virtual simulator
Various statistical methods have been reported in the assess- combined with inanimate box training leads to better
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ment of the learning curve. Commonly data are split into laparoscopic skill acquisition. An interesting finding reported
arbitrary groups and the means compared by chi-squared test is that in skills training every task should be repeated atleast 30
or ANOVA. Some studies had data displayed graphically with to 35 times for maximum benefit. The distribution of training
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no statistical analysis. Others used univariate analysis of over several days has also been shown to be superior to training
experience versus outcome. Some studies used multivariate in one day. Other factors enhancing training are fellowship
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analysis techniques such as logistic regression and multiple programmer, or playing video games. One can also obtain
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regression to adjust for confounding factors. A systematic feedback for improvement of training program. In one such
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review concluded that the statistical methods used for study the deficiency factors identified were lack of knowledge,
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assessing learning curves have been crude and the reporting lack of synchronized movement of the non dominant hand and
of studies poor. Recognizing that better methods may be easy physical fatigue. Incorporation of intensive, well planned
developed in other non clinical fields where learning curves are invitro training into the curriculum were made and the programme
present (psychology and manufacturing ) a systematic search reassessed.
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was made of the non clinical literature to identify novel
statistical methods for modeling learning curves. A number of WHAT ARE THE LIMITATIONS OR PITFALLS ?
techniques were identified including generalized estimating
equations and multilevel models. The main recommendation “Steep” learning curves are usually used to describe procedures
was that given the hierarchical nature of the learning curve data that are difficult to learn – however this is a misnomer as it
and the need to adjust for covariant, hierarchical statistical implies that large gains in proficiency are achieved over a small
models should be used. number of cases. Instead the curve for a procedure that requires
a lot of cases to reach proficiency should be described as
“flattened”. 29
EFFECT OF LEARNING CURVE As long as no valid scoring system concerning the
ON RANDOMIZED CONTROLLED TRIALS
complexity of a surgical intervention exists, the learning curve
The learning curve can cause difficulties in the interpretation of cannot be used as benchmarks to compare different surgeons
RCTs by distorting comparisons. The usual approaches to or clinics as legitimate instruments to rank surgeons or different
designing trials of new surgical techniques has been either to hospitals.
provide intensive training and supervision or require Limitations of long learning curves, facilities for training,
participating surgeons to perform a fixed number of procedures mistakes of pioneers, surgical techniques not being described
prior to participation in a trial. Surgeons have been reluctant to in books are some of the limitations described. 30

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