Channeling bias occurs when a patient's prognosis or degree of illness influences which group he or she is put into in a study. It's a particular problem in nonrandomized medical trials, ones in which doctors select which patients are going to receive the drug or surgical procedure that's going to be evaluated.
It's not hard to figure out why it happens, because physicians, after all, generally want to help the people that they treat, and are trained to weigh the risks versus the rewards for a treatment.
Let's look at a hypothetical example of a study intended to evaluate the effectiveness of a certain surgical procedure on the hand. Surgeons might be more inclined to pick younger, healthier patients to get the operation, because they have lower risks of complications afterward, and more of a need to have full hand function.
In turn, they might be less likely to perform it on older patients who face higher post-operative risks and don't need to have the same degree of hand function because they're no longer working. If researchers aren't careful, the group that gets the surgery in the study will consist of younger patients, and the group that doesn't will be mostly older ones. That could produce a very different result than if the two groups were otherwise identical [source: Pannucci and Wilkins].