I'm afraid most people here criticizing her normal distribution remarks are oversimplifying it much more than her.
If on the other hand she is saying that a problem in healthcare is that significantly different sub-populations are lumped together resulting in inappropriate benchmarks for some sub-populations, that is more palatable. Even if this latter interpretation is not true, at least it isn't false by definition.
The problem with the claim lies in the attempt to associate a strictly technical concept (the normal distribution) to $GENERIC_BAD_STUFF with nothing more than vague wordplay.
Also, just FYI, you have it the other way around. When you sample from a population, you (usually) assume a certain distribution (at most you infer parameters). For example, if you're sampling for opinion polls, you would actually want to oversample minorities and then correct back.