Data Overload
Despite my long and vocal opposition to the gathering in data in schools, to the use of standardized tests to generate data that is in turn used for everything from judging students tons of it every day in my classroom-- in fact, one of my criticisms of many reformer data programs is they involve far too little data. On top of that, you need to collect good data (the Big Standardized Tests generate crappy data) and you need to run it through something that produces useful, legitimate analysis (not something like the opaque, crappy VAM models).
Twin pregnancies are considered high risk, and when the twins share one placenta there's a risk of something called Twin-Twin Transfusion Syndrome (if you are pregnant with twins, I recommend the advice of one of our doctors which was "Whatever you do, don't look this up on the internet")-- all of that put together gets you a ticket to a veritable testapalooza. Ultrasound after ultrasound, with measurements and pictures; my wife's uterus was more thoroughly explored than the surface of the moon after the first telescope.
Measurements indicated a difference in size of 21%, and protocol called for anything over 20% to trigger a new series of tests, even though none of our doctors thought any of these tests would discover anything important. One wonky heart measurement triggered a trip to Children's Hospital in Pittsburgh (where we took the grape elevator to the Hippo Ward) for some super-ultrasound; he confirmed what everyone already said, which is that there was nothing to care about. We had our regular doctors at home and a specialist in Erie watching over us. And all of our doctors agreed on one thing-- if you use all of the equipment available to modern medicine to gather tons and tons of data, you will manage to capture little human variations that will alarm you a lot and actually mean very little.
Part of the problem is that the protocols aren't really complex enough. It's like a protocol that says CURMUDGUCATION: Data Overload: