I think I agree with you. There's a lot of messiness with using ^U and often I'm sure that this approximation leads to decision errors in many real cases. I'd also agree that better approximations of ^U would be costly and are often not worth the effort.
Similar to how there's a term for "Expected value of perfect information", there could be an equivalent for the expected value of a utility function, even outside of uncertainty of parameterized that were thought to be included. Really, there could be calculations for "expected benefit from improvements to a model", though of course this would be difficult to parameterize (how would you declare that a model has been changed a lot vs. a little? If I introduce 2 new parameters, but these parameters aren't that important, then how big of a deal should this be considered in expectation?)