Why Quality Doesn't Matter
Oops. I meant that headline to read, "Why Quality Scoring Doesn't Matter." Oops. My bad.
I've maintained a skepticism about the value of so-called "quality transparency" scores when it comes to comparing one hospital/clinic/lab/doctor to another. My queasiness is mostly related to the problems of measurement and sample selection: Won't the toughest cases get routed to the best doctors and facilities? And if so, won't that be reflected in higher mortality rates relative to those who take the more mainstream cases? Yeah, I know about acuity adjustments, etc., but when it comes to life and death situations, I'd rather rely on the professional opinion of someone I trust -- say, the family doctor I've had for the last ten years -- than rely on my own reading of a spreadsheet with unknown risk adjustment tweekage criteria.
The Flying Fickle Finger of Fate
And further, I see the "foam finger" reduction of even those impressive tables and charts into marketing one-liners: "We're Number One! (with an asterisk)." (So if your comparing trauma units, do you look for "Number One with a Bullet?")
Now Matthew Holt points out another, perhaps more compelling, weakness: The numbers themselves aren't significant. As in "statistically significant."
It turns out that only for CABGs (coronary artery bypass grafts) are there enough cases performed to have statistical confidence that a hospital has that poor a record compared to the national average.
Holt cites a presentation by Joe Newhouse of Harvard Medical School, who pulls data from a 2004 JAMA article by Dimick, et al.
Adder Up
Okay, so if we've known these statistics are crap for three-going-on-four years, what's all the fuss about using these quality numbers to drive policy, even revenue? Holt suggests that even bad numbers can lead to improvements, sort of like college linebackers comparing Basket Weaving grades.
I'm not so sure. If I were a hospital administrator, I'd want to bank my paycheck on a more reliable team...











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