That’d be “3 points abaft the starboard beam”
176 karma · joined January 29, 2023
https://www.urban.org/research/publication/2021-poverty-proj...
So a minor investment in making people’s lives suck a little less has improved the rate by almost a third.
I agree with the Cato Institute that we should invest more in the safety net.
When you get an x-ray, you would expect to see 3 claims (again, simplifying).
—— One is the x-ray tech taking the picture. That gets a professional claim with a CPT code and is straightforward.
—- One is the interpretation by a radiologist of the imaging. That is a professional claim with a CPT and a modifier.
—- The last depends on the place of service. If it’s in a hospital, or at an outpatient facility, or at an ASC, then you get a facility claim to go with it.
Next, under what circumstances did the x-ray occur? Was it during an inpatient stay? If so, the payor might pay based on a DRG, which is basically a bundle of all the services that occur during the stay. How do you decide how much of the cost to allocate to the various parts of the x-ray? There are more variations on this.
Next, how are the providers contracted? Are they participating providers? Par vs non-par have different payment rates.
Next, was the service in-network or out-of-network, defined by the patient’s insurance benefits?
Does the patient’s PCP participate in a capitated arrangement (fixed fee to the PCP’s office per month)? If so, what is the allocated cost for the service based on the submitted encounter?
What about fees for network rental? Sorry, this one is esoteric, but it’s another factor.
And so forth and so on. It’s a mess.
I’m not trying to excuse the other bad behavior, but within the data itself, he’s experiencing a combination of health insurers’ incompetence, the kludged up data models they’ve had to build to represent the output of the multiple generations of claims processing systems and other administrative processes, and the general mess that provider identifiers are. Every payor calculates values differently. Every payor uses different codes (beyond the standard CMS and CPTs). Every payor has different arrangements that are difficult to represent in standard schema, eg capitation in Florida, delegation in California, or the oddness that are Taft-Hartley plan.
There is a link in the article to a discussion with CMS. Another participant in the discussion works for IQVIA, a long-time claims data aggregator (and CRO and a bunch of other things), and clearly understands what’s going on. It would be extremely difficult to do this work at all without significant experience working with multiple payors’ data, which requires time and access, and pays well once you do have that specialized experience.
Verse 1: Had a pickup truck, my favorite toy, Whiskey in console, feeling coy, Drove on dirt roads, feeling free, With a girl on the tailgate, in tight blue jeans for all to see.
Chorus: My truck left me, feeling stuck, Drinking whiskey in my blue jeans, feeling yuck, Miss the girl on the tailgate, her pretty look, Truck is gone, now I cry like a rook.
Verse 2: Fell behind on payments, lost my ride, The truck drove off, with the girl by its side, She wore tight blue jeans, hugged her curves just right, Now the truck and the girl are out of sight.
Chorus: My truck left me, feeling stuck, Drinking whiskey in my blue jeans, feeling yuck, Miss the girl on the tailgate, her pretty look, Truck is gone, now I cry like a rook.
Bridge: It was just a truck, I know, But its departure dealt a painful blow, I'll find a new ride and try to mend, But memories of the girl and the truck will never end.
Chorus: My truck left me, feeling stuck, Drinking whiskey in my blue jeans, feeling yuck, Miss the girl on the tailgate, her pretty look, Truck is gone, now I cry like a rook.
Outro: Maybe one day my truck will return, With the girl in tight blue jeans for all to yearn, Until then, I'll sip my whiskey and dream, Of the truck and the girl, a perfect team.