[mskar]

I work in data at https://www.carrumhealth.com/, and I've been parsing this data for weeks. The transparency prices allow us to meaningfully negotiate with providers, and make tangible, incremental progress toward cheaper health care. Providers and existing insurance carriers leverage information asymmetry to control the market otherwise.

For context, we bundle the 100's of itemized costs into a single, static bill per surgery type. In doing so, we've built a custom virtual-network with the most efficient surgeons. These surgeons are able to meet the volume and quality requirements to allow for lower margins. We're able to get negotiated rates that are 10-40% cheaper than traditional insurance contracts when we have data that we trust.

Unfortunately, this data alone isn't enough to properly determine prices because organizations will spread costs across procedure and billing codes that often occur in aggregate groups. For example, in a joint replacement surgery, some organizations may dump the cost into the billing for the implant itself, while others may put it under the procedure code. You have to gather billing data en masse to see which charges occur together, then combine this pricing data to determine what costs will actually look like for someone experiencing a procedure.

It's a nightmare!

[riskable]

How much do you think it costs to maintain all these negotiated contracts VS just having a single payer system with the same price for all procedures?

[mskar]

It's very expensive, carriers have an economic incentive to simplify it and this is still where they end up. There are a long tail of provider circumstances that the single-payer model will need to figure out. Some examples:

* Small hospitals in low-density, underserved areas have to make up for underutilized equipment and personnel costs. They raise prices on unrelated, common procedures to break even (This is very common)

* CMS (medicare/medicaid) sets a low price for a procedure that's overly common in a particular facility, now that facility loses money for each occurrence. They choose other procedures to raise the price to try to break even.

* Larger hospitals have higher administrative and operations costs (for things like training and research) that benefit society, but need to be averaged out across all procedure costs. This differs from hospital to hospital.

* Smaller professional facilities or physicians groups (like Ambulatory Surgery Centers) have much lower administrative costs and a smaller staff, so they have lower overhead per procedure. They are designed to be efficient, and can handle lower prices. However if there are any major complications, they won't be able to service the patient, and have to send to a hospital. This then pushes all the highest-cost, ICU-type procedures into hospitals, where there is already a higher overhead, causing hospitals to need separate pricing to cover more complex patients.

A large single payer price set will probably force efficiencies into the healthcare system. It'll be great for folk's costs, but we may see many facilities close, and lines of care will be consolidated into specialty centers. (more travel to get imaging, procedures, or to see a specialist)

[narrator]

What do you think about how Kaiser has handled the whole thing? The insurance company employing the doctors and just paying them a standard salary seems to create all the right incentives.

[thewebcount]

My experience in talking to people with chronic conditions that aren’t easily treatable is that Kaiser’s model works great until anything that’s slightly out of the ordinary happens, and then it falls apart. If you’re a zebra (as in “when you hear hooves, think horses, not zebras”), their model is pretty horrible.

[narrator]

The best thing about Kaiser, IMHO, is there is never a surprise out-of-network astronomical charge on the bill as I've seen with regular insurance.

[dnissley]

Isn't it pretty bad to be a zebra in general though? Certainly there isn't any place where zebras have it better than horses.

[sgent]

Yes but if you're at Kaiser in San Francisco and have a zebra there may only be one doc (or a small group) at UCSF that can treat your zebra, and they are not in the Kaiser network, so you go to Los Angles where Kaiser's specialist is, get treated by a lesser doc with a virtual visit assist from LA, or pay cash out of network.

[savanaly]

I think their point is that it's relatively better under another system, not that it's amazing there.

[Kinrany]

Have insurance split into two parts, the 95% cases and the rare and expensive?

[CogitoCogito]

Sounds like they have intelligently optimized for the common case.

[ecommerceguy]

>>* CMS (medicare/medicaid) sets a low price for a procedure that's overly common in a particular facility, now that facility loses money for each occurrence. They choose other procedures to raise the price to try to break even.

This is precisely why most Doctors I speak with are abhorrently against a single payer system.

[vineyardmike]

Most doctors I talk to vaguely run around the answer before mumbling that a huge way to cut costs (which will surely happen) is to cut doctors salaries.

Source: once engaged to a doctor who had doctor friends and doctor parents/family.

[gzer0]

And there is a reason why we shouldn't go off of anecdotal evidence. It's blatantly false.

Doctors’ salaries account for only about 8% of U.S. healthcare costs. A 40% cut in these salaries would reduce healthcare spending by only about 3% [1][2].

Doctor salaries are not a huge way to cut costs. If anything this would make the problem worse.

[1] https://www.latimes.com/opinion/story/2021-09-14/dont-blame-...

[2] https://pnhp.org/news/doctors-salaries-are-not-the-big-cost/

[vineyardmike]

It’s not false that doctors worry that. Doctors worry that single payer system will reduce their salaries. They’re an easy political target. They’re rich and (in this hypothetical case) their salary would come from the taxpayers. Taxpayers don’t like expensive salaries.

It’s irrelevant how much of the budget it is. It’s about perception and power. If you try to cut soap in the operating room or other supplies, you’ll look bad for endangering the patient. If you try to cut procedures you’ll look bad. If you try to cut doctor salaries, those “overpaid” doctors look bad for complaining.

Doctors have a reputation in america for being extremely well paid. If you tel people making $60k a year that their tax bill for medical costs could be lower if you reduce it by taking $50k from a doctor making $500k (taxpayer dollars!) they’ll support that. Even if it’s not a big amount.

Reducing healthcare spending 3% without any systemic change in medical treatments or equipment or negotiation with pharmaceutical companies is a huge and easy win.

[hayst4ck]

PBS put out a documentary ages ago comparing America to other countries. At the time our administrative overhead was 25% while Taiwan's overhead was 2%.

[tiahura]

Not much.

The net cost of insurance represents 6.4% of all healthcare spending.

https://www.ama-assn.org/delivering-care/patient-support-adv...

[didgetmaster]

Is the data unique or has it been duplicated for multiple formats? In other words is there a CSV file right alongside a Json file and an XML file that contains the exact same data, just in different formats?

Is the data partitioned at all (e.g. by state) so that you can just download the data for California without downloading all the data; loading it into a huge database table; and then querying it (e.g. SELECT * from <table> WHERE state = 'California')?

[mskar]

There is some duplication, where different networks under the same carrier could benefit from normalization, but in-general duplication isn't the primary issue.

The data is partitioned for some carriers at the network level, but unless that carrier has networks that are unique to a given state it's difficult to partition by location.

The majority of the data is lumped into very large, single JSON (not newline delimited), so an initial parsing step is required to break out substructures for parallel processing via warehousing technologies. I think Aetna has a 300Gb compressed (single) json file.

After breaking the json to a single array entry per provider/network, parsing is still a bit tricky because there are some very "hot" keys. Some provider array entries may only have 1000 code and cost entries, others may have 100k. We've seen array entries >50Mb for a single provider/network/carrier.

[drak0n1c]

Sounds like an application for ML, to determine which codes frequently coincide per-patient at each provider and then assign those groupings to cross-provider "Treatment XYZ" buckets to enable apples-to-apples comparisons.

[heliodor]

I would think a basic statistical analysis should suffice.

[ejb999]

most software billed as having 'ML' capabilities is just basic statistical analysis anyway - but that doesn't make for good marketing-speak.

[mskar]

Great call, many orgs in health tech use billing/procedure code embeddings to group, just like you're suggesting.

[hugh-avherald]

Calculating a basic median for those groups would be a non-trivial (indeed, probably quite difficult) exercise at this scale.

[dekhn]

Applying ML to health care is a guaranteed path to wealth, and later, insanity.

[rendaw]

How do you get info on bills for historic procedures? Do patients opt in, or will the hospitals provide that information as part of their cooperation with insurers?