There are countless stories of fraudsters using AI to social engineer or directly defraud companies. Feels obvious that AI can be used to harden systems/defenses. I just don't see that much of it.
Put together a deep dive into healthcare price transparency, the patient registration and eligibility process, how it's broken, and how it leads to providers not getting fairly compensated, and drives higher costs for all healthcare.
Covers:
- how our current tools fail providers and patients
- how payors benefit from the status quo and have no incentive to fix it systemically
- how providers can provide price transparency to patients (mostly in outpatient settings)
- other things providers can do to improve their processes & technology
If you're trying to improve your patient registration process, provide price transparency to patients, or building patient collections infrastructure, this is for you. Feedback is super welcome
I mean it is going to be so good to watch. you couldn't write a conspiracy theory this good.
I do think that other than for the censorship resistance use case, this was always going to be inevitable for whatever the reserve currency was. It was only a matter of time.
(Also makes me think a gold backed stable is inevitable on some time horizon)
I think on this basis most banks in the us are functionally insolvent.
Not defending SVB - just calling out that the dynamics that make svb insolvent (400bp rate rise in a couple years after a spike in deposits with lots of deployment in fixed income securities) are essentially true for all banks in the us.
What do you mean insurance agent? The process of picking health insurance in the US doesn't utilize agents.
> And also because after a plan is selected, copays and deductibles are essentially fixed so consumer would have no need to price shop.
This assumes that the service you're picking costs more than the deductible. If the service you're shopping for costs less than your deductible, you're paying for all of it up front...
> API endpoints that provide clean, abstracted negotiated rates data could be a great infrastructural product for both traditional providers and digital health companies.
Cascade Health (who I've been working with) have this API on the roadmap
>Patients that I've interviewed generally want a completely abstracted process - send or upload a picture of their bill and their insurance, and then hand it off. This would be similar to the cushion.ai experience.
Mixed on this. I think a way to select your insurance and know what you'd pay out of pocket, and to compare your out of pocket costs between multiple providers, is SUPER valuable. By the time you have a bill, you already owe money. Before the visit, you actually have a shot at making a decision that costs you less.
> Employers on the other hand want to ensure that they aren't being overcharged by their current stack. They are always looking for solutions for reducing costs and better understanding the drivers of those costs, which tools like springbuk.com address.
Cascade is also doing this.
> I have less familiarity with the provider side, but the cost of maintaining an insurance billing program has always seemed manual and inefficient.
Have a writeup coming about this one actually. I believe there's room for "Contract Streaming" which allows you to use the published data to a) ingest your contracted rates with every payor and b)know in advance what the out of network rates are for any payor, so you can tell a patient in advance exactly what their visit will cost them before they walk out the door. (There's also a bunch of other benefits around forecasting and stuff, but this is the start).
With
1. A way to choose your plan
2. A way to see all providers in network with that plan
3. A way to see contract rates
4. A way to estimate your out of pocket costs (copay plus deductible) if you go for a specific service
So your point on items covered by insurers is right with the caveat that way more patients are now on high deductible plans, so your out of pocket cost still gets impacted by the contract rates even if the provider is in network.
Agree on electives - there’s something to do there price wise but it’s not the most straightforward.
Re: pricing in general, it def matters in the decision but how you present it makes a huge difference. For uninsured people our flu map has actually been super critical (people are more likely to choose an option with a price at all and marginally more likely to choose a lower priced option (the price spreads are lower bc it’s a simple procedure but there are some places where you can pay over $100 for a flu shot - no one chooses those once they know)
The nit here is you have to give a person the ability to a) select their insurance, and b) show them the full out of pocket cost (copay + deductible) and then it makes a difference, which favors a logged in experience (like solv or Zocdoc) over a logged out experience. But I’m convinced that the reason it’s hard to see today is not because people don’t care about price. It’s because they don’t get to price discriminate at all.
Thanks for this color. I have a ton of thoughts about this. . . A few:
1. The best way I think we can enable patients/consumers to price discriminate is about pushing pricing into the moment when they're making a decision. An example of how to do this is: https://carbonhealth.com/flu/flu-vaccination-centers . .. we created a map, that indexes well, for where to find the lowest cost flu shot (this was done before the price transparency data was available, but I fully intend to a) incorporate the price transparency data for our existing maps and b) create new health maps for basically every service that tells you the relative rate for your plan
2. There's going to be real demand for an API that returns pricing data, for marketplaces that aggregate patients (like Solv, Zocdoc, Sesamecare, healthgrades etc) because pricing is probably the most in-demand decision driver that no one has.
3. Ultimately, I expect Google and Apple to incorporate these prices into maps. Then you'll see it have a real impact on consumer behavior, because most healthcare journeys (whether we like it or not) start with a search.
While I think you should make pricing available for everything (bc after all, there is a price for everything) I think it's most effective to start with diagnostics (mammograms, xrays, STD tests etc) because there's pretty low variance in outcomes (ie it kinda doesn't matter where you get them, you're getting the same thing). When it comes to complex therapeutic searches (eg oncology, chronic care) while pricing is one dimension, patients probably want to see pricing along with a proxy for quality (eg that specialists quality metrics, number of times the MD has done that procedure, etc), bc the healing process for those are not linearly related to price, and the cost of a visit is just a fraction of going down the wrong therapeutic pathway, for both the patient and the system.
Thank you. Lots of directions this could go - right now focusing on making it easy to get access to the data. Later we’ll figure out useful ways to interact with it.
Good thought - were planning to do some aggregation but there’s actually literally too much data to be holistic, so we’re going to do it on a few large plans and go from there