In the latest podcast episode from Bloomberg’s Vanguards of Health Care series, Machinify CEO, David Pierre, sat down with Bloomberg’s Senior Equity Research Analyst and Team Leader, Jonathan Palmer, to discuss what’s on the horizon for Machinify, AI in healthcare, and payment integrity in general.
To get a preview of what Jonathan and David covered, continue reading. But, if you’re interested in listening to the episode, check it out here.
Payment Integrity Overview
Jonathan: Maybe just for the way people in our audience—or I’m thinking maybe my mother—are going to listen to this, can you dive a little deeper into what each one of those categories is (referring to the companies that came together as the new Machinify), whether it’s payment integrity or the claims processing?
David: Just a little bit about payment integrity—it’s really the processes, the systems, and strategies that are really working together to ensure accurate and appropriate payments. So, when a healthcare claim comes in from a provider, it goes through a clearinghouse, which is basically a way to get that claim over to a payer, [we’re] being more proactive about it. We’re actually looking at it before that payment.
So, you hear a lot in the industry about retrospective claims analysis versus prospective. We’re actually looking at that claim, trying to determine if it’s appropriate, if it’s price appropriate, that there’s that the right codes are present, and then ultimately determining if it should be paid and how much should be paid. What we do is really ensure that the providers get paid appropriately at the onset, and then that consumers are ultimately paying their portion appropriately, and that our clients, which are payers, are paying the right amount for the services rendered.
You can think about it from a number of different [angles]. The first being, is the right payer actually responsible? So, our clients will look at it, and then, a lot of times, there’s primary or secondary coverage for a member, and this benefits the consumer at the end of the day because you’re ensuring that the right coverage is applied from a number of insurers.
If you think about someone who may have been in an auto accident, for instance, we have a ton of algorithms, machine learning, and then our subject matter experts, which could be attorneys, they could be analysts, they could be clinical specialists, they’re actually looking at the claim and determining, should the health insurance be the primary payer on this or should it be their auto carrier? Perhaps, if it’s an auto accident, that the member is involved in, and ensuring that, ultimately, those coverages are documented appropriately, and then ultimately pay their responsibility to save the consumer dollars at the end of the day and ultimately get the provider paid appropriately. And then our customers obviously are ensuring that they’re paying their portion where appropriate.
Mitigating Technical Debt
Jonathan: My understanding is that the landscape is really filled with a lot of [technical] debt on the part of a lot of different players in the ecosystem. Is that the right way to think about it? That we’re bringing [payment integrity] into the modern era?
David: Yeah, exactly. There is a tremendous amount of debt. And if you think of some of our clients, the struggle that they’ve had on the payer side is they have a tremendous amount of legacy technology that has a lot of [technical] debt associated with it.
And if you could think about the claims adjudication systems, they are actually going through, taking the claim, making sure some basic edits on it, making sure that it comes out of it with the correct price to pay, and the estimation benefits that then goes back to the provider. A lot of those systems are 10, 15, 20 years old. A lot of them are on-premise technologies.
What we have is pure cloud technology that then sits on top of those systems and is able to get to the claim before even those adjudication systems come into play. So ultimately, we’re saving the amount of back and forth between payers and providers.
When you think about our technology, we’re viewed as more of a secondary adjudication system. So, we’re able to price it in milliseconds, able to look at the claim through our technology and determine, “should we pay this claim or not?”
And our clients are actually pushing that up against their core adjudication system and saying, “This may not be our adjudication system, but we’re able to look at this and determine if there are any errors that would keep this claim from being paid appropriately. Should we go back and take a further look at this?” And that really helps our clients who are on the clock. You know, they have 30 days to get claims paid. The ability to do this in milliseconds, versus having individuals look at it and legacy technology really makes a huge difference in controlling costs within the system but then ensuring accuracy as well.
Get the Whole Scoop
Jonathan continues by digging into the Machinify products, exploring the reasoning behind the acquisition, David’s background, and more.
Be sure to listen to the full episode to get the whole scoop.
