How payers can use integrated data and better analytics to improve claims reimbursement and quality of care

Jared Lorinsky is chief strategy officer at Burlington, Mass.-based HealthEdge. He's been working in the payer reimbursement and payment integrity sphere for around two decades and sat down with Becker's to discuss how payers can use new technology and innovations to improve the quality of patient care through better integrated data, claims reimbursement processing and advanced analytics.

Mr. Lorinsky exclusively works on Source, a cloud-based platform that offers payers improved efficiencies, real-time analytics and regulatory updates in the areas of claims reimbursement, payment integrity and contract modeling.

Question: What do you believe is currently wrong with traditional payment integrity practices?

Jared Lorinsky: I think the whole concept of payment integrity and trying to identify savings as a result of things not being done right the first time, is really the flaw in the system. We exclusively work with health plans of all sizes across the country. We didn't build a platform for payment integrity, we just built the platform to pay claims accurately. A large percentage of the issues that payment integrity programs need to find are things that need better processes upfront. If done correctly, the amount of problems a payment integrity program is tasked with finding dwindles substantially. 

On the growth topic with payment integrity, it's almost a never-ending river of problems you can find. There's a big inclusion of AI into that process to try and detect things we as an industry haven't really been able to determine through more complex patterns and data analysis and mining. Those things are helpful, but I also challenge the status quo and say, why can't we just do the AI upfront and have a feedback loop that continues to move more toward the point of service so that everything is still less retrospective? Not even just prospective, but more upfront in real time so that we can move closer to the point of service. We're not there yet as an industry, but I think those are the things we're looking out for in the future that we want to be a part of.

Q: Are there specific technologies you think payers should be investing in to help address these issues?

JL: You always want to look out for solutions that are really being built to address not just the problems of today, but with a look for the future. More and more we're seeing requests for proposals and conversations around cloud-based, software as a service solutions that integrate disparate datasets. Integration has been a big challenge in the industry, and looking out for solutions that are flexible to integrate with any type of technology and are also working in the cloud. The goal is to do this as fast as possible, as efficiently as possible, but are also using these cloud-based technologies to be more efficient and to be more scalable.

When you're talking about a 30 million-member health plan, you have to be able to scale to the volume if they need 20 million claims a day processed — you've got to be able to meet that demand. If I'm a payer, I'd be looking for solutions with that design set and that are not using, to put it bluntly, 20- to 30-year-old source code that they're just trying to update. That's still a big problem in the industry, and there's sometimes not the incentive to innovate, so we prefer to work with our contemporaries in the industry that are doing just that.

Q: How can payer's internal claims processing teams incorporate AI-enabled analytics to get more claims correct?

JL: I would say the industry is still experimenting with that in my opinion, but the technology is there. You have people saying they're doing this. With any type of automation, whether it's AI or not, you have to work with a technology to say, this is what I'm doing today. How do I teach artificial intelligence to do this and to do it better and to catch things before it even gets to these people having to do this work. Oftentimes, a lot of it is manual reviews, rework and things that can be accomplished through basic process automation. But it's also being able to be smart enough to identify things before they ever become a problem, and I think that's where AI is pretty compelling. But again, you have to start with those most basic use cases first and then continue to scale the AI to be able to become smarter over time. We're all better than we were five years ago, but I think we're still in the adolescent phase.

Q: How do trends in payment integrity differ from when you first started your career to now?

JL: Back then is still kind of as it is today: it's pay and chase, though we have gotten a lot better.  The actual definition of payment integrity is to pay a claim accurately. But in the healthcare industry, I think our version of it has become recovery. If you go back to 10 to 15 years ago, it was all about recovery. We've done a great job of not making it all about recovery, but it still is a lot about recovery. The challenges are that you don't want to overpay and create waste, but at the same time, you don't want to create a lot of member and provider abrasion.

The whole point is that if there's an issue, let's find it upfront before you go through that process. I think that kind of legacy pay-and-chase model was very prevalent when we talk about payment integrity. That's why there's a lot of those companies out there in the payment integrity world where their whole business wasn't built on technology, it was built on pay and chase. I think over time, this transition to technology has been great. Today, you hear things like going from post-payment recovery to prepayment recovery, and I think that's a good step. But again, find it half a second after the claim comes in the door.

Q: What regulatory challenges in the payment integrity sphere do you foresee coming down the pipeline? 

JL: There's always regulatory challenges and things change daily, so it's impossible in many cases for everyone to keep up with the changes — a problem in and of itself. There's always new things being mandated like prompt payrolls, where it does put a lot of pressure on the payer to pay things in a timely manner. For example, if I have 26 days to pay the claim, I have to get it out the door even if I'm not done checking it. That puts pressure on them to go just pay the claim and figure it out later. Again, pay and chase. I think that's why more and more payers are coming to technology providers like us and saying they need a digital transformation to actually meet the regulatory requirements and pressures and to remain competitive in the markets they serve, because some health plans are ahead. Some are not at that level yet of leveraging technology to make the process more efficient.

Q: What does the future of payment integrity then look like in your eyes?

JL: In regard to prompt pay, I think the window to pay claims is going to shorten and the amount of transparency you need on the payments is going to continue to increase. There's big transparency initiatives going on right now, so it's not only that you have to pay things quickly and accurately, but you have to have more rationale and defensibility about what you're doing. That's solved through technology and workflow. We're seeing a lot of health plans come through and say we need to take a new look at our ecosystem. 

Q: How does integrated data specifically help to achieve better care outcomes in the long run?

JL: If you don't have integrated data and the ability to analyze it efficiently, you're always going to be behind. That means you're reacting to the problems you find, not staying ahead and assessing performance along the way, whether it's your quality of care, the quality of your relationship with the provider and the quality you get for the dollars that are available. Integrated data allows you to bring together care and the patient's information, feedback from members themselves, various types of clinical datasets and claims data. You're analyzing outcomes, but you're also modeling new outcomes. That's how you can achieve higher value. It's not just being reactive, learning from your outcomes and being more efficient about that — it's also understanding what may happen in the future based on the patterns of the data. That gets back to the technology conversation around cloud-based technologies that are very integratable with each other. That way, when the health plan is taking a look at how to reinvent their technology ecosystem, if they have those similar services together, it's very easy to integrate them and it's very easy to create data visualization. Without that, you see a lot of what's gone on over the last five to 10 years where there are value-based quality of care initiatives, but they're pretty much going through the processes and analyzing it after it happens and trying to improve for the next year, instead of improving in real time — which is what the technology should be enabling you to do. If there's a quality gap, understand it today, not in six months.

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