Revenue cycle management (RCM), long a staple function of hospital and health system operations, has been undergoing a thorough transformation of late, evolving forward through advancing iterations of such methods as business process automation (BPA)—also known as robotic process automation (RPA), which have been successfully incorporated into core RCM processes around managing all claims processes—and into new territory. That new territory encompasses the emergence of the leveraging of machine learning- and artificial intelligence (AI)-based technologies to achieve what is being called predictive denials management. Essentially, this involves the development of algorithms based on data analytics, that can trigger interventions based on anticipated insurance claims denials.
That evolution was the subject of one of the Ten Transformative Trends that the editors at Healthcare Innovation examined in the publication’s March/April issue. In an article entitled “The New Revenue Cycle Management,” Healthcare Innovation Editor-in-Chief Mark Hagland interviewed a variety of industry leaders regarding the rapid advances taking place now in revenue cycle management, which has become an absolutely critical function for hospitals, medical groups, and health systems, as their leaders attempt to weather the financial storm that has come in the past year with the emergence of the COVID-19 pandemic in the United States, and its impact on patient care organizations nationwide.
Among the industry experts whom Hagland interviewed for that Trend article were Paymon Farazi, chief product officer at the Eden Prairie, Minn.-based Optum, a data analytics company, and Doug Hires, COO of Optum’s provider market segment. Below are excerpts from the interview that Hagland conducted with them in February.
Please tell me about your respective roles in this operational area in healthcare.
Doug Hires: I have operational responsibility for our managed services and for our Optum provider services. Paymon is part of the product and engineering division.
Paymon Farazi: I lead product for Optum Insight. Insight is one of our three business platforms.
What is the leading edge right now in RCM innovation, from your points of view?
Farazi: The way I think about the bleeding edge of rev cycle automation is that there are a couple of ways you can go down the path. How you can automatically map process flows and codify them into applications. That’s an area of a lot of investment and energy these days. The other is auto-decision-ing or auto repair of claims errors and issues. You can build an algorithm to predict what the repair should be—a simple or fancy model. Or you can share payer logic with the provider to know when they’ll reject the claim. The goal is removing human touchpoints on a claim.
In other words, the difference in levels here is between the already-established forms of business process automation, and the more leading-edge phenomenon of predictive denials management, then, correct?
Farazi: Yes, that’s right.
So predictive denials management remains fairly early along in healthcare?
Hires: I think that that’s largely true, and I think of BPA in terms of robotic process automation, RPA, those types of things. That’s actually an extension of what we build into some software products in terms of daily function—trying to take some still-manual processes and repeat those manual processes at amazingly rapid cycles, and 24/7/365, to execute on the entire claims adjudication process. That is probably more mature across the industry, though innovators are advancing very directly to the components involving complex decision-making and analysis, anticipating and forecasting denial patterns—that’s the essence of predictive denials management.
Farazi: I would agree. The business process services element is fairly far along; and simply building if/then rules into the claims process, is one thing,” he says. “What’s more complicated is when you build in payer rules. You go to a provider and you ask them, ‘How do you deny claims?’ And either that payer shares proactively with the provider, or your team at the provider organization builds out machine-learning techniques to game out situations. And that last type of activity is the leading edge, and is a huge leap.
Hires: Claims processing and submission—the edit process that Paymon was talking about just now, and the automation, are largely automated across providers, so that’s almost a table-stakes kind of thing. Now, the degree of complexity among vendor platforms may change. The intelligence component, the third one, we’ll find, is not very prevalent at all—maybe some of the more sophisticated and large healthcare delivery systems are using analytics themselves, but it’s not necessarily yet an automated component running as part of the daily system,” Hires says. “So it ends up being surveillance, intervention and correction, in cycles. So you can identify, for instance, a bulk of claims based on a denial code that you get, and then start doing data searches to try to find them, and then remediate.”
Farazi: In fact, there’s a mirror-image process on the payer side. The payer is probably a little bit further ahead in terms of using advanced techniques to generate denials. But the bleeding edge is to share the outcome of that with the provider.
So you’re saying that payers would like to share that with providers?
Farazi: Well, we’re working on that. Some of the more forward-looking ones are beginning to do so.
Will a digital divide appear in this area as well, between hospitals and health systems that are well-resourced, and those that aren’t?
Hires: I think that you’ve probably accurately described what would happen if everyone were left on their own. Because the smaller, rural community hospitals certainly don’t have those assets. They’ll be looking for a vendor partner to create this for them in their current environment or as an additional solution. But that won’t be the only element here. While many health systems think they can build their own solutions, also recognize the tremendous amount of capital and maintenance for complex systems, and very few will venture down this path on their own. They might be hopeful and looking to do this on their own. There are some very leading-edge health systems out there, often they’re academics. And they’re used to research and development and are typically pretty well-funded, so they have the assets. But when the core business of health systems is delivering healthcare, they’re going to want to acquire systems rather than having to build it out themselves. So I think it becomes something where they’ll hope that the industry will meet them with innovation.
What do you see as the timeframe around these developments?
Farazi: I would think you’re looking at a time horizon of maybe five years. These things tend to happen pretty quickly once they get going. And I agree with Doug: they’re going to need partners to make this happen. And the faster they can acquire partners, the faster this can develop.
What should CIOs and CFOs be thinking and doing right now, given all of this?
Farazi: I would tell them to be proactive about where they think the biggest opportunities are in their organization, and lean into partnerships. I would not take a wait-and-see approach; this is going to happen faster than people realize. But if you can come prepared to a conversation, that could really accelerate time to value for them.
Hires: I think that’s right on point, Paymon. And the analysis and the evaluation of current challenges, and being able to look inside what’s happening… Because most providers have a broad set of payers, and the payers all tend to behave differently, under different contracts. It’s an incredibly non-standard world. So really understanding what’s going on inside your operation, and I’m thinking of CFOs right now, is a critical first step. Now, from an IT perspective, I think it’s also critical to understand how you’re storing your data, how you have access to your data, and how you can present your data to your organization’s stakeholders so that they can understand it. So there’s a partnership that needs to happen between the CIO and CFO, to make this happen.
Is there anything you’d like to add?
Hires: We’ve been focused here on the back-end processes of the revenue cycle; but in the middle, there’s also some significant technology and advancements that will continue. I’m thinking about the future of AI, as we look at it in our company, and how we’re applying it to the coding process.
In other words, the coding process has to become more sophisticated?
Farazi: That’s right, the front, middle, and back, are all important. And in the middle, in terms of coding, where we have robust processes in place that are NLP-based processes—the goal is to use those capabilities and tune them further, so that a medical record hits the system and a code is auto-generated, so that there’s no need for a coder to touch that claim. So developing algorithms to predict how something should be coded, but getting the payer and provider can agree on what the outcome should be. We have a pilot in process with three clients.
Hires: So to your point on horizon, while we were talking about three to five years on the one component, this one is advancing probably more near-term.
What is the front?
Farazi: The front is about patient registration, scheduling, patient payment, the patient-facing side. And that’s an area of high growth, and it’s not nearly as mature as the back or the middle. So you’re going to see a lot of activity there, as providers pursue strategies and technologies mature.