Healthcare claims wars: Is AI poised to finally give providers the advantage?

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Defined as "the capability of a machine to imitate intelligent human behavior," artificial intelligence (AI) sounds a lot like science fiction. And to some in healthcare, it sounds like something that will nuke their job from orbit. Others simply aren't ready to trust this new technology.

These fears are certainly understandable. But could they be misplaced? Let's take a look at the promises of AI for a health system's revenue cycle, how it works and why it is poised to be a game-changer for employee retention and productivity.

AI vs. automation: What's the difference?
The best way to understand what AI is and what it does is to compare it to something we already know and understand: automation. Automation involves following pre-established rules. It works best for a series of repeating tasks. It does not "think" or make decisions; it only follows directions.

One example of automation is a program that filters emails in your inbox and moves them to different folders based on the sender. An automated program is a simple tool that can save you a lot of time. But it has limitations. For instance, it can't read an email you received and autonomously draft a custom response.

On the other hand, an AI program could generate its own responses. With its ability to "think" for itself, it could compose a reply based on specific information it picks up in the received email, calibrating the tone and writing style as needed.

In short, that's the difference between AI and automation: AI can "think" and take action autonomously – not unlike cute science fiction movie droids.

So, if AI can truly "think," what could it do today to fix or alleviate some of the most pressing revenue cycle management problems for health systems?

The Dark Side of denial management

Denials have plagued the revenue cycle for years, and the problem is only getting worse. In a recent survey sponsored by Experian, nearly one-third of healthcare executives said that denials increased between 10% and 15% in 2022. Seventy-two percent said that reducing denials is their highest priority, and 78% said they are likely to replace their existing claims management system with new technology.

Could AI help? If so, how?

First, AI software can predict the chance of a denial ahead of time and respond accordingly. It can proactively flag claims at high risk of denial or evaluate claims in real time to identify preventable denials before submission. This would include real-time monitoring of payments, alerting us to payer changes as they occur and saving us a lot of stress later on.

Second, while prevention goes a long way to decrease denials, the truth is that some denials will sneak through like a rogue team at the villain's start base. In those cases, health systems can use AI to prioritize which denials to focus on for revenue collection purposes.

A case in point? High-dollar denials. At first glance, the denials with the highest value might seem like the obvious place to focus. Higher dollars equal higher recovered revenue, right? Not necessarily. Claims with high-dollar amounts attached to them do not always mean that health systems will collect those amounts. In fact, each claim has a variety of factors that influence the likelihood of collection.

A more cost-effective way of choosing which claims to focus on would be to calculate the probability that a denial will be overturned – and the expected revenue if the overturn is successful. This would also be measured against the staff time it could take to recover it. Then the right denials could be automatically routed to the right specialists based on the direct impact to the health system's bottom line.

We should also consider the ever-shifting sands of payer rules, codes and policies that lead to denials. In complying with the No Surprises Act, which mandates that patients receive a good faith estimate for services before they are performed, companies will have to stay vigilant to avoid costly rework. Fortunately, with its real-time monitoring capabilities, AI will likely prove as invaluable as a trusty laser sword when it comes to fending off denials.

Resubmissions: May the AI be with you

Manually submitting claims is a tedious, often arduous process that can feel like falling into a black hole: There's no escape, and it takes forever. Maybe that's why 65% of denied claims are never resubmitted.¹

But with an AI solution that monitors changes in payers' payment patterns and models a provider's historical payment data to their rework and appeal success trends, companies can gain a lot more information about where to put their staff's time and energy.

If staff knew which resubmitted claims would produce higher yields, they could reduce time spent on low-value denials that don't make economic sense to resubmit. (Remember, the high-dollar claims are often not the most profitable.)

A remedy for burnout?

Judging from a recent Bain report, it's safe to say that employee stress and turnover have become major problems in the wake of the COVID-19 pandemic.² Not only are 25% of U.S. clinicians contemplating a career change primarily due to burnout, but the report also states that "40% of all clinicians surveyed say they don't have the resources they need . . . [and] they report a lack of effective processes and workflows . . ."

In fact, a whopping 50% to 70% of clinicians say they've never used automated technologies for workflow management. Think of all that time, energy and attention drained by completing tedious manual processes that could have been focused on patients. In addition, automation can help boost staff morale and combat burnout.

AI: friend or foe?

So, is artificial intelligence here to stay? Will it snatch up our jobs, or will it simply make our current jobs easier?

While the fears surrounding AI and the displacement of jobs are certainly understandable, they are also misplaced. The truth is that the tasks suited for AI are the same ones currently causing burnout in staff. Those menial tasks should have been eliminated years ago. With practical applications for AI such as real-time monitoring of payer payments and helping health systems determine which claim denials to focus on, everybody wins.

The verdict seems clear: AI is here to stay, and those who adopt it will see major benefits. That's a victory any rebel crew could be proud of.

References

1. Reiner, G. August 29, 2018. Success in proactive denials management and prevention. Healthcare Financial Management Association (HFMA). https://www.hfma.org/revenue-cycle/denials-management/61778/.
2. Ney, E., Brookshire, M. and Weisbrod, J. October 11, 2022. A treatment for America's healthcare worker burnout. Bain & Company. https://www.bain.com/insights/a-treatment-for-americas-healthcare-worker-burnout/.

About the Author:

Clarissa Riggins, Chief Product Officer, Experian Health