Using Artificial Intelligence To Advance Revenue Cycle Management

Using Artificial Intelligence To Advance Revenue Cycle ManagementArtificial intelligence (AI) is making big waves in healthcare from detecting lung cancer and gene mutations that lead to autism to addressing social determinants of health and chronic conditions. The technology is automating and optimizing clinical workflows, leading to improved outcomes, lower costs, and enhanced patient and provider satisfaction.

The critical role artificial intelligence now plays in healthcare is prompting some providers to think about how that same technology can streamline and optimize other more manual, yet critical, processes in healthcare, like the revenue cycle.

Jonathan Parisi, the director of business operations and strategy at Neurosurgeons of New Jersey, is one of those providers.

“We know there’s a lot of data that goes along with medical account receivables. But to be able to capture it all, structure it, and turn it into something meaningful and actionable is a big chore,” he recently said in an interview with RevCycleIntelligence.com. “You need to have analysts pulling a lot of data to be able to leverage the information, and that is a hurdle in and of itself. We knew our people were working, but we didn’t really know how effective they were.”

A/R management is a critical component of the revenue cycle. But the revenue cycle is still bogged down by expensive, time-consuming manual processes, the Council for Affordable Quality Healthcare (CAQH) confirmed in its 2018 Index.

“Our A/R follow-up representatives work down lists of claims segmented by a particular payer,” Parisi said regarding his specialty practice’s A/R management process. “It was early on when I started to realize that most representatives were not even getting through their own list before they had to start again at the end of the month when they ran a new aging report.”

“It was very inefficient, and we were potentially losing a lot of money in that inconsistent follow-up process. That moment impressed upon me that we needed to improve this process,” he stressed.

Coming from a strategic planning and business intelligence background, Parisi knew the practice needed technology to streamline the largely manual process that dictated the practice’s financial health.

“Fast forward to when we started working with MedEvolve and their automated workflow and analytics solutions,” Parisi said. “The analytics on the backend are turbo-charging our ability to go after A/R, and that’ll ultimately lead to us to reducing FTEs overall or transitioning staff to other positions within the organization, making us much more efficient. And it’s all because representatives are not following up on claims that are unnecessary to work, and we know that.”

Applying Artificial Intelligence To Claims, A/R Management

Claims are not going away any time soon, so practices need to develop strategies for how to effectively and quickly tackle unpaid claims. Using a solution with a criteria-based algorithm is key to automating the process for short- and long-term A/R management improvement, Parisi recently learned.

“All of that human stuff is tough to control. How a representative is going through a list, how he or she is processing an aging report, and how quickly he or she is working are all variables,” Parisi stated. “We wanted to minimize those variations in order to be more efficient, and that’s what the workflow system helps us do. It stops representatives from working on claims that don’t need to be worked because the criteria have been set up in the system.”

In the new system, Parisi and his team are able to prioritize the claims representatives go after based on specific factors, such as the value of the claim or days outstanding.

“You could be going after a high-value claim or you may be going after a lower dollar claim but that’s only because it may be at risk of some timeliness statute. However, that’s real money to us,” he explained.

Furthermore, the system takes away some of the complex decision-making on the part of the representatives and offers them a GPS for efficient A/R follow-up.

“The system is like a GPS: representatives sit down, log into MedEvolve RCM Workflow, and hit go, and the system leads them. You don’t have to do too much thinking or prioritization because the system does that for you,” he elaborated.

The practice has already observed a 15 percent drop in overall accounts receivable and general increases in cash collections per month since implementing the solution just a couple of months ago.

But Parisi anticipates realizing longer-term benefits.

The algorithm in the solution is constantly analyzing A/R follow-up data to direct future, smarter workflows. The solution is always learning what attributes of a claim will cause staff to pursue more aggressive follow-up strategies and what attributes will result in a smooth follow-up process.

In addition to smarter workflows, Parisi is able to more effectively manage the human component of the revenue cycle.

“The system demystifies what people are doing. It allows us to see how effective representatives are at follow-up by showing how many claims they’re following up on in a day or even an hour,” he said. “We can now see what’s going on. Why are we not following up on claims until after 10:00? Or, why does it drop off after 4:00? It allows you to ask questions, and conversely, it allows you to reward people for doing great work.”

Parisi plans to use greater workforce transparency to identify barriers to excellent performance and coach staff on how to elevate their workflows. Through efficient workflows, he also expects to save the practice from adding additional FTEs, which is a major win for the growing organization.

Artificial intelligence in healthcare is making significant clinical strides. But practices like Neurosurgeons of New Jersey are also demonstrating how the advanced technology can optimize the financial side of healthcare.

Automating the revenue cycle using artificial intelligence can significantly streamline and advance financial processes, allowing providers to focus on what’s at the heart of their jobs: patient care.

For More Information: https://revcycleintelligence.com/news/using-artificial-intelligence-to-advance-revenue-cycle-management

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