There’s been no shortage of enthusiasm for the potential of AI when it comes to healthcare processes such as clinical diagnosis and – particularly at this moment – tracking and predicting the trajectory of diseases such as COVID-19. But for healthcare administrators, it may be the most useful role for AI will be helping them grapple with the complexities of revenue cycle management.
“There was a study done that estimated about $470 billion was spent on billing and insurance-related activities. The reason for that was there's an obscene amount of work that goes into getting a claim billed and then collecting on that claim,” said Ross Moore, MBA, general manager of revenue cycle at Olive, a health IT company that uses AI to automate provider workflows, in a recent article at RevCycleIntelligence. “Those manual, redundant tasks that are taking place in patient access, coding, billing, collections, and denials, those tasks themselves that are performed by the revenue cycle departments can actually be automated using AI.”
The bottom line is, notes the article, is that “AI deals really well with high transaction environments in which there are codified rules – like the healthcare revenue cycle.”
Specifically, revenue cycle contains “an abundance of tagged data,” which means values are attached to data points to indicate specific events, like why a claim was denied or attributes of a patient’s diagnosis.
“Whether it's matching a patient with the right provider, estimating out-of-pocket costs, or coding the claim, those are things that have long lists of variables associated with them, and AI is pretty uniquely good at evaluating those variables and coming up with an ever-improving success rate of getting to the right outcome against any of those process steps,” explained Joe Polaris, SVP of product and technology at R1 RCM, a revenue cycle management vendor.
The reason AI is better suited to tasks like this is that, unlike technology such as robotic process automation, AI imitates intelligent human behavior through algorithms that find patterns and plan future actions in order to produce a positive outcome.
Consequently, the article notes, “AI’s ‘intelligence’ can effectively address the most pressing revenue cycle management issues, such as prior authorizations, claim status checks, and out-of-pocket cost estimates, all while getting the information that needs human intervention to the right person at the right time.”
Given trends within the healthcare sector, then, it’s not surprising that RCM administrators are excited by AI’s potential. For example, the article cites a survey of 1,000 practicing physicians conducted by the American Medical Association (AMA) in which 86 percent of doctors described the burden of prior authorizations as high or extremely high.
“It's very, very resource-intensive on both sides, not just on the provider side. It's a series of interactions that are very transactional,” Sharlene Seidman, a vice president at Yale New Haven Health, who added that AI’s appeal is “about refining processes and then moving further ahead. Getting to more of those value-adding functions sooner so that we could focus on what's really important to us, which is our patient.”