TEN TRANSFORMATIVE TRENDS 2021 The New Revenue Cycle Management
After years of work to automate manual processes, provider organizations are edging towards leveraging machine learning and AI to turbocharge their revenue cycle management processes By Mark Hagland
T
he leaders of U.S. patient care organizations, whose incomes were dramatically fragilized by the shut- down of nearly all elective medical pro- cedures during the first and second quar- ters of 2020, as the Centers for Medicare and Medicaid Services (CMS) worked to protect clinicians, staff members, and patients from infection during the early months of the COVID-19 pandemic, have been working their way back to finan- cial stability since then. And it is in that context that revenue cycle management (RCM) has once again come into focus as a tool critical to ensuring viable operating margins for hospitals, medical groups, and health systems nationwide. The good news? After decades of the advancing evolution of core RCM opera- tions through such methods as business process automation (BPA)—also known as robotic process automation (RPA), which have been successfully incorpo- rated into core RCM processes around managing all claims processes—a new phenomenon is emerging that could prove very helpful: the leveraging of
had largely been manual work, since pay- ers pushed all the administrative activity onto portals,” says Jeffrey Porter, vice president of revenue cycle and chief rev- enue cycle officer at the 40-plus-facility, Pittsburgh-based UPMC health system. But within the next two years, Porter says, he and his team will be develop- ing machine learning-based algorithms to support the denials management and claims management work of their team. Paymon Farazi, chief product officer
at the Eden Prairie, Minn.-based Optum, a data analytics company, agrees. “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 compli- cated is when you build in payer rules. You go to a payer 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. That last type of activity is the leading edge, and is a huge leap.”
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.”
Meanwhile, says Farazi, “There’s
“What’s more complicated is when you build in payer rules. You go to a payer 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. That last type of activity is the leading edge, and is a huge leap.” —Paymon Farazi
machine learning- and artificial intelli- gence (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 inter- ventions based on anticipated insurance claims denials. “We’ve spent more than a decade using BPA/RPA technologies to automate what
The percentage of patient care orga- nizations even in the early stages of leveraging machine learning and AI tools to fuel predictive analytics in this way is still tiny, says Farazi’s colleague Doug Hires, who is COO of Optum’s provider market segment. “The intel- ligence component, we’ll find, is not very prevalent at all—maybe some of the more sophisticated and large healthcare
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.” Only a few health plans have done so to date, he notes; but that doesn’t mean that more won’t be doing so in the near future. Looking at the broader picture around
all of this, “It’s really about efficiency,” says James McHugh, managing direc- tor of revenue cycle consulting at the Naperville, Ill.-based Impact Advisors consulting firm. “Revenue cycle is all about workforce efficiency now; the rev- enue cycle is an assembly line. Now, you have these great EHRs [electronic health records] in place; but even then, with all that you can do with those systems, it’s still about leveraging the system you have. And COVID has accelerated the workforce management piece, includ- ing driving efficiency and the work-by- exception process. And I don’t think
continued on page 29 MARCH/APRIL 2021 |
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