Artificial intelligence can pay major dividends when it comes to managing back-office billing efforts, but the key to maximizing payments with it lies in knowing exactly where to build in coaching and automation.
That was the big takeaway Tuesday from a webinar on AI’s ability to transform revenue cycle management (RCM) for nursing homes, which are often saddled with extensive prior authorization submissions and claims denials. That makes enhancing collections an area ripe for technology-enabled improvements.
“As anyone who’s worked on the RCM side of the business knows, this is a high, high touch part of your operations and it’s, for the most part, relatively inefficient,” said Kevin Scalia, executive vice president of corporate development for Netsmart. “How do we strategically think about: How do we apply these new tools to your business to get the biggest bang for the buck? How do we try and identify things to simplify workflows and make it easier on your staff so we’re not burning them out, as billing gets more complicated?”
Erica Gregory, Netsmart’s senior vice president and general manager of RCM, said her company looked back to the beginning of the cycle when it first aimed to automate some billing functions about five years ago. Today, Netsmart’s RCM platform includes robotic process automation, large language models and chat bots that help clients at some 3,200 facilities.
The goal, the speakers said, is to have those tools serve to coach users, not for them to be used as crutches.
Because an estimated 80% of denials stem from pre-billing activities, Gregory said, her team first took a look at credentialing and payer communication processes to find smart ways to intervene.
“Our key challenges are at the beginning of the process and are leading us to some bad data elements,” she said. “Where are denials or those bottlenecks that are preventing a first-pass pay rate, where are they coming from?”
It’s often tied to data intake, coding errors or eligibility and authorization issues. This was one of the areas Netsmart said its clients were most interested in addressing.
To help determine eligibility and define how billing and payments should flow, Netsmart created key automations and “augmented” intelligence around scheduling eligibility checks for a building’s patient population. They also put in place automatic rules using an engine that could identify conflicts, such as if a bill were being submitted to the wrong payer first. And a pre-claims submission validation also caught opportunities to spot problematic claims.
“I’d much rather have that opportunity to fix the claim before it goes on file, as opposed waiting my standard adjudication timeline of 14 to 20 days and then having it come back as a denial and having to touch it again,” Gregory said.
On the authorization side, Gregory’s team wanted to reduce small tasks that were repeated too often, and data-entry was an easy target. The company added a library and a rules engine that guide its employees through care treatment plans and align them with data needed to support that.
Because that process is still manual, often through fax, Netsmart tagged in a partner to submit using an efax, a web portal or through an EDI clearinghouse, if an option. That means staff don’t have to do that task, nor do they have to run status reports with the addition of another tool.
Across all of its automation efforts, Netsmart said it had created enough productivity savings to equal the output of 72 full-time employees.
Some in the audience questioned how AI would be received by workers who see it as undermining their decision-making or threatening their jobs. But Gregory insisted automation that cuts down on data entry, better directs workflow the first time and allows staff to spend more time making bigger decisions ultimately should be seen as a plus.
“We really look at automation as having a threefold benefit,” Gregory said. “It really is about how we look at optimizing outcomes, how we simplify the reimbursement and the data related to that reimbursement, and how we empower our staff to do what they’ve been trained for their whole career and what they’re really good at.”
