The first step toward strengthening financial resiliency, according to Adams, is maximizing the efficiency of an existing workforce by embracing the advanced technology that’s available in the market. He adds that Nordic often finds that health care organizations are underutilizing existing technology, even that which is already implemented.
“Existing EMRs and other revenue cycle software applications may support automation that is not being used. Advancements and new automations may be included with each upgrade, but taking advantage of the new functionality requires intention and focus,” Adams says. “The first step is to drive efficiency by optimizing the technology tools that are already in place.”
Maximizing existing tools is important, but Seefeld observes that many EMRs and practice management systems lack the capacity to collect data that can help health care organizations get in front of the workforce and workflow efficiency issues. “We believe that if you can measure people and understand all the touches and actions that go into collecting medical claims after a service has been rendered, you can start to diagnose the ‘why.’ And that’s really important, right?” Seefeld says. “With these deeper insights, I know where in the process all the humans are getting involved, and therefore I can start to figure out ways to automate work and reduce manual effort.”
Seefeld says the missing piece from most systems is human-generated data. Health care organizations are adopting AI and automation in the revenue cycle but only applying it to common data sets, such as those which show a claim status or denial. “Without visibility into data related to workforce effectiveness, financial leaders have no way of measuring the quality and number of staff touchpoints as they engage with claims.”
Michigan-based Compass Health, an independent multispecialty medical group with nearly a dozen ambulatory locations, recently deployed an infrastructure that would support applying automation and AI to both common claims data and human-generated data with notable results. The organization was able to reduce its administrative staff needs by two full-time employees and realize a total increase in accounts receivable of greater than $1.2 million. According to Sandra Holdorf, revenue cycle manager for Compass Health’s central billing office, other key improvements include a reduction in cases with denials by 18% over a six-month period and total denied reimbursement by 28%, an increase in charges by 34% (> $5.4 million) and payments by 4%, and an increase in net collection rate by 1.3%.
“Getting the insights into issues like denials for authorizations, or why payment processing was taking longer than expected, was a nuisance,” Holdorf recalls. “We couldn’t get the information we needed in a way that would make some of the underlying causes of issues clear. Our [existing] system was fine for clinical stuff, but for back-end billing, it proved inadequate for our needs.”
Holdorf says they can now more easily manage data from multiple practice locations, stay ahead of health plan changes—especially those related to prior authorizations—automate workflows and gain insights into staff productivity.
Compass Health’s success goes back to the principles of total actions to outcome, Seefeld emphasizes. “If you have claims that have already been worked two times, five times, 10 times, they have probably been touched by multiple staff resources and most of those touches were wasted effort,” he says. “All that back and forth is costing money, and it’s eating away at your margin. In today’s financial climate, provider organizations need to ask: Can we afford to have a lot of erroneous touches going on in medical claims? No, we can’t.”
Adams notes that automation promises to improve multiple areas of the revenue cycle. For example, many organizations are turning to advanced technology to automate highly manual back-office billing and payment processes. The key is designing and deploying these solutions correctly and having strong ongoing governance processes in place.
Any highly repeatable or predictable process in the revenue cycle is ripe for automation, Adams adds. For example, many health systems have applied automation to the clearest opportunity areas such as claims submission, claim status, or payment posting to improve efficiency.
“Revenue cycle leaders are now looking for ways to automate more complex front-end processes including eligibility, benefits, and authorization,” Adams notes. “These areas are harder because third-party payers are involved. A willing partner is required on the other end.”
Financial clearance solutions exist, according to Seefeld, that can automate the preregistration process—covering all the steps a health care organization should take prior to a patient encounter. The purpose is twofold: to ensure the patients are aware and accountable for any balance owed (past, present, or future), and that all the necessary information is collected and verified up front to help ensure claims are not denied and reimbursement is timely.
Improving price transparency and helping patients understand balances owed through effective financial clearance strategies can support patient-centered revenue cycle designs. Adams points out that there’s also a lot of the focus on intuitive technology to support “self-service and delighting the patient by making it easy to complete a task.” He recommends a book—Designing for Health—by Craig Joseph, MD, Nordic’s chief medical officer, as a good starting point for patient-centered design.
“I really like the concept of designing processes in health care that are just simple and intuitive, ignoring the complexities happening in the background,” Adams says.
“AI in the revenue cycle has received more recent attention, going beyond automation, but there haven’t been as many proven applications yet,” Adams suggests. “We are starting to see some interesting applications in the coding and clinical documentation spaces with solutions that can help speed coding activities and improve documentation by providing recommendations to coders, CDI staff, and clinicians,” he says.