How Digital Innovations Are Helping Revenue Cycle Management Turn a Critical Corner

There’s little doubt that healthcare’s golden age of technology has arrived, accelerated in part by COVID-19. From telehealth platforms to remote patient monitoring technologies, digital innovations allowed hospitals to pivot quickly and transition most patients to virtual care models early on in the pandemic.

The same can be said for revenue cycle management (RCM). It, too, is experiencing a digital renaissance, which comes at a fortuitous time. As hospitals resume normal operations and revive elective surgery volumes back to pre-pandemic levels, they are grappling with fewer revenue cycle staff due to cuts made before and during the pandemic. What’s more, they face stiffer competition, nationally, with increasing demand for revenue cycle staff, including billing and coding professionals, many of whom are now part of a growing remote workforce. As revenue cycle work volumes rise, many organizations cannot hire staff back because of the steep financial losses suffered during the pandemic. In a May 2021 Annals of Surgery article, researchers estimated US hospitals lost $22.3 billion at the peak of the pandemic, March through May 2020, due to canceled elective surgeries, predicting a median recovery time of one to two years.

As a result, hospitals are tapping artificial intelligence (AI), robotic process automation (RPA), bots, and other technologies to fill in gaps, drive out waste, and reduce costs across the revenue cycle by finding data anomalies and improving processes, especially in crucial friction areas such as denials management. Gartner predicts 50 percent of US healthcare providers will invest in RPA in the next three years to optimize costs and resources.

According to a literature review in JAMA, the US healthcare system wastes $265.6 billion a year on administrative complexity, including billing and coding waste. While AI and RPA can be costly, even a small investment can yield significant savings. For example, a $200,000 bot could generate a $325,000 ROI each year by processing 27,000 claims electronically submitted for a 500-bed hospital. Subsequent investments could lead to millions in savings.

Additionally, as healthcare organizations adopt these digital technologies, they are looking more strategically at redesigning revenue cycle staff roles to focus on the most important work, leaving AI and RPA to automate the repetitive tasks in the workflow.

Digital Momentum Builds

Ten years ago, the digital healthcare landscape had a much different topography. At the time, large health systems were putting significant resources into building and sending electronic health records (EHR). Next came the evolution in Excel macros, which performed basic finite functions. In the last three years, the pace of innovation has picked up more dramatically with advances in RPA and natural language processing technologies (NLP) that enable computers to take over workflows and perform multiple steps. Also, data analytics and warehousing companies are now able to aggregate and normalize high volumes of data. This has been key in supporting health system megamergers to weave together disparate data across multiple independent entities to present an accurate picture of a comprehensive system.

Creating a More Proactive Revenue Cycle with AI, RPA, and Bots

As AI, RPA, and bots continue to take root across healthcare, the revenue cycle benefits in significant ways. These technologies allow health information (HI) professionals to transition from Excel macros to RPA and NLP to perform a longer series of tasks requiring human intervention, including everything from claims status checks to requests for coordination of benefits and additional documentation.

Moreover, through AI and machine learning, staff can review 12-24 months’ worth of longitudinal patient record trending. These technologies also help to identify business trends as they are happening, allowing revenue cycle teams to make proactive decisions about healthcare records and reimbursement systems. For example, regarding business trends, AI can work in the background to spot denial issues, allowing revenue cycle teams to respond faster with nuanced solutions and to process higher work volumes in shorter periods. AI and business rule data join multiple data points in the workflow of a single denial. Whoever is working the denied claim can quickly detect pertinent facts such as reasons for the denial by viewing the claim adjustment segment (CAS) and remark codes used for every segment of the denied claim. AI and business rule joins are much more efficient than an EHR, which typically provides only the most recent CAS and remark codes.

Subsequently, RPA allows a revenue cycle manager to leverage the data provided in the CAS and remark codes and determine next steps for resolving the denied claim electronically. This is also where bots enter the workflow to perform repetitive tasks necessary to appeal or close the claim. For instance, a bot can be programmed to go to a payer website to collect the electronic claim status and then grab and attach the medical record to the claim. Or bots can be deployed to handle authorization issues that commonly result in denials. If a claim comes back missing an authorization number, the bot can look for the number, add it to the claim form, and rebill the claim. Ultimately, these advancements position HI staff to see and respond to situations that need human intervention, allowing for a higher percentage of first-pass denial resolutions.

At the same time, analytics is undergoing a visual transformation, with digital dashboards that allow revenue cycle data to tell a more compelling, visual story than the Excel spreadsheet. Colorful graphs and charts present only the most relevant, actionable information at the time it is needed. Rather than sleuthing or data mining, key insights are now surfaced to the staff member. For example, a person can quickly drill into a 12-month trend line on DRG downgrades in much greater detail.

Reimagining RCM Workflows

With the increasing availability of AI, RPA, business rule data joins, and other technologies, revenue cycle managers are better positioned to allocate human and electronic resources where they make the most sense. For instance, a task that requires several repetitive steps may be best suited for a bot. Revenue cycle teams are using bots creatively across the entire revenue cycle. On the front end, bots can acquire prior authorizations for patient access staff, an important job that can result in significant financial loss if not handled correctly. According to the Healthcare Financial Management Association (HFMA), “errors in the prior authorization phase of the revenue cycle may account for nearly 24% of all claim denials,” making this an ideal task for RPA. Bots can also handle referrals on the front end.

In mid revenue cycle, healthcare organizations are increasingly using bots in computer-assisted coding. For example, a bot can process 1 million medical records, learn the combination of data points for those records, predict results, and code appropriately. On the back end, hospitals commonly deploy bots to handle all of the tasks involved in working a backlog of time-consuming credit balances, including matching payments to the appropriate health plan.

As healthcare organizations continue to optimize the revenue cycle and reduce administrative waste, AI and RPA will become more commonplace. Generally, bots can perform repetitive and mundane tasks much faster than humans, which is highly appealing as organizations grow and revenue cycle work multiplies. On the other hand, these developments also allow organizations to home in on revenue cycle work requiring human interpretation. Soon, instead of locating medical records, staff will be trained and paid to examine the medical record and write the appeal.

AI and RPA are still fairly new technologies when it comes to the healthcare industry. Starting out can be daunting. Critical questions will come up, such as how much to invest, where to invest, and how to nurture staff through change. A strategic technology partner with revenue cycle expertise can help in all of these areas by developing a roadmap matched to your organization’s budget, specific needs, and staff experience.

Terry Blessing III is senior vice president of client development for VisiQuate.