Revenue cycle innovation: How automation can mitigate the financial impact of COVID-19

Automation. It’s what makes innovation possible. Think of driverless cars, smart homes and continuous learning technology. The healthcare industry also uses automation to increase financial efficiency and resiliency during times of uncertainty.

We’re not talking about robotic process automation (RPA) that requires frequent reprogramming every time a payer requirement changes. We’re talking about hyper-aware artificial intelligence (AI) and machine learning (ML) that healthcare organizations deploy throughout the entire revenue cycle to decrease days in accounts receivable (A/R), reduce denials and cut labor costs.

“Automation that is grounded in AI and ML is proving crucial in truly optimizing revenue cycle processes, increasing efficiencies and lowering the cost to collect for hospitals and healthcare systems,” said Amy Raymond, head of revenue cycle operations at AKASA. “The pandemic has thrown many organizations into chaos. The consistency and optimization offered by the latest in automation innovation can help revenue cycle teams get back on track.”

Considering the benefits of automation, it’s not surprising that 66% of health systems currently use or are in the process of implementing AI- and ML-driven automation in their revenue cycle operations, according to a recent AKASA survey. The survey was conducted through HFMA’s Pulse Survey program between May 19, 2020, and June 22, 2020, and included 587 CFOs and revenue cycle leaders at hospitals and health systems nationwide.

A more recent AKASA survey conducted less than one year later found that 78% of health systems currently automate their revenue cycle or are in the process of doing so. That’s a 12% year-over-year increase. This data clearly indicates that automation is here to stay, and that revenue cycle innovation is a priority.

The revenue cycle is ripe for disruption

If there’s one thing that hospital financial leaders learned from COVID-19, it’s that innovation and organizational agility are paramount — particularly when it comes to revenue cycle operations. When the government issued stay-at-home orders, entire revenue cycle departments went remote. In addition, patient volumes fluctuated like never before, causing a ripple effect on cash flow. The American Hospital Association estimates that hospitals and health systems lost at least $323.1 billion in 2020. Some — particularly rural hospitals — never recovered. In fact, 17 rural hospitals closed during the first three quarters of 2020. According to data from the Sheps Center at the University of North Carolina at Chapel Hill, of the 20 total rural hospitals that closed in 2020, 13 were in the South. The Sheps Center defines a closed hospital as one that no longer offers inpatient services.

Healthcare organizations that did survive the financial crunch were ones that pushed forward with new workflows and technologies. Today, nearly two years into the pandemic, these organizations have continued that momentum with automation at the forefront. Seventy-five percent of organizations intend to restructure their revenue cycle operations in response to shifting dynamics driven by the pandemic, according to the 2020 AKASA survey. Automation and permanent work-from-home arrangements represent a large part of this. Hospital financial leaders know that robust automation solutions fortify their revenue cycle operations, enabling them to mitigate the impact of disruptions on staff and the bottom line.

Revenue cycle automation can mitigate the financial impact of COVID-19

When thinking about revenue cycle automation, healthcare organizations typically start with automating discrete processes. For example, nearly 61% of hospitals and health systems automate adjustment posting, according to the 2020 AKASA survey. Almost 52% automate billing edits, and 48% automate claim status. However, when deployed correctly, AI- and ML-driven automation can have a much more significant impact on the overall revenue cycle, leading to lower costs and greater revenue integrity.

Following are four ways in which hospital financial leaders can use AI- and ML-driven revenue cycle automation to lessen the economic impact of COVID-19 now and in the future.

1. Build and retain a core revenue cycle team. The last thing any hospital financial leader wants to do is hire talented revenue cycle staff only to furlough them when patient volumes decrease. Still, this was the reality for many organizations during the beginning of the pandemic. Nearly 51% of respondents to the 2020 AKASA survey said work and claim volumes became unpredictable during the pandemic. With erratic claim volumes came an inability to cover employee overhead. Nearly 36% of survey respondents said they were overstaffed due to decreases in claim volumes. Unfortunately, after furloughs and layoffs, many of these talented employees ultimately found jobs elsewhere thanks to the endless possibilities enabled by remote work.

Now, organizations are looking for ways to attract and retain top talent while being mindful of the ebbing and flowing of work demands. Automation can help. For example, it can prevent burnout associated with repetitive, mundane revenue cycle tasks. That’s because the technology handles cases it can complete with a high degree of confidence. Automation can also offset challenges associated with unexpected spikes in patient volumes. Vendors that provide a volume-based pricing model allow organizations to scale up and down as needed. Finally, it enables greater flexibility in terms of when and how people work. With automation, organizations have a set of work queues that always get done regardless of any challenges that remote staff face (e.g., connectivity issues, unanticipated time off due to COVID-19, childcare challenges and more). Forty-three percent of respondents that plan for more work-from-home use automation to support those efforts.

2. Contain labor costs. For many hospitals, labor represents a significant portion of their overall operating expenses. A mid-size health system, for example, might employ 2,500 to 3,000 people who work across the revenue cycle. AI- and ML-driven automation can take over some of the tasks that these employees perform, enabling organizations to contain labor costs better. Nebraska Methodist Health System, one of AKASA’s hospital clients, determined that revenue cycle automation could handle the work of 19 full-time employees working at optimal productivity.

“We have been impressed with the AKASA team’s expertise in revenue cycle operations,” said Jeff Francis, vice president and CFO of Nebraska Methodist Health System. “They were able to deploy Unified Automation^TM quickly, and we’ve seen the system adjust to process changes in real time. We’ve also had significant improvements in our revenue cycle operations over the past several months as our business office staff has had a greater opportunity to work at the ‘top of their license’ by focusing on more difficult claims while automation has handled claim status checks and other time-consuming tasks that are necessary but are a less strategic use of our staff’s time and talent.”

3. Redeploy talent more effectively. Through automation, organizations can shift revenue cycle staff focus so they can work on more technical denials and claims. That’s because they see fewer claims overall. The ones they do address tend to be more complex, bringing more value to their organization. They can also focus on improving the patient financial experience. When working properly, automation can help organizations elevate the nature of the work on which employees focus. They can focus on more complex roles and responsibilities that offer more challenging and dynamic positions within their organizations. Revenue cycle leaders can invest in developing more specialized and skilled teams.

4. Enhance revenue integrity. With AI- and ML-driven automation comes the ability to predict denials, automatically code claims based on a physician’s clinical notes, and more. The ability to predict — and prevent — denials is significant. As payers begin to audit claims submitted during the early days of the pandemic, some organizations have seen an increase in denials due to ever-changing payer regulations (think: telehealth and virtual care). In addition, registration staff continue to collect information from patients new to the healthcare system who simply want a COVID-19 vaccine or who are hospitalized due to COVID-19. With each new patient comes the potential for data errors and omissions. Automation and predictive denial prevention are paramount.

Looking ahead

As the current pandemic continues to unfold, the healthcare industry will likely witness the following four revenue cycle automation-related trends:

• Financial leaders will become more sophisticated in their analysis of revenue cycle automation solutions and better able to distinguish the approaches that overpromise and underdeliver from those that truly enhance revenue integrity and yield a solid return on investment (ROI).
• Healthcare organizations will expand the scope and complexity of revenue cycle tasks to automate.
• Healthcare organizations will look for solutions that are purpose-built for their use by a vendor partner that can provide an automation platform with potential applications enterprisewide.
• Healthcare organizations will pursue revenue cycle automation with more urgency and greater purpose.

“Effective revenue cycle leaders are looking ahead,” said Raymond. “How can staffing, resourcing, technology and workflows be improved? When implemented appropriately, automation should not only reduce your costs; it should increase the accuracy of the work and improve performance against your key performance indicators.”

As providers continue to navigate challenges associated with the pandemic, automation will become more integral to the revenue cycle. The question is, are healthcare organizations ready to innovate? There’s no time like the present to begin the journey toward a more efficient and effective revenue cycle.

AI-driven automation is the only automation that makes sense

There is an increasing demand for AI- and ML-based revenue cycle automation solutions that are better able to adapt to process changes, more fully automate complete functions and handle more complex tasks. However, it can be challenging to understand the nuances between these solutions and RPA. The 2020 AKASA survey found that nearly 60% of hospital financial leaders continue to mistakenly consider RPA to be a form of AI even though they are distinct and co-evolving technologies. When thinking about RPA versus AI- and ML-driven automation, it’s helpful to focus on these three differences:

1. USE CASES

RPA: Is limited to discrete tasks (think: Microsoft Excel macro) and repetitive processes that never change.

AI and ML: Can process the majority of revenue cycle management tasks, including highly complex and dynamic workflows, because it automatically observes and learns from workflows, system changes, outliers (i.e., ones that AI and ML can’t currently resolve and that require human intervention) and edge cases. For example, ML could learn to follow up with a payer on no-response claims automatically. AI- and ML-driven automation can assist with patient access tasks (e.g., eligibility, authorizations, document indexing, cost estimation and medical necessity), mid-cycle tasks (e.g., predictive claims scrubbing, inpatient and professional coding, charge reconciliation, claim edits, clinical documentation improvement queries and attachment submissions) and business office tasks (e.g., technical and clinical denial resolutions, underpayment appeals, payment posting, balance adjustments and comprehensive follow-up).

2. BUILD, INTEGRATION AND DEPLOYMENT

RPA: Can take up to 12-plus months to build and deploy an RPA bot for one discrete task that may or may not deliver the anticipated efficiencies or ROI. RPA also requires a person-heavy deployment to create and update software robots. For every $1 spent on RPA technology, an additional $3.41 is spent on consultants and support services to maintain that technology, according to a 2019 Forrester report.

AI and ML: Performs all tasks within existing systems, relies on a fully remote deployment and can often go live in less than six months once organizations provide adequate access to data.

3. RETURN ON INVESTMENT

RPA: Dwindling value due to the long onboarding process and the need for long-term maintenance.

AI and ML: Immediate and long-term value due to the system’s resilience and minimal maintenance required. AI- and ML-driven automation is robust and scalable, with the ability to expand numerous revenue cycle functions and remain resilient against procedural, technical and regulatory changes.

As hospital financial leaders consider these differences, it becomes clear that AI- and ML-driven automation drives high revenue cycle performance at a low cost. It enables uniquely proactive, predictive and non-fragile workflows not possible through other forms of automation.

Automation isn’t just for large health systems. Smaller hospitals can benefit, too.

Organizations with the highest net patient revenue are statistically more likely to have automation in their revenue cycle operations. In fact, 83% of organizations that generate more than $10 billion in NPR use revenue cycle automation, according to the 2020 AKASA survey. Only 36% of organizations that generate less than $500 million in NPR use it. These results mean there’s an opportunity for smaller hospitals to take advantage of automation to enhance revenue integrity and cash flow.

“It may be more difficult to carve out tasks for automation in smaller settings because people are often wearing a lot of different hats,” said Raymond. “So the ROI is a little more subtle. But tasks that represent portions of jobs can still be automated and help smaller health systems realize improved performance and efficiency of multitasking staff members.”

Following are six tips from Raymond that smaller hospitals and health systems should consider:

1. Smaller systems often believe they’re too small to centralize but feel it would be helpful. Automation can help with those centralizing efforts by merging your workflows.

2. Does your rev cycle staff have issues with consistency, productivity or accuracy? It may be because they’re being pulled in too many directions. Eliminating the noise by weaving in automation could help. 

3. Identify how automation can assist your specific organization. Figure out processes — regardless of how many people touch them — that can be automated. Would a task benefit from a standard, consistent approach? Is it time-consuming, with low return on value?

4. It’s often easier to start by automating small tasks and grow into larger, more complex tasks from there. Make sure that your solution provider has a road map for expanding efforts across the revenue cycle.

5. It may be hard to get buy-in for automation in smaller organizations when the current cost isn’t fully recognized because it’s being spread across departments or team members. Pull together the necessary data to show time spent on the task across all areas or staff. Then show an area that needs improvement. Define how staff could be working on this problem area instead and how it would increase revenue.

6. Once you deploy automation, work with your staff to refocus time and resources to higher-value work. Allow the automation to handle the multitude of redundant data processes that consume precious staff time.

Want to learn more about automation and what innovative healthcare leaders are focusing on right now? Download the Annual Report on Automation from AKASA at akasa.co/2Y0ZUjl.

3 key advantages of revenue cycle automation

1. Decreased days in A/R due to enhanced, AI-driven work queues

2. Fewer denials with the use of predictive analytics

3. Reduced labor costs due to effective deployment of highly skilled employees

About AKASA

AKASA is building the future of healthcare with AI. The only Unified Automation™ company for healthcare, AKASA uses the same machine learning approaches that made driverless cars possible to provide health systems with a single solution for automating revenue cycle operations. AKASA’s unique expert-in-the-loop approach combines machine learning with human judgment and subject matter expertise to provide robust and resilient automation. Unified Automation™ adapts to the highly dynamic nature of revenue cycle operations and has been purpose-built for healthcare. AKASA enables health systems to decrease their cost to collect so they can invest more in patient care and be better stewards of the healthcare dollar. While AKASA is based in the heart of Silicon Valley, we embrace a work-from-anywhere attitude and we are hiring. Learn more at www.AKASA.com.

This published piece is provided solely for informational purposes. HFMA does not endorse the published material or warrant or guarantee its accuracy. The statements and opinions by participants are those of the participants and not those of HFMA. References to commercial manufacturers, vendors, products, or services that may appear do not constitute endorsements by HFMA.