The transactional nature of revenue cycle management (RCM) makes it a prime target for automation technologies, particularly when those tools are focused on automating the manual and redundant tasks within patient access, coding, billing, and collections. In fact, automation is addressing some of RCM’s biggest pain points, increasing revenue capture and helping early adopters achieve revenue integrity.
As automation grows in popularity – nearly all healthcare organizations have an automation strategy in place today compared to less than half just four years ago – a growing number of early adopters are discovering that bespoke technologies like robotic process automation (RPA) can deliver a far more rapid return-on-investment (ROI).
RPA also supports a healthcare organization’s scalability requirements, making it particularly beneficial for multiple areas, as shown in the figure below:
Consider the case of Tidewater Physicians Multispecialty Group (TPMG), a Virginia-based multispecialty group practice with more than 245 primary care, specialty physicians, and advanced practice clinicians. The quality claims required under TPMG’s value-based contracts are zero-dollar codes, which some payers cannot accept. For those payers, the practice levied a penny charge on the codes as placeholders to prevent the entire claim from being rejected. The penny adjustment, which is not paid, must be manually written off by TPMG’s revenue cycle team so patients can be billed for the legitimate charges. The highly repetitive and redundant nature of the transactions made it ideal for RPA, so TPMG worked with its revenue cycle management partner to create an automated transaction posting solution that integrated into its NextGen practice management system.
Ultimately, TPMG leveraged RPA to automate 98% of the penny adjustment process and resolved a backlog of more than 100,000 outstanding write-offs in just four months – a task that would have cost $41,000 annually in FTE labor if it had been done manually.
In another example, a clinical staffing and practice management company was inundated by a growing volume of faxes featuring a mix of data including demographic information, medical charts, x-rays, records featuring text with embedded images. To support the intake of this data, the organization deployed a combination of dual OCR engines, RPA, and tech-enabled services to convert 150,000 faxed medical records per month via the cloud into its EHR. Within months, more than 70% of their fax volume was fully automated while maintaining 99% quality. Additionally, the organization minimized turnaround times to 24 hours or less while simultaneously redeploying 60% of the labor to more value-added activities.
Eliminating Misconceptions
To understand how to optimally leverage automation tools like RPA, it’s important to clear up some of the most common misconceptions about them. One of the biggest is that RPA is a form of artificial intelligence (AI) – a misunderstanding that can lead to misuse, unrealistic expectations about its capabilities, and, ultimately, disappointment and frustration. For example, some healthcare organizations may think they can use RPA to make complex clinical decisions or diagnose diseases, which is beyond the technology’s capabilities.
RPA is a set of tools and techniques that automate repetitive, rule-based tasks, while AI involves the creation of intelligent machines that can perform tasks that normally require human intelligence. Additionally, RPA uses software robots or “digital workers” to mimic human actions and complete tasks such as data entry, processing claims, or scheduling appointments, while AI involves the development of algorithms and systems that can analyze data, make decisions, and learn from experience.
| RPA (a system of rules) | AI (a system that learns) |
| Rule-based decision making | Natural language processing (NLP) |
| Process execution | Autonomous computing |
| Data collection/extraction | Deep learning (from human decisions) |
| Data preparation | Machine learning |
| Quality guardrails (high accuracy) | Relies on a high probability |
| Scheduling and tracking | Forecast demand |
| Uses structured data and workflows | Relies on unstructured data and processes |
Taking the Leap
RPA and other bespoke automation technologies can play a key role in just about any healthcare organization’s RCM strategy – provided they are properly vetted and optimized. To ensure that happens, it is important to first carefully evaluate the revenue cycle department’s processes and workflows to determine how each process affects other areas of the workflow, what other departments or stakeholders might be impacted, and how labor can be reallocated to other tasks.
Setting goals and clearly defining expectations is also important, as is having a clear understanding of where automation makes the most sense for the organization. Not every RCM process is suited for RPA. It works best when the problem is clearly defined and solvable with a repetitive task. In the case of TPMG and its penny adjustment problem, the financial adjustments that needed to be made were clear, as were which systems needed to be updated and the steps required to complete each discrete task – making it an ideal fit for RPA.
This is where an automation partner with deep revenue cycle expertise can play a critical role by conducting a thorough due diligence process to gain a full understanding of the pain points RPA can most effectively address, then developing a progressive implementation strategy to achieve identified goals before going into the design stage.
For TPMG, working closely with our team to map out the systems and steps involved in the penny adjustment process helped ensure the final RPA tool not only resolved the issue, but that it also integrated smoothly and successfully into the RCM workflow. They also took a slow, measured approach to roll out of RPA, running a series of small batches through the tools, carefully analyzing the results, and making necessary adjustments before moving on to a larger batch. The tool was not activated until it had passed all quality assurance testing.
As a result of its careful approach to planning and implementation, TMPG’s RPA has a 99% accuracy rate and is expected to generate an estimated savings of more than $200,000 over a five-year period just from the penny adjustment task. By enabling more rapid patient billing, RPA has also helped accelerate the revenue cycle, improve overall cash flow, and provide TPMG with clearer insights into its financial outlook – not to mention alleviating a significant source of customer and staff frustration.
Made to Order
When it comes to automating critical aspects of the revenue cycle, tailor-made tools will deliver the greatest ROI by addressing a healthcare organization’s specific pain points. The keys to success are having a clear understanding of what processes are prime for RPA and other bespoke technology tools and which should be avoided and taking a thorough approach – preferably aided by a trusted partner with deep experience in both automation and RCM – to planning, designing, and implementation.
When properly designed and implemented, RPA tools can eliminate RCM pain points, improve cash flow, optimize internal resources, and help solidify an organization’s bottom line.
Emily Bonham
Emily Bonham is Senior Vice President of Product Management with AGS Health, and Nicholas Frenette, Executive Director of Solutions Engineering with AGS Health.
