Recent surveys, such as the Royal Philips U.S. Future Health Index 2019 report, highlight significant opportunities for digital transformation to improve healthcare cost and quality. Use cases abound for leveraging intelligent automation and other digital technologies to enhance distinct parts of the healthcare experience — especially within the revenue cycle.
In fact, these technologies can help address high-value revenue cycle management (RCM) challenges associated with the cost to collect, denials management and improving the patient’s financial experience. However, the question is how to do it. Navigating such transformation requires a nuanced understanding of two things: first, the variety of technologies that fall under the “intelligent automation” umbrella – artificial intelligence (AI), robotic process automation (RPA), cognitive automation, and others; and second, the strengths, limitations, and optimal applications of each of those technologies.
In its most basic definition, “AI” simply means the ability of machines to imitate, simulate or mimic intelligent human behavior. Within that definition are a whole host of technologies spanning a wide continuum — from RPA to deep learning and more. For starters, hospitals and health systems might want to evaluate the potential benefits provided by two specific types of intelligent RCM technology: RPA and cognitive automation.
Through RPA, robots can execute specific, pre-defined steps. RPA allows robots to emulate exactly what a human would do to complete a particular process, which makes it a valuable tool for automating manual, repetitive tasks.
Historically, that has meant that bots could only accomplish the precise steps they were programmed to perform; variability in processes prevented us from scaling bots’ level of value-add. Fortunately, with modern advances in programming languages and technology solutions, current RPA technologies are much more flexible than their predecessors. Thus, today’s RPA is capable of overcoming the variable world of healthcare RCM, and when applied with modern software design and engineering practices, can actually execute highly complex work, with 100% quality, at scale.
It is important to continually identify RCM processes that can be automated at scale. In fact, we have already identified over 1,000 use cases and activated over 160 digital workers that are the equivalent of 700-1,000 full-time employees. These digital workers perform over 4.5M transactions annually representing over 15.6 million tasks across 30 EMR platforms and 100 locations.
To use a specific example, an RCM use case that can be automated is a typical claims denial workflow. In most hospitals and health systems, an electronic claims scrubber identifies claims at risk for denial. Humans then review the list, audit each claim for a multitude of potential issues, and seek and retrieve information required to complete a clean claim. With RPA, on the other hand, claims at risk for denial can be intelligently routed for resolution without the need for human intervention. This not only speeds the claims denial workflow, but it also lessens the chance for human error.
As this example illustrates, RPA can enable efficient and effective management of large volumes of manual RCM work. But don’t make the common mistake of believing RPA is meant to replace a human workforce. Instead, RPA is best used to complement and elevate how humans work. RPA lets bots execute repetitive tasks in an efficient and standardized manner, so that people are free to spend their time and brainpower on higher-order problems.
If RPA lets robots perform certain actions, cognitive automation uses software to extend and improve the range of actions typically correlated with RPA. Cognitive automation brings “intelligence” to information-intensive processes.
Cognitive automation leverages different algorithms and technology approaches. These might include natural language processing (NLP), text analytics and data mining, semantic technology, and machine learning. With these approaches, technology can accomplish "intelligent" feats such as recognizing meaning in words. In turn, these capabilities extend the benefits of RPA by delivering more accuracy in complex business processes that involve the use of unstructured information.
Cognitive automation is a crucial part of making the technology toolkit faster, smarter and more accurate. As technology becomes more intelligent, hospitals and health systems gain new opportunities to drive strong financial results for healthcare providers and a better experience for patients.
Together, RPA and cognitive automation can remove repetitive tasks from the healthcare financial process and start to transform the revenue cycle. Implemented properly, these two types of technology can give hospitals and health systems the ability to:
Digital transformation isn’t a "do-it-yourself" endeavor — it takes the skill and experience of those who understand its many nuances. Building automation technology internally or purchasing it from a stand-alone vendor has the potential to expedite current production errors or automate internal processes that are already disjointed or inadequate. It’s imperative to look for a partner who has significantly invested in automation technology, has the right expertise to develop a long-term strategy and knows how to successfully deploy the right technologies, such as RPA and cognitive automation, to your core RCM processes to see substantial results. There is no question that AI-enabled RCM solutions give hospitals and health systems the power to solve complex revenue cycle problems better and faster—you just need the right strategy and partner in order to do so.
As R1 RCM’s Senior Vice President of Product and Technology, Joe Polaris leads the company’s product strategy development and roadmap execution. He has been with R1 RCM for more than 13 years and has developed deep front-line revenue cycle expertise holding positions such as Revenue Cycle Site Lead and Director of Operations, where he built innovative end-to-end processes that have increased the financial stability for hospitals and health systems.