The Meduit Innovation Lab Blog

Taking the Pulse of Healthcare RCM Technology: What’s New and What’s Next

Posted by Meduit RCM on May 15, 2024 9:00:00 AM

As we approach the halfway mark of 2024, healthcare costs in the United States continue to reach unprecedented heights. In 2023, expenditures were expected to reach up to $4.7 trillion. In 2031, that number is projected to be $7.2 trillion. (1) These dollar amounts underscore how critical it is for hospitals, health systems, and private practices to have the right revenue cycle infrastructure in place. Without one, collecting the funds required to expand services and meet the changing needs of patients is virtually impossible. 

With more money than ever hanging in the balance, the RCM landscape is changing quickly to adapt. New strategies, and in particular, new technologies, have emerged to close the gap between what’s paid and what’s owed. Traditional processes are being left behind in favor of (much) faster automation. Yet the human “experience” for patients and providers is still very much a focal point of the RCM process, and new ways to improve patient engagement abound – many of them created by, of all things, automated tools. 

All in all, it's a fascinating time in healthcare RCM and an excellent time to assess what’s new, what’s not, and where the industry might be headed. 

AI Is Changing the Pace and Face of RCM

 The integration of Artificial Intelligence and automation into RCM processes has had a seismic impact on healthcare collections. Currently, AI is being used to do everything from mundane tasks like processing, coding, and billing (with unprecedented speed and accuracy) to expediting the patient payment process to preempting potential claim denials before they occur. 

The efficiency, accuracy, and revenue optimization improvements AI creates are undeniable. Healthcare organizations that were quick to adapt to AI and automation are reaping the many benefits and shielding themselves (at least somewhat) from the lack of trained RCM professionals available in the industry, while those that have been slow to embrace AI are feeling the adverse impact of being on the wrong side of technology. 

Which leads us to…

The Continuing Rise of Claim Denials (and how AI factors in)

According to Healthcare Finance News, insurance claim denial rates have increased by 20% in the last five years. This spike is creating a significant administrative and financial burden for healthcare organizations. To put it into real-world context, hospitals and health systems spend an estimated $19.7 billion a year managing denied claims.(2)

Ironically, AI is a primary driver for these claim denials. Payers are using it to muddy the claims process, making it increasingly difficult for providers to achieve timely and successful outcomes. For as much good as AI does to economize the overall RCM process, it’s also keeping many providers from collecting the revenue they need.

As this chess match between payers and providers evolves in real time, savvy health organizations are partnering with RCM vendors that use AI and predictive modeling to preempt claim denials before they occur. It will be interesting to see how this strategy stems the flow of denials in the near future.

Predictive Analytics Inspire a More Focused RCM Approach

Predictive analytics are playing an increasingly important role in revenue cycle management by leveraging large data sets to identify trends, issues, and opportunities that can be acted upon to improve RCM outcomes.

With more data-powered insight at their disposal, providers can be more purposeful and precise with their RCM initiatives. For example:

  • Prioritizing High-value Accounts

Predictive analytics incorporate variables like patient demographics and payment history to segment accounts based on their likelihood to pay. This enables providers and their RCM partners to target higher-probability patients first and with more resources, thereby increasing the odds of a successful outcome.

  • Preempting Claim Denials

By analyzing the patterns of historical claims data, predictive models can identify current claims that are a denial risk. Flagging these claims early allows healthcare organizations to fix potential issues before submitting the claim.

Cultivating the Patient Experience

Research shows that most patients (around 70%) favor self-service options when paying their bills. They don’t want to engage with a customer service representative unless it’s absolutely necessary.

Since meeting customers where they are with the experience they want is critical for a successful revenue cycle, it’s become an operational imperative for providers to find the right balance of self- and full-service payment options to satisfy patients.

AI and robotic automation make it easier to deliver new self-service options that cater to patient preferences. For example:

  • “Patient-assist” automation walks patients through every step of their bill-paying process. Patients can pay on their own schedule without speaking with a customer representative unless there’s a question or problem.
  • Conversational AI can be deployed 24/7/365 to address patient needs and record data that can be utilized to improve future interactions.
  • More sophisticated text and email outreach platforms are replacing traditional phone calls and email attempts.

Understandably, patients want to control their own payment process. With new tools like the ones listed above, AI is making it easier. Combined with a robust, highly trained customer service presence, technology adds flexibility and freedom to the patient payment process, aligning with what patients are looking for.

Where Will Technology Take Us?

It’s not hyperbole to say that the RCM industry is in the midst of a technology revolution. AI, automation, and the use of big data and analytics are influencing just about every element of the revenue cycle, for better or worse. AI is being used to improve the patient experience, mitigate the impact of labor shortages, reduce costs, and accelerate cash flows. Conversely, payers are using advanced algorithms to increase claim denials and slow down reimbursements.

As AI becomes even more sophisticated, the transformation of our industry is sure to continue. A year from now, the innovations we’re discussing today could very well be old news. That’s how rapidly technology is changing everything.

At Meduit, we don’t plan to let any of our over 1,100 provider partners fall behind. To that end, we will have exciting news to share later this year that reflects the winds of change blowing through our industry and our dedication to helping our RCM customers remain on the cutting edge. Playing catch-up has never been how we operate, and there’s no reason to start now. Needless to say, we’re excited for what lies ahead; please stay tuned for more details coming soon.

1. (, “National Health Expenditures 2022-2031”).
2. (Kacik, Alex. “Claim denials cost hospitals $20 billion a year.” Modern Healthcare. 3/22/24)