Exploring the Future of AI in Revenue Cycle and Finance Management

Executives in HealthLeaders' Mastermind program on AI in RCM and finance operations say the technology will help them integrate with other departments in the health system and even work with patients to pay their bills.

Imagine an AI tool that can calculate a patient’s bill factoring in insurance coverage, a health plan’s tendency to deny a certain claim, and social determinants of health that may factor into the patient’s ability to pay. Then imagine that tool helping a hospital to work with the patient on a payment plan, compare its pricing structure with competitors and track social media mentions.

AI is seen as a tool to reduce administrative work and help clinicians get in front of their patients, but in the revenue cycle management and finance space, sometimes it’s hard to see beyond the dollars and cents and measure AI’s true impact.

Participants in HealthLeaders’ Mastermind program on the use of AI in RCM and financial operations connected those dots during a recent roundtable in Chicago, where they discussed the evolution of a technology already well-entrenched in their departments. One aspect of that conversation was to use AI to bridge the financial and clinical sides of the hospital.

“We all have to work in that same sandbox,” noted Jacqueline Samuel, MBA, PMP, director of revenue cycle quality, strategy and analytics at Atlanta’s Grady Health System.

AI has been put to work in the RCM and finance space over the past few years to address administrative tasks and do the number-crunching and data retrieval that would normally occupy staff time. Now the focus has shifted to generative AI, in which RCM and financial data is used to give staff pathways to better results; and on the horizon is predictive AI, which will give staff better ideas about where those pathways end.

Not only will the technology evolve, but how health systems and hospitals use it will change as well.

Beyond the applications in coding and denials management, executives see an opportunity for AI to learn how payers deny claims and help RCM staff proactively address, even avoid, those denials, or to tackle the complexities of the prior authorization process to reduce friction. As these tools evolve, Jane Lombardo, director of revenue cycle optimization at Stanford Health Care, said RCM staff will become “stewards” of the technology, overseeing how it’s applied and monitoring its effectiveness.

Steven Kos, MSHCA, CHCIO, senior director of revenue cycle applications at Florida’s Baptist Health, said the development of AI tools will also compel healthcare organizations to rethink RCM and finance skillsets, perhaps adding staff who are skilled at revenue cycle informatics, revenue integrity and patient advocacy or engagement.

Shannan Bolton, Stanford Health Care’s vice president of optimization and performance improvement, sees AI becoming a powerful tool for education and financial counseling, helping patients to both understand their financial responsibilities and the options available to them for paying their bills.  

“That’s where we fall short with patients,” she said.

And Christina Slemp, MHA, MSHI, vice president of revenue cycle for Tennessee-based Community Health Systems, added that AI can help reduce the stress for patients by giving them the information they need quickly, rather than waiting around for explanations.

In fact, RCM are in the unique position to integrate clinical and financial data, helping both patients and their care teams. Some health systems are already experimenting with ambient AI to capture the doctor-patient encounter and code that encounter at the same time.

That strategy can also apply to patient scheduling, Bolton says, identifying a key element of the revenue cycle and a hotspot. Patient scheduling drives revenues when handled in an efficient manner, but it can also cause headaches when patients struggle to schedule their appointments or miss them. Ai tools that enable patients to self-schedule and help providers coordinate their workflows.

Beyond helping patients to schedule their appointments, RCM and financial executives say AI will become critical in reducing the complexity around billing and collections. That includes working with payers to fine-tune coverage and reduce denials and working with patients to make sure they understand and can pay their bills.

And that’s where the technology may make the biggest impact in the future.

Kos and Clark Casarella, PhD, senior data scientist at Sanford Health, said Ai will be used to improve the way hospitals and health systems work with patients on their financial responsibilities, creating a patient scorecard of sorts that researches in real time their ability to pay a bill. And Bolton pointed out that the technology can help organizations better understand why a patient has financial insecurity, thereby addressing the underlying social determinants of health that affect the revenue cycle process.

At the end of the day, patient financial responsibility is just one small part of a healthcare organization’s RCM and financial operations, but it’s an important and often-overlooked part. And it’s one that will become more important as the healthcare landscape shifts closer to patient-centered and value-based care. AI has the potential to help, giving both patients and providers the data and tools they need to work together.

The HealthLeaders Mastermind program is an exclusive series of calls and events with healthcare executives. This AI in Finance Mastermind series features ideas, solutions, and insights on excelling your AI programs.

To inquire about participating in an upcoming Mastermind series or attending a HealthLeaders Exchange event, email us at exchange@healthleadersmedia.com