Q&A: Using AI in revenue integrity
Q: Is your organization using AI to support any revenue integrity functions? If so, what has that experience been like? If not, what are some of the barriers to implementing AI?
Ashley Brown, CHRI, RH-RCMS, RH-CBS, CAH-CBS, CH-CBS, CH-RCMS, revenue cycle analyst at La Paz Regional Hospital in Parker, Arizona: Currently the organization is not utilizing any AI systems for revenue cycle. For us as a small organization, obviously money is very important. We have to weigh the cost of everything that we do, of course, and the time. I’m a small department of one at the moment, so getting with each individual director and discovering their pain points and trying to help them solve problems with a department of one is time consuming, especially while trying to create this department. So some things are just not prioritized at the moment, and AI is just one of those items.
Kelli L. Howard, MS, CSPPM, senior manager of revenue integrity at Mayo Clinic in Phoenix, Arizona: We are in the adoption and evaluation phase across several platforms, but not necessarily directly related in revenue integrity. Because of the sheer complexity and variability of the work within revenue integrity, there haven’t been many opportunities identified. That being said, one of my favorite AI uses that we just stood up a few months ago, reviews documentation for adequate teaching physician attestations. Being an academic facility, resident billing and attestation documentation are extremely important. So from a compliance perspective, coding quality, education to providers, so on and so forth—the AI model reviews documentation, and then categorizes [it in one of two ways]: Either there’s absolutely no attestation present where it would have been expected, [or] we have an attestation but it’s either missing documentation for physical presence, or a tie to the resident note or lacking medical decision making. That data has helped us to streamline which providers require education, where opportunities for coding education may be needed, and where there could be compliance risks or opportunities. It’s been pretty slick and very value added.
Brenda L. Melone, MS, RN, CPC, senior director of revenue cycle at Sturdy Health in Attleboro, Massachusetts: We use computer-assisted coding, autonomous coding, for our inpatient applications. We also use a vendor who does our professional coding in our emergency departments only, and they have a tool which is very AI based. The AI that’s coming in the healthcare space is going to really be a game changer for so many people. I’m definitely embracing it, and I have my finger on the pulse of rolling it out to all other areas: registration, claim solution, denials management, etc.
Jaclyn Woolnough, director of revenue integrity at MetroHealth in Cleveland, Ohio: Metro Health is currently utilizing AI, and the revenue integrity structure here does include both hospital and professional coders reporting up indirectly through me. Right now outside [of our EHR] we are using [a third-party vendor solution] that includes some AI functions for both professional and hospital coding. We’re also looking at implementing AI in certain charge reviews or queues that are currently worked by members of the revenue integrity team today, but our eyes are, I think, a little bit more on the future. We have established an AI steering committee. There are subcommittees of the steering committee, and one of those subcommittees is revenue cycle and finance AI. We individually—all the members of that committee—are the ones who listen to what’s available [and] see what’s out there; [then we] take it to that committee, and then we have a process for approvals and implementation through the governance of the steering committee.
Editor's note: Learn more about how revenue integrity programs are applying AI in NAHRI's 2026 State of the Revenue Integrity Industry Report.