In this webinar, Charta Health's Adam Morris talks with Vanessa Miller, vice president of revenue operations at Family Care Center (FCC), a private equity-backed behavioral health provider, about how she used AI and automation to scale revenue cycle management as FCC grew from five clinics and 65 providers to 50 clinics and more than 700 providers. Vanessa walks through the tools FCC adopted across the front end, mid-cycle, and back end of the revenue cycle, how she evaluates vendors, and why visibility is the foundation of a high-performing RCM team.
Key takeaways
- In a PE-backed organization, growth is expected, so Vanessa evaluates every process by whether it can support FCC when it is twice as large.
- Facing staffing shortages in healthcare, rev cycle, and behavioral health, she reframed the question from "who do I hire" to "why does this work exist, and how do I automate it."
- On the front end, FCC automated credentialing and pre-visit eligibility, benefits, and authorization checks, on the principle that getting eligibility and authorizations right up front prevents downstream denials.
- In the mid-cycle, FCC moved from 10% retrospective audits of the previous quarter to pre-billing review of 100% of claims, one of its first AI initiatives.
- On the back end, FCC combines denials analytics, RPA and voice AI for claim follow-up, automated payment posting, and an OCR lockbox to reduce manual remittance posting.
- Vanessa's non-negotiable when choosing a vendor is flexibility: if the platform can't adapt to your workflows, your organization ends up bending to fit the software.
Watch the webinar recording: Scaling RCM operations with AI: Lessons from an early adopter
Introducing the session
Adam Morris: Hello, and welcome to this session on scaling RCM operations with AI. I'm Adam Morris with Charta Health. We're joined for this session by [Vanessa] Miller, the vice president of revenue operations at Family Care Center. Family Care Center is a fast-growing, private equity-backed behavioral health care provider operating dozens of clinics across five states. FCC's 700-plus providers span multiple service lines, including psychotherapy, psychiatry, psych testing, and transcranial magnetic stimulation. FCC also recently added an intensive outpatient program to its expanding service lines.
Vanessa is one of the teammates leading the rapid development of the business, in her case on the revenue cycle operations side. Vanessa has accelerated business growth in part by taking a proactive approach to exploring AI technologies for rev cycle management, a tech stack that has allowed her not only to optimize revenue capture and achieve more reliable forecasts, but also to scale FCC's compliance operations across five states and new service lines without scaling her compliance team by the same factor. We'll get to all of that in just a moment.
I'd like to start, however, by reminding everyone in the audience that this is an interactive webinar and welcome you to submit any questions you have for Vanessa at any point using the Q&A feature in the side navigation panel on your screen. We'll address those questions at the close of the session, and if we don't get to your question, someone on the team will reach out to respond. You can also find some useful resources today on the right-hand nav of your screen, in the section marked Resources. But without further ado, Vanessa, let's get started. I'd like to begin by hearing more about you and your journey. Could you tell us more about your role at FCC, how you got there, and the problems you're focused on solving today?
A revenue cycle leader's path from 5 clinics to 50
In brief: Vanessa Miller has more than 20 years in healthcare and oversees revenue cycle management and credentialing enterprise-wide at Family Care Center. She led system implementations, operational redesigns, and process improvement as FCC grew from 5 clinics and 65 providers to 50 clinics and more than 700 providers, and she saw technology as the way to keep scaling effectively.
Vanessa Miller: Thank you, Adam. I'm Vanessa. I'm the vice president of revenue operations, and I have been in the healthcare space for over 20 years. I have worked at every level, from digging in the weeds doing the work, to leading teams through transformation, and now overseeing RCM and credentialing enterprise-wide. I've helped with the end-to-end scope: scheduling, insurance verification, authorizations, coding, billing, payment posting, denials. Pretty much anything, you name it, I have lived through it hands-on. That full view is what has helped me with making upstream decisions that can help with those downstream financial impacts.
At Family Care Center, we started at five clinics and 65 providers. By leading large-scale system implementations, operational redesigns, and process improvement, I've been able to scale up to 50 clinics with over 700 providers. With that growth, I found that technology was the opportunity we had to continue to scale and grow effectively. So I've invested in my passion of solving problems and eliminating waste, not just in buying software.
And a little bit around Family Care Center and why I'm here: I believe in who we are and what we offer. Providing access to care and being part of a team that treats the whole patient is something I can get behind every day.
How private equity backing shapes revenue cycle decisions
In brief: With private equity backing, growth is expected, not optional. Miller tests every process by asking whether it can support the organization when it is twice as large, because a revenue cycle team that is catching up to the business is setting itself up to fail.
Adam: You mentioned a little bit about FCC. I also wanted to observe that it is a private equity-backed company, and I'm curious what unique pressures that might put on growth expectations for you in your role and for the rev cycle team. How does the PE backing shape the decisions you're making day to day?
Vanessa: One of the unique things about having PE backing is that growth isn't optional. It's expected. So you have to learn to pivot. Every new clinic, every new state means new infrastructure that we have to scale, and we have to be ahead of the business. If you're catching up to the business, then you are setting yourself up to fail. So I look at every decision as: Can this process support us not just today, but when we're twice as large? And how do I continue to find those efficiencies to allow us to scale and grow, so that we can manage those pressures that you see within the PE space?
Why automate revenue cycle work instead of scaling headcount?
In brief: Staffing shortages in healthcare, rev cycle, and behavioral health meant hiring alone couldn't keep pace with FCC's growth. Miller reframed the question from who to hire to why the work exists and how to automate it, using technology to remove repetitive work rather than to replace staff.
Adam: And I'm guessing that's what led you to investigate AI. We've discussed this before, Vanessa: you were pretty aggressive early on in exploring and evaluating AI solutions in the rev cycle. I'm curious to hear more about your thought process there. What pushed you, or maybe who pushed you, to go all in on technology rather than just scaling headcount, as would have been the traditional way of scaling RCM operations?
Vanessa: Early on, I realized that scaling headcount and hiring was not the way that we were going to be able to navigate through this complexity. There are staffing shortages in healthcare, rev cycle, and behavioral health. So, managing those shortages while also trying to scale and grow an organization, you have to reframe the question from "who do I hire" to "why does this work exist, and how do I automate it to work smarter and not harder?" If someone is spending their entire day copying data between systems, checking eligibility, [doing] repetitive tasks, that's not where their expertise lives, and it's not where we're going to get the most value from the team that we're hiring.
I found that technology was a way for me to help elevate the team and not eliminate them. We still have a large headcount. We still have a lot of team members that we need to manage the day-to-day functions. The real unlock wasn't necessarily cost savings. It was more about job satisfaction and people being able to feel their impact. So when I started looking into the technology space, I was looking for opportunities not to replace people, but to remove the work that they shouldn't have to do. That is why technology started to play into the decisions I made.
How to evaluate AI tools for revenue cycle management
In brief: Miller started from where manual workflows were creating delays and inconsistency, then evaluated vendors to address those gaps. FCC now uses several automation partners, covering RPA, voice AI, eligibility, automated remittance posting, referral summarization, patient statements, and analytics.
Adam: That makes sense. I'd love to hear you take us a little deeper into the mechanics of all of this now. Could you first give us a step-by-step of how you navigated the exploration and evaluation of these AI technologies, or tech solutions, for the rev cycle? And then later we can get under the hood with some of the details on what those are.
Vanessa: Absolutely. As I mentioned, I was identifying that there was potential for delays, inconsistency, and heavy manual workflows. So I started trying to look at what partners were in the market and where technology could help supplement things. We talked with a lot of vendors, and, with full transparency, Charta is not the only automation that we have deployed. We have invested in a lot of technology, from RPA to voice AI, eligibility, automated remittance posting, referral summarization, patient statements, analytics, you name it.
We have tried to find the way to leverage that technology, again, to help with supporting the team and removing some of those heavy manual efforts that innately have human error and process error built in. I try to find a way to give leaders the visibility that they have never had before by leveraging all this technology, vetting these different vendors, and finding the right tools to invest in.
Front-end revenue cycle automation: Credentialing, eligibility, and authorizations
In brief: FCC automated provider credentialing to get new providers billable faster and to track credentialing status across the organization. It also automated pre-visit eligibility, benefits, and authorization checks that otherwise span payer portals, Availity, Inovalon, and phone calls. Miller's principle: getting eligibility and authorizations right up front prevents denials downstream.
Adam: Great. I'd love to get a little more in-depth here, Vanessa, and look at the three stages of the rev cycle as they're traditionally thought of, individually and separately from each other. Let's start with the front end of the revenue cycle. What are some efficiencies you found there, some technologies you adopted that led to positive change?
Vanessa: Thanks. Some of the front-end functionality that we've deployed stands outside of just RCM and into the provider experience. So when I think of front end, I go front end. We've partnered with Medallion, and they help us with delegation and provider credentialing automation. With that partnership, we've been able to reduce our providers' onboarding time, and we've been able to increase visibility into our credentialing statuses across the organization. Unfortunately, payers like to delay, so having real-time transparency into that has been crucial to our scale, our growth, and our continued revenue generation. Getting these providers in, credentialed, and billable faster isn't just a provider satisfier; it's also a revenue driver. That's why we looked at that as one of our front-end opportunities.
Then you think of the next stage of a patient's life. Once they've identified their provider, and you know who they're seeing and what they're being seen for, you're moving into: What's their cost going to be? Are we in network? Do they have copays, coinsurance, deductibles? Do you need an authorization? So we tried to look at how we automated those processes. We're in a new relationship with a company called Soma. What Soma does is help automate the fragmented processes you can run into across multiple platforms. When you're verifying a patient's benefits, you might be checking the payer portal, Availity, Inovalon, all of these different locations. You're picking up the phone, and it can become a very time-consuming process when you're trying to manage thousands of patients.
By implementing this holistic solution, we're able to have a single stop that can manage all of those pre-visit functions, and that helps with decreasing the downstream tasks and denials. If you get the eligibility right on the front end, you're not going to run into those denials. If you get that authorization, you're not going to run into those denials. So we're looking at how we can fix things upstream, through credentialing and benefits, to drive that downstream output.
Mid-cycle revenue integrity: From 10% sample audits to 100% pre-billing review
In brief: Pre-billing claim review with Charta was one of FCC's first AI initiatives. FCC moved from auditing 10% of the previous quarter's claims to reviewing 100% of claims, which Miller says lets her team focus on provider education and stay compliant while scaling across states.
Adam: One thing I heard at the HFMA conference earlier this year was that there's all this concern about denials on the very back end, and the conversation has shifted toward reducing the size of the target: making sure that front-end errors and mid-cycle errors are not even getting out the door in the first place. So let's shift now to the mid-cycle. I want to hear more about how you've experienced technology there.
Vanessa: Within the mid-cycle, we have partnered with Charta. For us, this was about investing in something that could help us with scaling and growing and having confidence in the integrity of our claims. When you're hiring at a max rate with PE backing, you need to have your pulse on any potential provider trends, bad habits they may have brought from other organizations, and make sure you have confidence in the revenue you're booking. So looking at this pre-billing integrity and compliance lane with Charta was one of the very first AI automation initiatives that we undertook, because we wanted to make sure we had confidence in our data and our infrastructure.
That has helped us with revenue integrity across our claims. We moved from the [days of old], running 10% audits on the last quarter and hoping that you find the needle in the haystack, to 100% audits on all of our claims. Our team has been able to focus on meaningful change and meaningful provider education, and it's allowed us to remain compliant despite our growth and our scale. That has helped us with reducing what we may not know. Sometimes that cost is a little hidden, and you don't know until, unfortunately, you know. So being able to say that we've got that confidence was a big point for us as we scaled and grew, especially across states.
Adam: That's great to hear. Definitely with states with different compliance regimes. That's something we could talk about later, but it is a concern for a lot of growing behavioral health organizations. The compliance is different everywhere you go, depending on what service lines you're in.
Vanessa: Yeah.
Back-end revenue cycle automation: Denials, claim follow-up, and payment posting
In brief: On the back end, FCC uses denials analytics to find breakdowns in aging and AR, RPA and voice AI agents to check claim status and resubmit stale claims, automated payment posting, and an OCR lockbox that converts paper checks and remits. The aim is to move staff from portal checks to patient questions and larger payer issues.
Adam: Maybe we'll come back to that, but let's shift now to the back end of the rev cycle. Some things will inevitably make it through, and denials are impossible to eradicate. What have you implemented here?
Vanessa: Within the back end, outside of just denials, you also have follow-up, payment posting, and patient collections. You have a lot of opportunities to automate within the back end, and that's why we've leveraged a few more vendors within this back-end spectrum. One of the main things we've looked at is, one, how do we get the data that we need and identify those trends? And two, how do we act on them? These partners all work cohesively together for us.
We use Level Health for denials intelligence and automation reporting. They [give you a] clear picture of where your breakdowns are within your aging and your AR, so that you can create meaningful projects, identify trends faster, and drive change upstream, whether that's with payer redirection because they have something loaded incorrectly, or with process automation. For example, we found that eligibility was a big gap, so we identified the need for that upstream automation. Having that clear, transparent data helped drive the decisions we've made as an organization.
From there, we've looked at the tasks the team is doing. If they're just going to a payer portal, checking the status of a claim, notating an account, resubmitting a claim, that's a process we can automate. We would love to have the team on the phone helping answer questions [about] patients' bills, following up with payers on larger issues, and getting mass resubmissions done. So we started leveraging Droidl from an AI standpoint to help with progressing those stale claims that are stuck in follow-up, and following up on claims that are locked up for whatever reason. They also help with payment posting. They can go and pull, "Hey, this hit your bank today. I'm going to go post this electronic agreement in your system for you tomorrow." So they're automating those tasks and allowing the team the time to focus on what's meaningful.
We've also leveraged them for voice AI: things like calling a payer to say, "What's the status of this claim? Here's the patient name and information. Can you give me a status? Oh, you don't have that? All right, let me go resubmit it." Then those voice and RPA agents work cohesively to join those processes together. That has been a big lift for us from a technology standpoint on the back end, and it's freed up a lot of our team's time.
We've also looked at HealthLogic. They are an OCR lockbox technology, and they partner directly with our bank. That decreases the touchpoints, decreases the delay in cash, and allows for automation. When you're getting paper checks and paper remits, they help with converting those, depositing those, and moving them faster through the process. That has helped our team not post manual remits and not have to go claim by claim, especially when you enter new markets. As you negotiate new payers and new contracts, you start to run into: "Oh, the EFT got missed, the ERA got missed, and now you have thousands of remits that you need to post." Having those converted to the appropriate formatting, so they're adjustable in the system, has been a huge time savings for us on the back end as well.
How AI adoption affects revenue cycle team satisfaction
In brief: FCC hasn't formally measured it. Miller says early fear that AI would take jobs gave way to buy-in once staff saw automation supplementing their work, and frontline team members began proposing processes to automate and helping teach the agents.
Adam: Thank you for all of that detail, Vanessa. That's very helpful, I'm sure, for a lot of the folks tuning in. I wanted to ask a question to tie together a couple of the things you said before we move on to the audience questions. You mentioned at the very outset that employee satisfaction on your team is top of mind. And I heard you mention, as you were going through the phases of the rev cycle, that removing repetitive tasks is something you wanted to do, because no one wants to do a bunch of repetitive tasks. Are you hearing from your team about the satisfaction there? Does it happen to be something you measure, or is it anecdotal? What have you heard?
Vanessa: For us, the satisfaction is something that we've seen. When we first started deploying technology, there was a lot of fear and concern, and a lot of people saying, "AI is going to take my job." So there was a lot of pushback initially. As we started deploying these agents and partnering with these vendors, what our team found is that it was supplementing their workflow, not replacing them, and it was bringing that job satisfaction. What we found is that they started to bring ideas forward. They would say, "I have this process that is manual and labor-intensive for me. Is this something we could automate?" So the frontline teams started bringing those ideas to the forefront.
It's not something we've necessarily measured, but it shows in their buy-in, their engagement, and their willingness to help in the development. We've empowered the teams to say, "You're the subject matter expert. Why don't you take some of that time to help set up that process? Why don't you teach that agent?" It's also helping with upskilling and allowing our team to feel invested in the process. That has helped bring down a lot of the concern we've seen, while also giving them that satisfaction that, while not entirely measurable, is something we have seen surface from them.
When is a revenue cycle process ready for automation?
In brief: Miller looks for a process that is becoming a bottleneck to growth. Her signals include volume outpacing the team, heavy manual work, inconsistent outcomes, lack of visibility, too many spreadsheets, and growth outpacing operations.
Adam: That is great to hear. Some more follow-up questions here: How did you know when you were ready to bring on an AI tool? Was there a specific friction or data point that told you, "Now I've got to move"?
Vanessa: When I started to identify that a process was becoming a bottleneck to our growth is when we started to decide whether it was time to invest in something new. When you start seeing that your volume is outpacing your team, or the complexity is too much, that's when you can start to signal that you might need to invest in new tools and technology. Some of the signals I looked for that were driving those bottlenecks were things like manual work, the team having inconsistent outcomes, the lack of visibility, and having too many spreadsheets floating around, because we don't have enough of those as it is in the healthcare space. And then, whether our growth was outpacing our operations. If we were not able to scale and grow with the volume, that was a signal that we needed to assess the processes and identify our next opportunity.
The non-negotiable when choosing an RCM automation vendor: Flexibility
In brief: Flexibility is Miller's non-negotiable. Workflows, EHRs, EMRs, and clearinghouses differ by organization and specialty, and a rigid, out-of-the-box platform forces the organization to bend to the software instead of the software adapting to its operations.
Adam: As you were evaluating and doing demos of these platforms and asking questions, what was something in that exploration process that came back to you as a hard stop: a signal that you couldn't adopt this technology, or that you didn't want to continue the conversation?
Vanessa: One of the biggest hard stops, or non-negotiables, for me was flexibility. Healthcare operations are not standardized. You mentioned it earlier: The behavioral health space is different from the family practice space. It's different from the surgical space. And every organization has a different workflow. So if you're leveraging a platform that's not flexible and is a very out-of-the-box workflow, your organization is going to start to bend to the processes that fit the software, rather than having the technology adapt to your operations.
In order for you to work as efficiently as possible, you do need that flexibility and adaptability to your processes and your workloads. We all have different EHRs, EMRs, and clearinghouses. You need that flexibility in a partner, or your processes are never going to be as efficient as they could be, and you're still living in that space of waste instead of full efficiency.
Adam: Anyone who's ever worked in an EHR can probably relate to what you're saying right now.
Vanessa: Yeah.
Why visibility is the foundation of a high-performing RCM team
In brief: Miller's non-negotiable for a high-performing RCM team is visibility: "If you cannot see the problem, then you can't solve the problem." Consolidating AR data and following each claim end to end revealed problems beyond payer behavior, and encounter-level data lets FCC address new providers' documentation habits within months instead of years.
Adam: You mentioned how that was a non-negotiable. I want to play on that topic for a second. As a leader in rev cycle, what's a non-negotiable for building a high-functioning team that's going to succeed in the compliance, regulatory, billing, and oversight landscape of 2026?
Vanessa: For me, one of the non-negotiables to start is visibility. If you cannot see the problem, then you can't solve the problem. That is why we looked at working with partners like Level, to allow us to have that visibility. We were able to say, "These reports are siloed. These processes are siloed. How do we look at all the pieces of AR and follow the life of a claim end to end?" Consolidating that visibility allowed us to discover more problems than just cash flow issues. It's not always living in the payer's realm. A lot of the time it is, but not always. So leveraging that visibility is something we've tried to move toward.
Another example for us is with Charta: being able to have visibility into provider education. I mentioned it before: You can have providers who come in with bad habits from prior organizations, and that's never anything on them. Every organization has its own baseline for what good looks like. Being able to identify and educate those providers using a tool like Charta has been great for us, because while it's a difficult shift for a provider, they appreciate knowing a month or two in versus two or three years in, when something surfaces downstream. That allows them to have confidence in themselves as well, and to feel supported within the organization. So visibility is huge across the entire landscape. Go ahead.
The biggest shift in revenue cycle management for 2027
In brief: Miller expects AI to become part of revenue cycle infrastructure in 2027, automating the entire operational journey rather than single tasks. She expects RCM leaders to shift from workflow managers to transformational leaders, and human expertise to become more valuable as repetitive clicks are removed.
Adam: I was going to say, I have one more question before we pivot to the audience.
Vanessa: Mm-hmm.
Adam: What do you think is the biggest shift on the horizon for revenue cycle management as we look ahead to 2027?
Vanessa: I would say in 2027, the biggest shift is that AI is going to become part of the infrastructure. Rather than being vendors that you look to for automation, it's going to be living in all of our workflows. You're looking at automating not just one task, but the entire operational journey. I see 2027 being the time when our leaders start transitioning into transformational leaders rather than just workflow managers, and they're going to start transforming those processes for the team.
I think the human experience and expertise is going to become more valuable as well. It's going to be less about AI taking on more and having those clicks removed from the team, and more about the team being able to solve the problems. They're going to be able to manage those patient phone calls. There's a fast food joint that I know of, and one of their values is that they would rather be overstaffed than understaffed, because they want their team members to have a mindset of "How can I serve you?" rather than "You're a detractor from my day because I have too much to do." Being able to leverage those detractors from the team's workflow so they can focus on that "How can I serve you?" mindset is important in the healthcare space.
Adam: It also lets people push themselves and operate at the top end of their license and their training, whether they're a coder or whatever their function in the revenue cycle.
How automation supports multi-state compliance
In brief: Credentialing, licensure, and payer enrollment rules differ by state. FCC uses technology to track more than 10,000 records at a state-by-state level, which Miller says also helped it identify payers that weren't meeting a 2026 Arizona law on credentialing timelines.
Adam: Vanessa, we have some time to take a couple of questions from the audience. We had one come in related to that state question: How did tech adoption help you expand across states? Because there is some complexity there.
Vanessa: When you're operating across five-plus states and growing, things like credentialing, licensure, and payer enrollment rules all differ by state. What might be routine and compliant in one state might be a risk in another. So when you're trying to manage all of those processes, being able to build tracking systems that allow you to monitor at a state-by-state level is something we felt was an important adoption for us early on. We have over 10,000 records at any point in time that we have to maintain. So we knew we had to leverage technology to have confidence in all those application statuses, payer enrollments, expiring credentials, DEA licensures, making sure that everything stays compliant.
It has also allowed us to stay on top of legislation. For example, in 2026, the Arizona legislature passed some laws that affected credentialing timelines, and they hold payers more accountable within that state. By having technology in place, we were able to identify where payers are not meeting the new legislation and hold them responsible for meeting those new laws. That's something we wouldn't have been able to see if we were on antiquated processes.
Multi-state compliance isn't one rule book. When you're running in five parallel states, technology is what makes it possible to see them all at once. It goes back to visibility, and making sure that you can see what's, as you put it earlier, under the hood, so that you are driving things in a compliant and strategic way.
Using E/M leveling data to drive provider education
In brief: With Charta, FCC surfaces encounters where documentation may not support the E/M level, with the supporting analysis presented so staff don't have to read through a 10-page record. Miller says the data serves both provider education and team productivity.
Adam: It sounds like visibility is the key, and that gets us to this next question from someone in the audience: What's an example of something you discovered through visibility, maybe some data, Vanessa, that you look at to drive change in the organization?
Vanessa: For us, data has changed where we invest our effort, and it's moved us from chasing dollars to preventing the leakage before the patient is even seen. An example of that is our partnership with Charta, looking at E/M leveling and identifying the potential areas where encounters may or may not be meeting the E/M levels that have been surfaced. Having this clear, concise data presented to us in a format, [shown on screen during the live session], has allowed our team to work more efficiently and effectively.
Data is multi-pronged. It's visibility, but it's also ease of access. In this example, if we have an E/M where the level is potentially not met, having to go through 10 pages of a medical record can be just as cumbersome as doing it themselves to begin with. So having the analysis surfaced for them has helped them increase their productivity and, again, [inaudible]. This has helped us surface data not just as "This is a provider education opportunity because they're not meeting the E/M levels," but also by surfacing the data more easily to our teams to support them in their day to day.
Closing
Adam: You gave me a little bit of a flashback there, Vanessa, to the part of the CPC exam where you're doing the E/M leveling. It would be very nice to have all the relevant evidence surfaced to you right away, before reading through the question.
Vanessa: [Inaudible] six-hour exam?
Adam: It felt like six. No, I did enjoy it. Well, we're going to have to leave it there. I want to thank you again, Vanessa, for joining us today, and thanks to everyone in the audience for joining. Keep an eye on your inbox for invitations to additional webinars from Charta and other learning opportunities, and check out the resources panel on your screen. Thanks again, Vanessa. It was great having you.
Vanessa: Thank you, and have a great day.
Frequently asked questions
How did Family Care Center use AI to scale revenue cycle management?
FCC layered automation across the full revenue cycle: credentialing and pre-visit eligibility and authorization checks on the front end, 100% pre-billing claim review with Charta in the mid-cycle, and denials analytics, RPA and voice AI claim follow-up, automated payment posting, and an OCR lockbox on the back end. Vanessa Miller says this supported growth from 5 clinics to 50.
What should revenue cycle leaders look for in an AI or automation vendor?
For Miller, flexibility is the non-negotiable. Because workflows, EHRs, EMRs, and clearinghouses vary by organization, a platform that can't adapt forces the organization to bend its processes to the software.
How do you know a revenue cycle process is ready to automate?
When it becomes a bottleneck to growth. Miller's signals are volume outpacing the team, heavy manual work, inconsistent outcomes, lack of visibility, too many spreadsheets, and growth outpacing operations.
How is pre-billing review different from retrospective sample audits?
FCC previously audited about 10% of the last quarter's claims after the fact. It now reviews 100% of claims before billing, which Miller says shifts her team's effort to provider education and prevention instead of searching for problems after claims go out.
Does AI replace revenue cycle staff?
Not at FCC. Miller says the organization still has a large team; automation removes repetitive work such as portal status checks and resubmissions so staff can handle patient questions, larger payer issues, and helping configure the automations themselves.
How does automation help with multi-state compliance?
Credentialing, licensure, and payer enrollment rules differ by state. FCC tracks more than 10,000 records at the state level, giving it a view across all its states at once.
