Guest: Tami McMasters Gomez, Executive Director of Mid-Revenue Cycle, UC Davis Health
Host: Praveen Chandran
Introduction and Leadership Background at UC Davis Health Mid-Revenue Cycle
Praveen Chandran
You're listening to The RC Executive Lounge podcast, the show where healthcare revenue leaders share real-world strategies, hard-earned lessons, and bold ideas shaping the future of revenue cycle. The views expressed by guests are their own and do not constitute endorsement of any specific product or solution.
Hi everyone, welcome to another episode of Season 2 of The RC Executive Lounge podcast series. I'm your host, Praveen, and I'm super glad you're all joining us today.
I'm very excited to welcome one of the most recognized voices in the mid-revenue cycle. Our guest is Tami McMasters Gomez, Executive Director of Mid-Revenue Cycle at UC Davis Health in Sacramento, where she leads health information management, coding, clinical documentation integrity, and revenue integrity across one of the country's leading academic health systems.
In her role, Tami is responsible for the accuracy, compliance, and efficiency of the mid-revenue cycle, bringing coding, CDI, compliance, and finance teams together under a unified strategy and leveraging technology and artificial intelligence to drive sustainable performance.
Tami is a nationally recognized leader and a sought-after expert on AI in the revenue cycle. Her program won the 2021 ACDIS Diversity in CDI Award. She received the 2022 ACDIS CDI Professional Achievement Award and she serves on the ACDIS Advisory Board. She holds her MHL along with the CCDS, CDIP, and CCS-P credentials and speaks nationally on predictive analytics and AI-driven decision-making in the revenue cycle.
A few things set her apart. She made the bold decision to discontinue UC Davis Health's CDI and coding reconciliation process, driving a 33 percent increase in productivity backed by coding accuracy near 99.9 percent. She has been candid that AI should augment her coding workforce, not replace it, and she launched the UC Davis Neurodiversity Coding Internship Program, creating professional pathways for neurodivergent individuals into medical coding.
We will talk today about the biggest challenges facing the RCM industry and how to prioritize amid them, the role agentic AI is playing in the revenue cycle, and how she navigates difficult leadership challenges in a complex RCM environment. Now let's welcome Tami. Tami, welcome to the show and thank you so much for joining us.
Tami McMasters Gomez
Thank you so much, Praveen, and I'm humbled to be here. Thanks for having me.
Setting Strategic Priorities and Preventing Revenue Leakage Upstream
Praveen Chandran
Let's dive right in. With so many pressures on finance and RCM teams today, from payer delays to staffing gaps, how do you go about setting your top strategic priorities? What is your framework or approach to thinking about strategic priorities in the first place?
Tami McMasters Gomez
In the mid-revenue cycle, I try to anchor priorities around preventing revenue leakage before the claim is ever dropped or coded. So I think about how we can be more strategic, working more proactively rather than reactively. That includes frameworks like authorization and medical necessity accuracy. Are we getting it right the first time based on payer rules, clinical criteria, and documentation?
That also includes clinical documentation integrity in real time. Are we supporting the level of care and the services billed, not retrospectively, but during the actual admission of the patient? More upstream rather than downstream.
And then downstream denial prevention: what avoidable denials look like and which ones are originating from breakdowns within the mid-revenue cycle. We also rely heavily on denial root cause analysis tied back to mid-revenue cycle processes, payer policy intelligence, and targeting high-impact areas like outpatient procedures, infusions, and imaging.
Ultimately my goal for the mid-revenue cycle is to act as a control point that protects revenue before it even becomes at risk from an accounts receivable perspective.
Praveen Chandran
Makes sense. And every organization has to make tough choices, especially at your level. You're probably getting twenty, thirty, or fifty initiatives from your team members, and your team's bandwidth is always limited. So you obviously have to pick a few every year and have to say no to some really good initiatives. Can you share an example where you had to say no to a really good initiative in favor of something a lot more critical in the last one or two years?
Tami McMasters Gomez
We had an opportunity to expand retrospective clinical documentation review programs, and it would have improved capture after the fact, but it does require significant resources. So instead we prioritized adoption of technology in that space, using real-time tools to sit as a safety net behind our CDI team, looking at where there were missed query opportunities or missed coding opportunities. This is really where we're looking at automation and technology to augment, rather than throwing labor resources at the problem.
We didn't say no to increasing staffing because it wasn't valuable. We're really looking at how we can leverage technology at the same time while being mindful of budget, as most institutions are challenged right now in this space.
Balancing Technology Investment with Operational Priorities
Praveen Chandran
Makes sense. And it seems like in that example you were leaning towards technology to solve a valuable problem. A related question: there is a tension between innovation requirements, which are technology investments, and operational requirements, which are short-term needs. How do you as a leader navigate that tension? Your technology investments are great and would have amazing ROI, but they're also risky bets versus operational requirements where the operations team is potentially knocking on the door requesting an immediate solve. How do you manage the tension between the two?
Tami McMasters Gomez
We tend to play this a little more conservatively compared to some organizations. We look at how we can engage with a vendor or an automation or a technology in some type of proof of concept so that we can actually gauge what the yield is in return. What are we investing from an IT infrastructure build perspective? What are we investing from a staffing team engagement perspective? And what is the yield in return? Are we going to see the yield we're expecting, or is this a product that has overpromised and underdelivered?
So I think it's really important for organizations to consider some type of proof of concept with a vendor so that the vendor can actually stand up the product and prove that return, and you can get a feel for what it's going to take to manage it. Then you take that back to your leadership and say, "We've done our due diligence. We've looked into this and this is what realistically we can expect to see in terms of predictable outcomes."
Praveen Chandran
That's actually a great way to test the waters and then go deeper as you see the ROI. Thank you so much for that. Now we hear a lot about programs like patient financing and denial prevention at almost every major RCM event. You go to HFMA, MGMA, HIMSS, wherever it is, these topics show up a lot. Where do these kinds of programs fit into your strategic roadmap, and how does your organization approach these initiatives?
Tami McMasters Gomez
In mid-revenue cycle, I think we play a different but critical role in both. Denial prevention is central to everything we do. We have a denials program manager and that program sits within revenue integrity, but we really have to look at being more proactive upstream instead of reactive. We can't wait for the denial to happen. We need to think about how we can ensure authorization accuracy upfront, align documentation with payer expectations upfront, and then help reduce medical necessity and technical denials as a result.
Patient financing intersects through authorization and clarity. When authorizations and coverage are clear up front and we've done our due diligence, we can expect to see more accurate estimates, which will eventually reduce surprise billing and support financial engagement. So while we don't own financing, we directly influence it by ensuring that we have cleaner claims and more predictable outcomes, trying to plug those gaps upstream rather than being reactive and writing appeals.
And there are still advantages to appealing things in the retroactive space because you have to. But the way I think about and operationalize this is to take that information, do root cause analysis, and then continue to plug those gaps upstream where we can.
Praveen Chandran
Makes sense. That's a good stopping point before we move to the next segment. Let's take a short break. When we come back, we are going to talk to Tami about a recent initiative that she and her team led, what challenges they were solving for, and how they went about the implementation. Let's take a short break.
Denial Prevention, Authorization Accuracy, and Patient Financing
Praveen Chandran
Welcome back. Tami, I'd love to dive into a recent initiative that you and your team led. Maybe let's start with what challenges were you solving for.
Tami McMasters Gomez
What we're really diving deep into right now is focusing on how we can help with documentation around medical necessity and authorization-related denials, particularly for some of those high-cost outpatient services. The issues could range from frequent payer policy mismatches to manual and inconsistent authorization workflows, to documentation not fully aligned with clinical criteria. We might not have a covered diagnosis for some type of outpatient procedure or test that's being done.
So really a lot of that is driven around documentation and making sure, again, that we're proactive upstream with those frequent payer policy mismatches and that manual, inconsistent authorization workflow. What we're trying to do is build an intersection between revenue integrity, authorizations, denials, and our CDI team so that we can address these things upstream.
We throw people at it, we throw processes at it, but we also look at where we can partner to find solutions: looking for real-time payer rule guidance at the point of decision-making, integrating with provider workflows, not just the back-office teams, and looking for ways to build out predictive alerts before the services are rendered.
A key factor is making sure that you choose the right tools that bridge the clinical and revenue cycle teams and that we don't operate in silos. Bringing all those teams together is a big ask, and there are still going to be things that slip through the cracks. But those are things we can use to improve outcomes upstream and continue to plug the gaps.
Praveen Chandran
Makes sense. And once you identified this challenge, how did you go about selecting a solution or a partner? Whenever there's a problem of this scale, there's that tension between build versus buy. How did you go about resolving it, and what was the outcome?
Tami McMasters Gomez
First and foremost, we had to identify some of the pitfalls and surprises. There are a few big lessons learned. Making sure that you have clinical engagement is going to be critical. The mid-revenue cycle assessment depends on physician and clinical staff alignment, not just the revenue cycle teams. And really knowing and being conscious of the fact that standardization is harder than expected. Variability in service lines and payer rules adds that complexity layer. And upstream dependencies, like scheduling and order entry, surface quickly.
So what we're doing, and how we're approaching this, is kind of a triad: people, process, and technology. Picking the right technology may not be the only solution. It might be that we need to build or integrate into our EHR specific workflows that are more on the physician side of the house. It may be that we need to set some edits on ordering for specific medications or drugs that need a covered diagnosis. Or it may be that we need to implement an advance beneficiary notice process that isn't necessarily being actively deployed in the clinic setting the way it might be in the emergency room or other areas.
So I wanted to level-set that it's not just about selecting a technology. It's also making sure that you have the right people and processes in place, and then selecting the technology to fill the gaps where you do have an opportunity. Doing that requires looking at the various vendors in the space, looking at what you have in your current tech stack within your EHR, whether or not there are tools that exist in your current infrastructure that you can leverage, and then making the decision.
Initiative Deep Dive: Write-Off Avoidance Task Force and Vendor Selection
Praveen Chandran
Makes sense. And as you look at the implementation for this project, what did that look like? Were there any unforeseen pitfalls, surprises, or lessons you learned along the way that you could share with our audience?
Tami McMasters Gomez
To be fully transparent, we're actually in the process of looking at the various vendors on the technology side, but we've plugged the gaps I mentioned upstream with people and process. We've leveraged all of the tools we can within our current people and the collaboration with the clinical teams, the patient access teams up front, the mid-revenue cycle and the back-end teams all working together in a large cross-functional team. It's called the write-off avoidance task force.
We meet regularly. We go through the different documentation schemas and the different denial reasons. We're working very collectively. Things are being routed to work queues. And at the same time, while we're doing all of this, we're interviewing various vendors in the space to determine what is going to be the best fit for the organization, considering we already have a foundation in place. What is it that we're trying to solve now? What technology are we hoping to adopt and what are we hoping to achieve?
Praveen Chandran
And then measuring and tracking that impact, right? Making sure that you're yielding that ROI. You may have a vendor that promises a yield and ROI, but you have to measure it and look at that outcome.
Tami McMasters Gomez
Absolutely.
Measuring Success and Key Revenue Cycle Metrics
Praveen Chandran
As you proceed with execution in the future with a vendor, how would you track success for a program like this? Obviously program success has multiple layers: the financial layer where there's ROI and yield, and also an operational layer where there's going to be a change in operational metrics and potentially denial metrics. What does tracking success look like for a program of this scale?
Tami McMasters Gomez
We would look at medical necessity denial rates, first-pass claim acceptance tied to mid-revenue cycle edits, and avoidable denial dollars that have been prevented. Some early outcomes may be a reduction in targeted denials, fewer retroactive authorizations, and improved collaboration between clinical and RCM teams.
I think we're also emphasizing leading indicators, because by the time you see a denial, it's already too late. So measuring those things right now, and then once we have a baseline without the technology, measuring those same things with the technology in place will help determine whether or not you're yielding that ROI.
Praveen Chandran
Makes sense. And just from my understanding, is it also true that if the denial rates go down based on this initiative, there's a possibility that the cash days on hand also goes up?
Tami McMasters Gomez
It can be that our cash flow before adjustments goes down and our cash goes up. But it depends on the workflows and how you work to prevent some of those avoidable denied dollars upstream rather than being reactive. I would expect our cash flow before adjustments to go down while cash actually improves.
Praveen Chandran
Yes, that makes sense. Thank you. Let's move on to the next section. In the next section, we are going to talk to Tami about the role agentic AI is about to play in the revenue cycle and how it can improve outcomes for the hospital as well as for patients. Please stay tuned.
Autonomous Coding, Agentic AI, and Human-in-the-Loop Governance
Praveen Chandran
We are back. Tami, I want to shift gears into technology. What role do you see agentic AI playing in the revenue cycle, or more specifically in the mid-revenue cycle, as you look at the next twelve months versus the next three to five years?
Tami McMasters Gomez
In the mid-revenue cycle, we are already using AI to become a real-time decision support engine. Some examples would be around autonomous coding, and we just actually went live with two different vendors in the autonomous coding space.
We're using one vendor to tackle more of an entry-level type of coding, specifically around ancillary coding in radiology, to be exact. These are more entry-level, repetitive types of coding for things like mammograms, CT scans, and ultrasounds, where it's high volume but low complexity and low risk, but you still end up assigning fifteen FTEs to the work because the volume is so high. What we're hoping to accomplish is to reduce the administrative burden of having coders do this type of work. At the same time, we're trying to solve for growth. We're seeing a lot of growth in our organization, and the volumes for these services are increasing by a third. So do we continue to hire more coders in an environment where there's a national shortage, or do we augment growth with technology and allow autonomous coding to handle these accounts in lower-risk areas where the complexity isn't there?
The other thing we're doing from a compliance and risk mitigation perspective is making sure that our accuracy thresholds are around the 90 to 95 percent range. What that means is the autonomous coding engine will code the account, but if it's not confident at that 90 to 95 percent threshold, it will route to a work queue for a coder to do a second-level review behind the AI and make sure the coding is correct with any needed updates.
So we have a human in the loop to ensure integrity with that process. And then we make sure we also have a QA process in place for that 10 or 5 percent risk that we're willing to accept. Even if you feel confident in letting these things go direct to bill, meaning no coder needs to stop them in a work queue and they're autonomously coded and passing through, you should still have a policy around auditing AI and also a QA process that is auditing that 10 to 20 percent variance that you're willing to take the risk on.
At the same time, we're also going live with another autonomous coding solution that is coding E&M in the outpatient space, specifically in your outpatient clinics: your physician office visits, the lower-complexity annual well-child visits, and annual health screenings. This autonomous coding solution will autonomously code E&M diagnosis and modifier coding. We're seeing great results with this, and as the engine becomes smarter and we start to yield that accuracy threshold I mentioned, we hope to also solve the problem around growth and labor reduction with regards to needing to hire more staff, especially in the current climate where we have a national shortage.
Praveen Chandran
That makes sense. And agentic AI specifically has two types of applications within claims denial management and more broadly in RCM. One is places where it could bring incremental improvements, like a five or ten percent improvement. And other places where it could truly bring a five-times or ten-times step-function improvement. What do you think are the areas where agentic AI can really bring that step-function improvement within broader RCM or more so within mid-revenue cycle?
Tami McMasters Gomez
I think the biggest shift will be embedding intelligence into clinical workflows rather than layering it on afterward. Some of the game-changing areas are real-time documentation guidance aligned to payer criteria, predictive identification of authorization risk, and automated validation of orders against payer rules.
At the same time, I think ambient technology, and we are already using a form of it mostly in the outpatient setting, to mitigate administrative burden around documentation for our physicians. But I do think with the advancements in that space, we can start to see ambient technology also embed some more real-time guidance around documentation.
I think the other big thing we should be watching for is how we navigate governance around AI. There are already several assembly and state bills in the state of California that prohibit the use of AI in clinical care decision-making, and that can get really complicated when we talk about medical necessity reviews and CDI work, because CDI is driving clinical documentation that is used in the chart to treat and care for the patient. So there's a lot of governance we have to keep in mind around how we embed these intelligences into our clinical workflows.
Step-Function AI Impact and Technologies Worth Watching
Praveen Chandran
That makes sense. And one last question for this section before we move to the next: what other technologies are you exploring actively or watching closely that you think would be applicable for revenue cycle or mid-revenue cycle? Outside of AI, is anything interesting to you?
Tami McMasters Gomez
Anything that has a clinical and an RCM workflow integration platform is something we should be looking at. Real-time eligibility and authorization tools, whether AI-driven or not. Anything that's integrated and embedded into your current EHR workflows. And payer transparency tools, policy engines, and rule libraries can be really helpful as we start to see payer behavior shift.
Praveen Chandran
Makes sense. Payer transparency in particular seems like a focus for a lot of people, given that there is just so much change happening in that area. One last question: is there a metric that you as a leader obsess over every morning, so much so that if that metric goes down there's significant tension in the organization?
Tami McMasters Gomez
There are three that keep me focused: accounts receivable, our cash flow before adjustments, which is our CFB, and because I'm in mid-revenue cycle, I'm paying close attention to denials and charge lag. Those are the four key metrics I obsess over daily.
One of the things I implemented at our organization is a daily huddle called HIPAY. It's meant to focus on these four metrics and look at where in the system something is being held up. Is it sitting in a work queue waiting for the OR logs to get updated so the charges can drop on the claim? Is it sitting in a coding work queue because a coder is waiting for documentation? Where is it sitting in the organization? And then we can escalate and take action, especially if it's a high-dollar case that's impacting CFB or an older account that's impacting charge lag. Every day we get all the key stakeholders on this call and everybody is held to an expectation around escalation and addressing issues, and sometimes they get escalated up to our VP depending on what we're trying to solve.
Praveen Chandran
Makes sense. Let's take a short break. When we come back in our last segment of the episode, we're going to talk to Tami about complex leadership challenges that she has navigated in these types of complex RCM environments. Let's take a break. We'll be back soon.
Building Momentum, Leadership Advice, and Recommended Reading
Praveen Chandran
Welcome back, Tami. Change is hard. It is especially hard in complex RCM environments. How do you as a leader build momentum for change across various different teams? Especially given that revenue cycle is a highly cross-functional area with so many teams to coordinate. How do you navigate building momentum for change?
Tami McMasters Gomez
In mid-revenue cycle it's unique because it crosses clinical and operational worlds. Really focusing on bringing data to clinicians in a meaningful way is critical. That could be showing how documentation impacts denials and patient care delays, and how it impacts our rankings in US News or our quality outcomes in Leapfrog. Some of that is actually patient-facing, and it can be used in a way that determines where patients choose to receive their care.
I think embedding change into workflows, not adding extra steps, and that change management piece is really going to be key. Building momentum also relies heavily on change management. And then celebrating prevention, not just recovery. How well are we doing at working upstream? Moving your focus as far upstream as possible, because every dollar prevented from a denial in the mid-revenue cycle is going to be exponentially more valuable than one recovered later. I think those are the building blocks for how we can yield momentum and move the needle on change.
Praveen Chandran
Makes sense. If you could give one piece of advice to a fellow RCM leader or a CFO tackling similar challenges, whether in denials management, patient financing, financial assistance, or any other area of RCM, what would it be?
Tami McMasters Gomez
I have two things. The first, and this has really been the tone of this conversation all along, is to move your focus as far upstream as possible. Being proactive rather than reactive as much as you can.
But I also think that as you're exploring technology and adoption and investments into different agentic AI or AI tools, you need a proof of concept, and you also need a human in the loop. We're not going to plug and play and walk away. We need to have someone behind the AI, auditing the AI, governing the AI, and making sure that we're not putting our organization at more risk. I think those two things can create immediate change in your organization today.
Praveen Chandran
Makes sense. One last question to close out the episode: is there a recent book, a podcast, or a framework that significantly influenced your leadership thinking, whether in RCM or in general?
Tami McMasters Gomez
There's a book called The Speed of Trust that has really helped my foundation in terms of how I lead. Making sure that the people you're working with trust you, that you have the trust of your peers, and that you're working together by creating collaborative relationships built on trust. Because without trust, I don't think you have a lot of success with change management and other things downstream.
There's a second book I read that carries over into the professional world. It's called Just Let Them. It's more of a self-help book around the idea that you cannot control the way people react or the way people behave, but you can control the way you react, the way you behave, and the way you choose to move. I kind of live by that mantra. If someone is upset, I can apologize and try to make the situation better and do what I need to do to get us to a place of mutual understanding, but I can't really control how the other person reacts or perceives the way I move.
So I think it's really about making sure you stay in that space of understanding and trust, looking at all perspectives, and taking into consideration that others may not be looking at things from the same lens as you. They may be dealing with something personal that has driven the way they view a situation. We have to be mindful as leaders of the circumstances that sometimes surround conflict.
Praveen Chandran
The last point you made around trust and empathy is a really powerful insight. Tami, thank you so much for sharing such powerful insights with our audience and thank you so much for joining the show today.
I'm really glad we did this episode because just listening to you, I was able to think of a lot of insights I learned personally, and I'm sure our audience is taking back a lot of interesting ideas they can use in their day-to-day. So thanks again for joining the show, and I hope you can join us in another episode. Thank you so much.
Tami McMasters Gomez
Thank you for having me. I appreciate it.
