Future-Proof Your Coding Team with Audit-Ready Skills

Stephani Scott: So what I thought I would do at the start of of our conversations is really bring to you the business case of up scaling your coders into auditors, helping your coders, learn, an auditor mindset, if you will. I think, that's maybe the the first step to future proofing our coders.

Then I wanted to talk about what the difference is between an auditor and a coder, what those different unique skill sets are so you can get a better understanding of how you can kind of intertwine those different roles and responsibilities.

I then wanted to touch on AI and how's that how that is changing our world today in the revenue cycle.

I have a couple of case studies that I've pulled. These are real life scenarios of organizations that have up skilled their coders. And, I'll share with you just briefly, their challenges and their what they did, to implement changes and then what those results are. Very interesting.

And then we'll wrap up today with talking about, as managers, what you can do within your organization to upscale your coders.

So with that, let's let's start off with just a quote. So this is, something that Henry Kissinger said that I loved, and I think we can really take it to heart. The task of a leader is to get their people from where they are to where they haven't been. And I think this is so perfect for where we're at in our industry with all of the AI technology that's coming out there and onboard and rapidly, being implemented and in use is we need to think of our teams, our coders, of what we're doing today and where we're going to be tomorrow. It's going to look very different, into the future, and we need to be mindful and and prepare our teams as such.

So if we can train our coders to think more like auditors, they'll be more pre proactive in preventing errors or mitigating risks that might come about, and just improving the overall claim process. So if we kinda take take them out of their current role, hey. Heavy production, and and have them expand, their skills and think and perform more like auditors, we're gonna see these changes evolve.

So let's talk about the business case for why we would want to do that. Well, we know that the OIG and a lot of the commercial payers are continually auditing our claims, doing prepayment reviews, post payment reviews, and they're, constantly changing their guidelines. And so we know from recent reports that there's billions of dollars that have been recovered through their initiatives of of their audits that they're doing.

And we know that whenever we have to work a denial, it can cost twenty five dollars to thirty dollars, and in some instances, as high as forty five dollars. So it depends on, you know, where you're looking at, where where that number falls, and and what type of, services you're providing within your organization. But if we take that range from twenty five, thirty to even possibly forty five, that's a lot of money that we're constantly being inundated of having to rework these, coding denials and and edits that come up.

Additionally, as organizations, we're facing a lot of compliance risks. Right? Oftentimes, we're understaffed.

There's a lot of, turnover with our coders, turnover with our billers, and it we're left to be understaffed. Or there's initiatives that we've got going on where we're doing EHR upgrades, and it's resulting into backlog. And and we're not staff we typically don't have a bench that could come in and and kinda help us, when those situations happen or, you know, seasonalities that that come up. So we're constantly fighting that battle.

We're also constantly fighting the battle of industry updates. So just this week, congress passed an extension on the telehealth rules. Right? So, obviously, we're not gonna talk about that today.

But, again, it's you know, a a few months ago, a few weeks ago, we were instructed, hey. This is this is the new guideline. This is how we have to, do things, how we have to document, how we have to code.

Congress quickly changed that overnight, and now we're we're back to, some some hybrid rules with the telehealth. So things are constantly changing than if we're not keeping ourself and our organization updated with these guideline changes. It it puts us at risk. And when we're at risk, it's a potential situation where we're gonna lose revenue.

Another business case to upscale your coders is to combat physician burnout. And so you're probably thinking, okay. Why is she bringing up physician burnout? But but let me talk through this for a minute, and you'll see.

So physicians, are getting burned out more now than they ever have before. I've been in health care for over thirty years, and I see it. I see it when I am a patient and I go into different organizations. I see it with different physicians that I work with in my job, and it's just it's never ending. And it it started if I kinda think back, this burnout kinda started with the implementation of EHRs in the late nineties.

We knew that that was something that was coming. We had to evolve. We had to go to these EHR systems for a lot of different reasons, but inadvertently, it made, documentation a lot harder and put a heavy burden on providers. So in addition to that, there's all these different value based programs that we're participating in. And because we're participating, there's additional things that have to be documented and are performed by the physicians and support staff as well. So that adds additional pressure and burden to get things absolutely perfect.

All the while, these physicians have to overcome increases in health care costs. Our economy over there the last several years, it it's expensive. Right? It it's expensive to order all the supplies you need.

It's expensive to keep, your buildings and everything going, and we have to deal with reimbursement, decreases that that come out, especially this year with the, physician fee schedule. And so all of these things are attributing to physician burnout. And when our physicians are burned out, it's inevitable that there are going to be documentation gaps. Right?

It's it's really hard when you're overworked trying to, spend time, getting the see patients and getting the documentation. Right? So on the slide, the the first bullet, there was a a study that we reviewed and talked about a lot of physicians spend thirty to fifty percent of their day just reviewing documentation and, adding their notes into the record. So a lot of times these providers are spending hours and hours after seeing patients trying to get caught up.

And we know when, the physician is burned out and and there's documentation gaps in in the end, that's gonna impact us as coders. That's gonna impact our rev cycle somehow. And so if we can help solve for this physician burnout and upscale our coders into thinking more like auditors, we can, mitigate some of these risks.

As coders, we are, not in the room with the patient and the provider when they're being seen. So we have to put together all these different pieces of the puzzle to recreate a picture that happened during that visit. And so sometimes a critical piece or several critical pieces to that puzzle are missing because all we have to rely on is what was documented.

And if there's pieces that the provider inadvertently left out or there's a workflow gap within the EHR system or template template gaps, we could be missing those critical pieces. And so, you know, it's we try our best to draw conclusions and and get those those dotted lines more solid and and put those pieces together.

But still, oftentimes, we're left to rely on what's documented and that that documentation has a lot of these gaps that we often see, acuity of the patient, the status of condition.

We see diagnoses, but no, treatment plan. So there's lack of me in the know. So all of these things we are all too familiar with as coders and as managers. Right?

And these have been, the same common doc documentation gaps that have been around for a very long time. And I I think sometimes we do pretty good at it. But they tend to to hang out there and old habits kinda come back, and and they just don't really change all of that much over time. So, again, if we can get our coders to, upscale their skills, we can help mitigate some of these documentation gaps.

On October eighth of twenty twenty four, MGMA released a survey that they did.

And in the survey, they found that four out of ten medical groups, so forty three percent of the group that they were surveying, had reported that they added or expanded the use of AI in that year, so in twenty twenty four.

Compared to the previous year, there was only twenty one percent. So that's a significant expansion just in one year. Right? So just over double the percentage of these groups, are starting to implement different forms of AI to combat some of the challenges that we just spoke about.

And I also find it's it's interesting that, this past year, fifty three percent said, nope. We're not doing anything right now. I would be, very interested to find out why. Why aren't they doing anything right now when that that would be interesting to to see those details.

So, anyway, out of, the percentage of, organizations that were implementing AI, these are the types of tools and technology they're implementing, and I put it them in ranking order here on this slide. So by far, organizations are really investing into ambient AI or spray scribing technology.

And these are tools that, the provider can turn on at the beginning of the visit, and it's just recording the visit, and it will draft a note. And what it does is it cleans it up, and it's just not a recording. It's not like drag and voice recognition or or a recorded message. The AI is really smart and savvy, and it will actually put together a clinically correct note.

Very cool, very beneficial to the provider because then now they're see they're focusing on the patient. Right? And all they have to do is review it. Some of these Ambient Scribe tools also have coding, a computer says the coding technology along with it. So it's very cool. Right? You kinda get that that, double technology advancement together.

Second, forty percent of these organizations are implementing clinical diagnostic technology, and these are diagnostic tools around radiology, screening tools, for example, depression screening, cognitive screenings, maybe your cardiac assessment screenings that the patients go through to to put their, their cardiac risk scores before they go into surgery, those types of things. So, these are very cool technologies that, instead of on paper that the patients come in and fill out, these tools are, sent over and patients can do an them in advance of the visit in many instances.

And then the provider just looks at those and they, do their interpretation, and it's it's all built into, you know so it really saves a lot of time, and they're pretty accurate.

Then there's other tools around, patient triage, which I find super interesting, because they're just leveraging existing technology like phone and texting and other means of communication to help advance the communication back and forth with with our patients. And then, of course, we see a lot of the others around rev cycle.

So within AAPC services, we get the pleasure to work with a lot of different organizations across the country. We also get the opportunity to work with these tech companies.

And we have personally been working with ambient AI technology, ambiate, CDI encoding technologies, computer assisted coding, some of these screening tools, and I can tell you I'm really excited about them. The accuracy is pretty good. It's pretty phenomenal.

And I can see as we're working with these vendors and then we're working with organizations, how pleased the organizations are and how helpful these tools really are becoming, as as we're trying to deliver health care.

So that all said, what sets auditors apart from coders?

Coders and auditors have very different approaches as they're doing their work.

Typically, a coder is going to focus more on, hey, assigning the codes, reading the provider documentation, making sure they're correct, and they're driven by production. Right? Whereas, auditors are looking more closely at the documentation.

They'll look more closely at medical necessity. They might look more closely at exactly what the payer requirements are as far as documentation, not just the coding, and then bring those things to light as opportunities. So auditors are more opted opportunity driven rather than production driven. So if we think about that, it makes sense of, the importance of perhaps upscaling our coders and an auditors and thinking more about opportunities.

So when we do that, we shift the mindset of being just reactive. Hey. I'm I'm gonna code this, get it off my desk, move on to the next one. I've gotta fix these, errors for denials that have come through to a more proactive report approach where our coders are actually preventing those errors from happening in the first place. They're taking a few extra steps. They're being a little bit more more mindful of the opportunities.

And and we'll get into more details about how we can do that. This is where the the the focus needs to be, and this is where the I AI technology is really taking us as an organization.

Alright. So let's talk about those auditor skills that we can teach our coders.

A trained experienced coder possesses a lot of abilities that are really perfect for the future of AI technology.

Coders have the strong ability to adapt. Right? These changing guidelines, like the tell the health guidelines I just mentioned previously, we have that uncanny, ability to pivot quickly and adapt to those change. In fact, we we oftentimes are very passionate about changes, especially if we can, see the benefit and and see, the into the future, those changes and how impactful we can be as a as a coder as we're a part of those changes.

Coders tend to if they feel like, they're not gonna be part of those changes, we we tend to kinda steer away from those types of things.

So it's important to to keep, that top of mind as we're working with our coders.

AI can help coders use these highly skills of adaptability, being thorough, paying attention to details, and really hone in on these skills and use them for more challenging tasks. And if we're able to do that, then as coders, we can advance our careers and advance them more quickly than maybe otherwise we wouldn't be able to.

Coders have that uncanny ability to think critically as as we're looking at, at cases and very decisively. So not every patient is the same. Right? It's not a one size fits all. And so coders, understand that, and they can apply that, particularly as they're looking at these more complex, more challenging tasks that that we anticipate that they'll be doing.

With the evolution of this technology, there are going to be new and more specialized roles for coders. Coders are, going to need specialized certifications, such as the ones AAPC offers. What about other technology driven certifications?

Lots of potential out there. Coders are going to evolve more quickly into auditing, perhaps hybrid roles.

Other specialized roles for coders could be in clinical documentation improvement, as well as educating and becoming the go to expert within your organization.

So let's dive just a little bit deeper into some of these specialized roles that coders could evolve into.

There are several areas in which human coders are absolutely irreplaceable.

Words can only paint and shape and outline the picture. It they it can't add the detail. So if we think about that ambient scribing technology, it's it's not gonna be perfect.

And there are still going to be areas where a human quarter is absolutely going to be needed to draw out those more details to ensure the accuracy complex cases, there's nuances about patient's medical history, their unique circumstances that they're in, like different comorbid conditions and how those conditions are perhaps impacting the patient today or not impacting the patient. AI just can't can't gather all of that information because AI is driven based off of algorithms and data patterns to make their decisions, and so they can predict information, which sometimes results in whose hallucinations with codes. Right? And because of that, it's never going to be a hundred percent perfect, and these complex unique cases will require a coder that has contextual judgment skills to come in and help sure those particular cases and ensure the accuracy.

We also need to train our coders to become patient centric coders. So in the past, you know, we would we would teach our coders, hey. You know, look at the documentation, look over these elements, Check them off on our our coding worksheet or our audit worksheet.

And that was great. Right? But that's not the way we do business today. That's not what the way the twenty twenty one e and m guidelines and twenty three e and m guidelines are.

We really need to help our coders, understand the patient's journey. Right? It's not about, hey. I'm just gonna code this really quick.

It's they need to understand the patient. So at AAPC Services, we developed a three pronged approach that I'm gonna talk about in just a minute. And if we teach our coders that to think, patient centric and think about the patient's journey, all of a sudden, we we become invaluable. Right?

Because AI is not gonna be able to do that. And, again, it's it's going to, allow us to to focus on the the complexity of of the rev cycle.

Okay. So in dish in addition to the complex cases, coders can lead the organization in different communications across different, departments, so, across interdisciplinary organizations. So right now, a lot of times, coders work with providers. They work with the the billers.

But why not we have them work more closely directly with insurance companies?

Why not we have them work more closely with other stakeholder holders within the organization?

There are so many different nuances, of from within the rev cycle that starts with patients being scheduled, patients coming in and being triaged by the nurse, see seeing the physician, and then getting the documentation, getting it coded, and so on. And so all of these things are important to a coder that's thinking more about opportunities and thinking more about auditing and mitigating, different issues that come up and applying root cause analysis to these different scenarios and then communicating these things within those different departments. So they really are a critical stakeholder and should be viewed that way and allow them to bring in, as part of conversations in with these different, departments.

So imagine if we implement AI and AI is going to be doing those easy tasks and those repetitive task, all of a sudden, the coders will have more time to think more like an auditor, to manage these complex cases and, specialties, and be a part of these communications and a part of the overall success of within the organization because they're gonna be bringing not only these these, industry updates, like the telehealth changes, but also, bringing them to a broader range of departments within your organization.

Coders will evolve to performing quality oversight. There that'll be more of a role that they might be doing because AI is gonna be chugging along, like I said, doing those easy routine tasks, and a coder needs to validate that AI. Like, there's always gonna be errors. AI is never gonna be a hundred percent perfect and error free.

There's a lot of technology that's really pretty good that gets us close, but it's not gonna be a hundred percent. So coders, they're going to change to a more quality oversight role. Right?

And that requires a different mindset.

They can review the accuracy and compliance of the AI for documentation, accuracy and compliance of the AI for coding, accuracy and compliance with the regulatory guidelines that continually change.

And then they can be part of that continuous continuous monitoring program very much as auditors are today.

Okay. Let's talk about, coders evolving into CDI specialists.

I really think that you don't have to be a clinician to be a CDI specialist. I know a lot of times in the hospitals, that's where a lot of the heavy focus on, because they're looking more at quality care in some of those programs.

And while we can be part of those conversations, we can really add a lot of value with our expert knowledge and skill within the clinical documentation and workflows. So So like I mentioned before, as a coder, if we're working and we're having this strong communication within our provider groups and the support staff, we're gonna be able to say, okay. I keep seeing the same error. Let me go have this conversation.

Now let me figure out why is that happening.

Now all of a sudden, they become a CDI specialist. Right? That's exactly what they do in within the hospital organization. So why can't that happen across all organizations and all different types of specialties?

And so they can they can be part of those teams, and they can be part of implementing changes that have to happen with the AI with the AI technology that's that come up because the AI has to keep up with those updates, right, just as much as we do. And so who's going to bring that forward and, work with that AI vendor to make sure sure those updates are in place? It's gonna be the coding team. They're gonna be part of that. They can be part of, putting those little nudges in the aid, AI for providers in the form of queries or even implementing a stronger query program within your organization.

All of us have those one or two or three coders in our group that tend to stand out. Though those coders that everybody goes to to ask questions for. Right? We we have all those folks.

And, this is a natural, opportunity for those go to experts to really be promoted into maybe a a more of an educational role. So as technologies are making the coding process more efficient, maybe you could create, different education roles.

And as managers, we need to be aware of our staff so we can, you know, identify those folks and the desire, for those different promotions and really encourage them and promote them and and give them the education and things that they need so that they can really be that go to expert across those different interdisciplinary teams. Right? Not just among the coding team, but across.

We really want them to, these education experts to be the liaison between those groups and the new different AI technology that that's going to be implemented within our organizations.

Okay. So let's talk about this three pronged approach that I mentioned earlier.

When I was, diving into the twenty twenty one E and M guidelines, it was obvious to me that we needed a mindset, within our department. And I thought a lot about our coders and our auditors, how we currently did things and thought about things.

And it was obvious to me that we needed to to think more clinically. And as I really worked through those guidelines and, you know, really be began to understand them, it dawned on me, okay. Wait a minute. We need to have this three pronged approach where we are, patient centric and we're really understanding each and individual patient that we're coding or auditing. We need to understand their problems and we need to understand their risks from a clinical perspective. So we don't have to be clinicians, and we shouldn't ever think that we're clinicians, but we can be patient centric, centric. So we can understand the patients by making sure that we look for the age of the patient.

We look at past medical history. So even though we're not looking for those history components like back in the old days to count those bullets, we still need to understand, okay, what's the past history on this patient? What are their medications?

What are the social factors are coming into play?

Are there any other relevant details that the provider is aware that as a coder, I also need to be aware so I can make sure that I'm applying the right, E and M leveling and I'm applying the right ICD ten codes.

Very important for us to understand the patient.

Next, we need to look at their individual problems, the problems that and symptoms that they're presenting with along with the problems that the provider has documented in the assessment and plan. Right? It's not always just about the assessment and plan. And we need to understand the acuties of these problems.

So that takes a little bit of effort and a little bit of training, and and I've got a couple of slides where we can talk about that further.

Upskilling our coders to really understand risks of treatment that the provider is recommending and or prescribing as well as just the overall management of that patient. So, you know, it's easy to say, okay.

Provider prescribed a prescription drug. We know what that risk is. It's easy to think about different surgical or procedure cases.

But what if this is a complex patient, but the provider is not going to do anything right now?

What are the risks of not doing anything right now? We need to consider that as we're, leveling those risk components. Like, for example, let's say you've got a patient that was on some medication and patient has a follow-up. They're still symptomatic, and the provider said, you know what? Let's not change the medication right now. But if you start to experience x y z symptoms or it gets worse, go to the emergency room immediately.

That's a whole different level of risk than, note that might say, hey. Yeah. Those prescription seems to be working. Yeah. You're good to go. Just follow-up PRN.

Very different risks on a similar approach, right, from from the provider that might be documented. So we need to train our auditors to think in that manner, not just not just look at the outward, treatment that are provided.

So as we teach our coders this three pronged approach, we need to teach them to get out of the box, get out of the checkbox habit, if you will, and give them a way where they can do that research. Like, they're not gonna know that these answers right away.

I still when when I'm doing production coding, I still have to to Google Google these conditions, Google prognoses, look at different symptoms, and are these, systemic symptoms or are they common symptoms that are just normally part of that? What are the risk of these treatment plans? What's the risk of of not treating the patient? I mean, all these different things are questions that we can simply type in the Internet and get some answers or even go to our providers through a physician query and ask and kind of fill that gap a little bit where perhaps, there's missing pieces and and a dotted line where we really want a strong line evidence in the medical record.

Alright. So let's talk about physician queries.

More and more, we're hearing the professional side of organizations implementing a formal physician query process, which is great. I love that. So I I started my career at the hospital, and so that was something that we've all we we always did. And so I love that evolution of the query process coming to physician organizations. But what I'm finding now is it's not very efficient.

And there's a lot of things that we can do to more formalize this process and make it more efficient so that as, you know, AI is doing its thing, doing the easy, the routine, the coders are are thinking more about opportunities and thinking about making improvements and potential missed revenue that they have the time to properly query the provider. So I wanted to spend time on when to query and how to do your queries.

So coders and auditors, as as they find missing pieces to the puzzle, they need to do that research. So they need to apply that three pronged approach that I just spoke about, and they need to do a little bit research on their own. If they exhausted that, exhausted CMS, exhausted payer policy, and they're still missing information, then this is when that they would query because we don't want to just query providers every little thing. Right?

That'll destroy their relationship and providers. We don't wanna add to that burden that they're already facing. Right? So we want to be mindful about when we query.

And if it truly is missing, then we can query that.

For example, clarify the reason for visit.

You think that that is is something that we don't have to worry about anymore. But since the twenty one guidelines and twenty three guidelines, we're starting to see not as much, information around the chief complaint and around the history of present illness. Those things are still required, for a complete note, but they're not required for for calculation of the coding. Right? And so we're starting to see some gaps around there.

We need to understand very clearly reasons for tests that are being ordered. We just looked at, audit results for twenty twenty four and finding that there's lack of medical necessity starting to bubble up and climb up the list further as, errors that are are happening. So all of these instances are really great opportunities, to query the provider.

Another instance when we should query is when there's conflicting information.

When, there's a problem list that is very different than what's in the assessment and plan, oftentimes, there might be a higher level of specificity. So, for example, we see diabetes where with hyperglycemia, that's a higher levels of specificity code. But in today's visit, the patient's stable. Their m a one c is five something.

Everything's going well, and yet that's the diagnosis that's pulled from the problem list. So, resolving those conflicts, so we're making sure we're getting to the most accurate codes is is really important.

What about statements that are very unclear, where there should be a cause and effect in a relationship and it's not there or it's very confusing. We're not sure how these comorbid conditions really come into play. A lot of times, we'll see them listed in assessment plan just listed there, but how are they impacting the patient today? We know as experienced coders that diabetes with a patient with kidney failure definitely can come into play, but how is that relationship impacting today's visit? And, of course, we have our historical, conditions versus acute or active conditions are always always come into play, when we should query. And, of course, eligibility or incomplete documentation.

When we query, you know, we've identified the, reason why or reasons why, but when we query, there's a right way to do it and a wrong way to do it. So Ahima provides excellent guidance on the right way to do this. And in the end, it really comes down to, when a coder queries a provider, it needs to be monetized. It can be verbally or in writing, but it needs to be memorialized within the medical record and prefer preferably part of that current visit that was in question.

Alright. So somehow there has to be a workflow to get that in there. So a lot of groups, either they don't have the capability when they're with their EHR to have a workflow process or they haven't turned on that feature, and they're just emailing. Well, that isn't gonna that's not compliant.

Right? That's not really go going to meet, the requirements. What if you're participating in, a risk adjustment program and there's, higher spec specificity of codes that was supported because of a result of a query, but it never makes it in the medical record. Now all of a sudden you're at risk for a callback.

Right? And there's many scenarios that could happen, that are very similar similar to that.

As coders, we need to present to the provider the facts. We never wanna lead the provider, say, hey. You could upcode if we do this, you know, that type of thing. We always want to present facts. Medical record documentation says this, or there's this discrepancy, lab results or other diagnostic tests says this.

Only present the the facts and let the provider answer.

Sometimes if there's templates, a checkbox, like a not a fill in the blank, but a a checkbox, is it this, is it this, or is it the this? Which one is best?

Works out really well because you're not leading the provider. You're stating the facts and then asking them, okay, exactly what is it?

Never tie reimbursement in with your queries. It's all about just making sure your documentation is sound and your codes that are on the claim are sound. Right? And then you, of course, wanna be compliant with your payer guidelines and with your your organization guidelines as well.

Alright. So let's talk about how AI is changing auditing.

Ambient AI that is coding aware will make coders work smarter, not harder, and transform their careers. I am an absolute firm believer of this. I've had the opportunity to work with several different AI vendors and different organizations, and I can tell you AI has made me a better coder. Right? It really has made me pause and think a little bit differently, and it's it allows us, again, to just be more proactive. So let's talk about what AI can do and what it can't do.

AI can suggest codes.

Right? It's not gonna be a hundred percent accurate. There could be some hallucinations in there.

It reduces manual entry time, and I can identify different patterns in coding and bring it, to the, person's awareness.

It can lower physician documentation burden, and it can improve the overall clinical documentation of the note. What it cannot do in is interpret the clinical intent, the severity, the way that an, auditor can. So helping our coders think more like an auditor right out the gate, is just so important and so valuable to your organization.

AI cannot recognize those different nuances with patients as well as with different payer guidelines.

CMS isn't always the most stringent guideline out there now. We need to make sure that we're mindful of what our payers want as well.

AI can't catch documentation deficiencies or, sometimes those inconsistencies that happen as well, it can't catch that. Right? It it's it's not gonna understand, that there's a potential problem there. And then it's not always gonna catch potential missed revenue where where we had a query, that we can ask a provider can then actually lead to, additional services that were performed that now can be coded.

So last week, Becker's had a webinar where they brought in several stakeholders from the Cleveland Clinic who recently did a AI technology pilot, and they settled on a vendor.

And, one thing I wanted to share with you today is the conversation around the return on investment and how doctor Bose over there at Cleveland Clinic, he he's a primary care provider, and he was one of the leaders that led this AI initiative. He he still sees patients, so he's not just, you know, graduated into a a more technology role. He's actively seeing patients and led, this pilot program.

He talked about how AI empowers hue humans. It doesn't replace humans. So they did a very intense, pilot over months and months, and and he talked about how it it just doesn't replace humans. It doesn't replace humans clinically, and it's not gonna replace coders.

He talked about how he got a lot of time back so he could spend more time with his family and spend more time going to his son's sports activities after school instead of staying having to stay and finish his notes. And so what I thought we could do is we could say, alright. AI can save a coder's time and give them time back so they're not under a lot of pressure, so they've got more time to spend with their family as well. Right?

It just resonated with me how true that this is.

They they talked about on this webinar how it improves physician retention. We talked about that, physicians are are getting burned out and and it's resulting in in these positions leaving. Well, ask yourself, do we have the same problem with our coders?

Are are production coders burnt out, overwhelmed, stressed out with what's happening in the industry, and so we're losing them. And so we have to bring new ones on, and it takes such effort to bring everybody up to speed.

You know, AI can help reduce that and really help provide a full career path growth with our coders that are are coming out.

AI can improve the integrity of the data across the different departments. And so that's what I mentioned earlier. Doctor Bose really kinda talked about how that works. So as coders, we can improve our our, data among our coder and biller department and other stakeholders.

And then lastly, implementing AI, will, present an even playing field for quality care. So as coders, we're not providing care for patients. We are definitely part of that quality of care, formula. Right? We wanna make sure those claims are right so patients are getting overbilled or undercharged and all of those different things. So we we definitely come into play and can make a difference there.

Alright. So let's quickly talk about some of these case studies.

So I do have references to these case studies at the end of the slide. So when we release the on demand and you get a copy of the deck, you'll see those reference links so you can look at these in more detail.

So this was a case study public published rather by HealthCatalyst, and it was a community health organization where they were seeing a high level of claim denials, because of comp complex coding cases that they were doing. So they had, complex specialties in cases. And because of that, they were receiving these these increased denials, and they were losing a lot of revenue. They just couldn't keep up with it. So what they did is they implemented a strategy where they upskilled their existing coding staff and created a hybrid position where they were coder auditors.

And they did that by teaching them documentation integrity, so the CDI specialist that I mentioned.

They taught them to recognize patterns of denials for particular payers. So as they're coding and reviewing the notes, they they would immediately think of, okay. They're you know, they're here's a pattern of a denial from a payer payer. We need to, mitigate for that. They, it brought them in during the implementation of AI so they could validate the AI workflow and oversee the accuracy of the AI output documentation and coding.

And as a result, they were able to decrease their denials by twenty percent, improve the first claim pass by fifteen percent, and significantly reduce their risk of clawbacks.

Huge success rate here with upskilling their coders.

Case two is is similar. This was a large hospital network system. It it was massive, and this was an article put out by MedWave and, similar case study where they implemented AI and empowered their coders and brought them in at the beginning of of this process.

And as a result, they saw thirty percent reduction in the coder time.

So they become more efficient. So imagine if your coders have thirty percent more time where they could focus on other things. A twenty percent improvement in coding accuracy and fifteen percent improvement in reimbursement, because they were able to spend more time, making sure that those complex cases and opportunities for missed revenue were were mitigated.

Okay. This case study is, something that we did within our organization within AAPC service. So we had an organization that, their physicians did most of the coding. They had a few senior level coders that would kinda look at some of the complex cases and work the coding denials.

But the organization decided, hey. You know what? We're going to lessen the physician burden, and we're gonna hire a full team of coders. So they did that, and they brought on, quite a few new CPC coders.

What they started to see is an increase in error and increase of of denials. Right? These these coders, just didn't have, some of the experience that they needed. So they brought in AAPC for us to come in and do some audit and education with these newer coders and with the entire coding team. And so we did that. And then shortly after that, they, implemented AI.

And these are some results of a reaudit that we started to do. So these are just preliminary results, of teaching the coders to think more like auditors and upskilling their their skills so that they can look for those opportunities and higher level of accuracy and then partnered with AI, what impact it can make.

Huge successes.

Alright. So let's spend the last few minutes talking about, as a manager, what you need to do to upskill your coder. So we touched on a lot of different information on the business case of why you should upskill your coders to auditors, have maybe coder auditor hybrids, what those skill sets are, the benefits. So let's talk about, as managers, what specifically you can do.

You can provide targeted training to your coders.

AAPC has a CPMA credential.

There's other specialty credentials out there. There's other credentials around technology, compliance, and maybe CVI that that you could help provide and support your team with.

You can implement a prebuilt audit. So if you've got a coding team and, they're coding the claim or just reviewing the claims before they go out the door, you could implement a peer to peer audit program where maybe a peer, a fellow coder, is reviewing a small percentage of their neighbor's claims that they coded. Right? We don't wanna do a hundred percent. We just wanna identify maybe what that what that sample is, and and maybe maybe it's a type of code or, type of service. Who knows?

But we can identify that small sampling and do a peer to peer review, and then their coder would do the same for that person. And then you have those two get together.

This is a huge, opportunity to bring success and bring success quickly because you learn so much from each other because you're gonna bring this different perspective.

And there's no pressure about a formal audit, there's no scorecard.

So it's really fun activity, and you're gonna see that change quickly.

You could pair your coders with auditors. Right? Have auditors kinda mentor them, give them some hands on learning. How do you look at this note differently? How do I learn those audit skills and those proactive skills, as a coder?

So you could do some of that. You could leverage AI. If you're going to be leveraging a lot AI, make sure your coders are part of that stakeholder team from the very beginning, not after the fact that the decision was made or after, it's implemented from the very beginning.

I am a firm believer that coders can help validate and bring trust to these new technology tools that are out there.

Implement a physician query process. Make sure you utilize as much, technology like, a workflow within your EHR system as you can and, make sure you lay out when to query and when not to and and how to query. It's really not that hard to to get that going. Sometimes we're hesitant because you think, oh, we just don't have time. But I promise you, if you do it and you do it right, it's going to make a difference on the back end. And then, of course, train your coders to monitor and measure their own success.

Right? Have them keep track of how their own production, their own quality, you know, how many coding denials are getting or decreasing. Have them part of that, not just they they get a report card from someone else. That's really gonna be a great motivation tool to to get them going.

As a manager, you have an important role.

Marwan Farah is a software engineer manager. And, last summer, I was doing some research about project management and managing staff and teams, and I came across this article, and it really resonated with me because while coders aren't engineers, we're similar in the fact that what we do is very complex.

We have very tight deadlines.

And if we don't do it right, there's there's a severe impact on the back end. And so we're similar to engineers in that way. And in this article, he talked about these eight leadership roles or management roles.

And, I I just I love what he said, and I I wanted to to bring it to light a little bit where we are making sure that that as a manager, you're your team's compass. You're providing that direction. You're providing your team's inspiration where you're forward thinking.

Get these coders out of their comfort zone. Help them embrace the AI technology that's coming because it is here and it's rapidly being adopted. And if we don't get our coders on board and upscale them, they're gonna be left behind, and we don't want that. So be that inspiration for them. Be honest and transparent in all your communication. Right? Don't hit the snooze button on top tough conversations.

Make sure that we're proactively and and working with our our coders individually and as a group.

Invest in your team.

Invest in their training and their education and helping them to upskill.

Teach them to own it. Right? As a manager, you're accountable for that team, but they are just accountable individually and as a team.

So help them, own everything that that department is, and and, help help them be part of those solutions.

Embrace the task swapping that I mentioned earlier.

I know it seems like we just don't have a lot of time for this. So you don't have to do all of these things all at once. Just pick one or two things and and get them implemented and get them moving along and then do something else.

Make sure that if there's a crisis, you're handling it and you're the lighthouse captain. Like, make sure that, hey. You know what? We I always tell my team, if we make a mistake, it's a paper mistake.

We're not impacting a patient's life here. We're not impacting, you know, the world. It's just it's a paper mistake. Paper mistakes can be fixed. Let's dig in and figure out and fix it. And then make sure that you love your team.

That goes a long way if your team respects you and you respect them and and they know that you have their best interest in mind. So just wanted to leave you with this quote. In the changing climate of health care, a manager's role is to guide their coder team to reach their maximum potential. I think we could all agree with that.

We first need to recognize there are no boundaries on how you motivate and lead your team. You know your team best, you know their personalities, you know their skill sets.

And so what we talked about today are suggestions, but take that and run with it.

Think outside of the box and, you know, think about the future and the future of technology and where we need to be.

Once you do, you will be able to successfully navigate the impacts of change and ensure your team's success. So, Cordell, I think we've got two minutes left. I don't know if we have any pending questions that we could review real quick.

Yeah. We do. In fact, most of the questions that you came in, you answered over the course of the presentation, but, we've got one or two, I think, still left open.

One of them being the lack of staff slash knowledge has definitely been a factor for our, for our practice. How can we use AI to help go out, to help claims go out clean the first time? For example, can we use AI to recommend CPT codes based on an operative note? How do you do this in a HIPAA compliant manner?

Great. Great question.

There is AI that can look at that clinical documentation and suggest an e and m level. I have sent seen some AI that will look at a procedure note and make a suggestion for that. Now the technology isn't as advanced on the surgical cases, at least not what I have seen so far, but it's getting there.

So I think, a first step is looking at the different AI technology that is out there. And maybe on a whiteboard, identifying where your biggest opportunities are. Is it implementing AI during the the rev cycle process of, billing?

Is it, at the front end at documentation? Is it in the middle at coding? And look for a vendor, AI vendor that's out there and, look at that potential use and the benefits of that. Another approach is, if you're if you're not able to implement AI quickly, it's it's an investment, takes time, Then there's things that you can teach your coders to look at now.

Maybe do that cross training and mentoring that I mentioned and, maybe split up the work, among different teams where maybe you've got a junior coder working with a more senior coder on some of these advanced cases or specialties, and having them do a few while your senior folks are really, you know, turning through that production. So you're incrementally teaching and learning your more junior coders and upskilling them. So, there's a lot on AI that we could spend time. We don't have time today, but, keep monitoring, keep your pulse on the different technologies that are out there, and, keep keep the conversations going within your organization so you can, be ready when when it's time to implement.

Okay. I know we're past time, but we did have a lot of questions come in around queries. One in particular is you mentioned that if the query to the physician does not memorialize, then it does not meet the requirements. Are there official guidelines for queries? And if so, where can I find them?

Great question. AHIMA has an official guideline policy that is great. So you wanna pull that down, and then also you wanna look at your payer contracts, and then take all of that information to your compliance manager or director, and then develop your own internal query process.

Perfect. That, Ahima, link actually in the toolkit was shared a couple of times in the chat, so you can find it there. We'll also go ahead and record, add that to our references, at the end of the slide deck that we will be sending out later this week.

Also, with that slide deck, you'll get an on demand recording of this presentation. And with that, I wanted to let everyone know that if you are interested in, talking to Stephanie and her team about her own audit and coding services and how we can support your goals, you'll be able to do so once this webinar, is closed out. So thank you, everyone. Thank you, especially Stephanie, for the presentation. Appreciate everyone's time, and hope to see you next time.