On-demand webinar
InterQual AutoReview: Optimizing UM with Automation and AI
Learn how hospitals and health systems can optimize and transform their UM programs.
In this webinar, you’ll learn how InterQual® AutoReview can help hospitals facing rising costs and labor shortages streamline their utilization management (UM) processes. It features a demo of how InterQual AutoReview applies artificial intelligence (AI) to electronic health record (EHR) data to create and populate medical reviews. We’ll also highlight how hospitals nationwide are leveraging medical review automation to gain much-needed efficiencies. Hear from Laura McIntire, RN, BSN, MA, as she provides lessons learned from UM transformation journeys of early adopters.
Heather Vollmer:
Hello everyone and thank you for joining today's webinar, Interqual AutoReview: Optimizing UM with Automation and AI. My name is Heather Vollmer with Optum, and I will be your host today. Before we begin, please note the following housekeeping items. At the bottom of your audience console are multiple application widgets you can use to customize your viewing experience. If you have any questions during the webcast, you can click on the Q&A widget at the bottom of your screen to submit a question. If you experience any technical difficulty, please click on the health widget. It covers common technical issues.
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Laura McIntire:
Thank you, Heather, and good afternoon everyone. My name is Laura McIntire. I lead our strategic client teams for Interqual. I've worked for Change Healthcare for many years, which is now part of Optum. I'm a registered nurse with a Bachelor of Science degree in nursing and a Master's in Healthcare Administration. And I've been in the industry for more years than I'd like to count. But it's a pleasure to be here today to share with you how Interqual AutoReview can be used to help optimize your UM program, and to share a little bit about how some of our customers, who are using AutoReview, have realized success in their UM transformation journey with this capability. So I'm excited to be here. So to start off, I wanted to share a little bit about some of what we're all seeing and feeling in the industry, because regardless of what type of organization you work for, we're all facing challenging times across the healthcare industry globally.
There's a global nursing shortage. As a result of the pandemic, we've seen this thing, that we're dubbing the great resignation, across healthcare, which really further compounds this problem that's been building for years. And honestly, there's really no clear path to how we're going to really reduce that nursing shortage or how we're going to really reduce that gap in nursing resources. To compound things, we've got an aging population that brings with it more complex care needs, and those numbers are just continuing to grow. We also know that access to behavioral health and mental health services is incredibly challenging right now. And compared to other industries, we have really outdated technologies and a tremendous amount of inefficiency in our systems. Our processes are all highly manual. They're tedious, they're fraught with error, and authorizations are really time-consuming. To add on to that, the back and forth between hospitals and health plans is incredibly burdensome for anyone that's involved in that process.
And as we all know, costs are still continuing to rise. So since the onset of COVID, we're actually seeing denial rates rising. They've gone up about 11% nationally. And we know that the entire appeals process is a challenge, a challenge that's resource intensive and burdensome. We also are seeing that success rates of appeals are declining, so increasing the lack of resources to prevent and work those denials, which means we need to be diligent about getting the right level of care from the start. So we're really at a tipping point more now than ever, and we're really needing to look at what opportunities and capabilities exist out there to help reduce the burden, to help offset the impact of the nursing shortage, to help ensure that we're doing things accurately and appropriately from the start, and that we're doing the best we can to manage costs in the most efficient way possible.
So I'm going to talk a little bit about how we can think about automation. It's not all doom and gloom, right? We've got a lot that's going on out there in the market. If you've been thinking about how to transform your UM program, there's a lot of things to be thinking about and a lot of capabilities to look at out there. At Change Healthcare, now Optum, we've been looking at technology to help drive efficiencies in the process, the workflow processes of today, for more than a decade. It's incredibly hard complex work. And to be blunt, there's no silver bullet out there. There's no silver bullet solution that's complete or perfect. Capabilities like artificial intelligence and robotic process automation are evolving. We know that the industry standards, think fire, you hear fire in any article or any podcast you're listening to, related to healthcare, industry standards like that are also continuing to evolve.
So we're not quite there yet, in terms of having an end-to-end, all encompassing perfect solution. But we don't need to wait until technology is perfect. There's still a tremendous amount of value to be gained by taking advantage of capabilities that are in the market today. Transforming your program with these automation capabilities really can help reduce administrative burden. We know that they can help drive accuracy, and also foster collaboration between payers and providers, really trying to build trust, because we all know that's lacking today. So anything we can do to employ machines to do what they're good at, can free up resources, those precious clinical resources, to do what they're good at. So with staffing challenges that I think we all have today, we can really take some of those routine tasks or basic tasks, that are high volume, out of the equation, freeing up clinical staff and allowing them to focus on more complex patients, and thus being able to get to a state where we can actually begin to manage by exception.
So I think it's a place we all want to be. I'm going to talk a lot today about the Interqual AutoReview capability. I'll jump into some case scenarios and do a couple of demonstrations for you, but just to talk a little bit about it before we jump in and start. At Interqual, we've got a team of clinical consultants who have done thousands of audits, chart audits, case audits, to really help our customers optimize the use of Interqual in our capability solutions. And in that audit process, we have found somewhere around one out of three cases have some sort of error, or some sort of inaccuracy, or some sort of process that they didn't package up the case in a way that made clinical sense to a health plan and therefore getting denied or they're challenged with it. So whether it's the right subset being selected, whether it's driving to the right level of care, or whether it's finding criteria that's validated by data that exists in the EHR, it could be any of that.
And we know that AutoReview, Interqual AutoReview, can help solve for a lot of that. It really can drive to accuracy, because we're populating a medical necessity review with data from the source, the source of truth, that EHR, and we're automatically creating that review without having a human even intervening it. So that drives trust and defensibility. A little bit about Interqual AutoReview, and just give you a little background if you're not familiar with it. This is a capability. It's a cloud-based solution that automates the medical necessity reviews at the point of admission decision using real-time data from your EHR. This robotic process automation capability directly integrates into your workflow, which is critically important, and I'll talk a little bit more about that as we move forward. But with the admission order serving as the trigger to begin the automated process, the process kicks off when that admission order hits the record. It creates a medical necessity review.
It populates that medical necessity review with the data in the EHR, and completes that review. So it extracts that data, structured data and unstructured data, from the EHR, and transmits that review with the embedded data back into your UM workflow. Okay? This is where your staff can then access that review. For the ones that are fully completed, they can validate that that's appropriate and correct and send it off to the health plan the way they normally would, or if it's only partially completed, they can edit it or finish the review, if you will. And it will also provide a notification back to the EHR. So really exciting to think about the possibilities here and to think about the cases that we maybe can take off the workload of the care manager today.
As I mentioned, it integrates directly into the workflow. And from a workflow standpoint, just to give you a sense for where InterQual AutoReview comes into play, you may have a patient that presents to the ER or the ED, they're triaged, and there's some sort of clinical assessment process that occurs. And once the clinician or physician makes a determination that the patient needs to be admitted to the hospital, regardless of whether or not it's observation status or an inpatient status, the AutoReview capability is going to trigger, and that AutoReview will trigger and continue to run for the first 24 hours. It will collect data and it will populate that review for the first 24 hours, automating that episode day one review for you. So really saving a lot of time for the care manager in trying to gather that information and do that work from the start.
So to recap, it's integrated the workflow, it automates the review by triggering from the point of admission order. It continues to collect data for that case, for the first 24 hours, and populates the criteria, the InterQual criteria, not only with the check mark indicating that that criteria point is met or not met, but it also embeds the data, the EMR data, and its source, date and time stamped, and brings it right into your UM system. Under the covers, what we've done is tagged the words within InterQual to standard nomenclature databases, and we have a rigorous process from mapping the data to make it machine-readable, and we perform a technical and clinical validation process to ensure accuracy. And AutoReview is going to select the appropriate subset, based on the admission diagnosis. It's going to select the appropriate level of care and the corresponding criteria points, based on that patient severity, the interventions that have been delivered, and it's going to be defensible and clear because it's going to have that actual data coming from the record, embedded as that source of truth.
Today, this capability is available in the market. We are able to automate over 80% of condition focused reviews for the admission day. So that first episode day, while we're not yet able to auto populate all data points, we are able to fully complete about 15% of reviews to a level of care. And for those that were not able to fully complete, we can populate about 75% of the criteria needed to complete that review. So there's a tremendous amount of value in those that we can partially complete as well. I don't want to discount those, because I think that piece is incredibly important. So for example, if you're doing a medical necessity review and there are four criterion that you need to collect, four data points that you need to collect, to complete that review, we can capture and populate three of those. So if we're not able to fully get all of them, we can get at least three of those four.
So that means the user simply needs to open up that automated review, find the single criterion we were not able to collect or not able to verify or interpret, and they can simply check that record to see if that criterion can be manually completed. So the amount of time savings can be substantial. There's always going to be some criteria that are challenging to make machine-readable, such as things like the word "greater than baseline." These are things that are going to require a clinical interpretation. They're a little bit harder to get at, a little bit more challenging for a machine to read and accurately interpret it, because if we can't ensure accuracy is there, we're not going to have that auto populate, we're going to still rely on care managers or utilization managers to go in and verify those criteria points. But lots of value still to be had, whether it's fully met to a level of care or even just partially met to that level of care.
And because AutoReview is a cloud-based technology, we also include, along with it, a really robust reporting platform. This is where you can monitor how many auto-reviews are generated. You can track user adoption as well as productivity measures, such as the number of reviews that users are completing. Our reporting platform has interactive drill-downs. It really allows you to focus on the data that's pertinent to whatever issue is at hand. So we have encounter level data that allows you to look at UM behaviors on a case-by-case level. We have performance visualizations that allow you, at a glance, information so you can see how the AutoReview capability is performing. We have productivity reports by user, by facility, by subset, lots of ways that you can drill down and figure out how things are going or where you might have opportunities to improve.
We even have observation versus inpatient data, along with estimated ROIs, and many, many, many more things. Our platform is also somewhat customizable. So if we don't have a report that you're looking for information on, we can work with you to figure that out. But our AutoReview customers, today, are using these reports, really to their advantage, trying to keep their finger on the pulse of what's happening across their department, and improving the results by taking action based on them, whether it's individual user education, whether it's process changes or process improvements, or maybe even system updates. So I'll talk a little bit more about that when we get into the results.
Okay, so let's jump in. Before I jump into the demonstration, let me walk through and set the stage with a patient case scenario. So I'll take you through this, and then I'm going to move over into our application to be able to show you what AutoReview would look like. So in this case scenario, we have an 89-year-old patient that presents to the ED with a three-day history of shortness of breath, cough, weakness, and fever, that started that morning. In the ED, He had 02 SATs that ranged from 85 to 87% on room air. Looks like he was placed on three liters of nasal cannula. And then his 02 SATs came up to somewhere around 93 to 97. He had orders to be admitted for community-acquired pneumonia. He started on antibiotics. He got some IV fluids. He had a chest X-ray that showed right lower lobe infiltrate, and had a bunch of standard blood work, urinalysis, cultures, things of that nature.
You can see in his vitals that his blood pressure was low on arrival, his temperature was low grade. He had a couple of abnormal lab values there. BUN elevated at 42, sodium was 132, his UA was negative, COVID was negative. Definitely has a white count that's elevated, and those blood cultures are still pending. So let me move over. I'm going to move over to the application. Share that screen with you. Now, when we integrate Interqual AutoReview, we integrate it into your workflow application and run against the EHR, so we don't have access to that. So what we have here is our Acme care manager FIG tool that we've created, to be able to demonstrate and show you the capabilities. So when you have AutoReview integrated, and you go in and you access the case, and you click on it, just like I did, it's going to bring you right into that Medical Necessity Review. And you can see that the Medical Necessity Review has already been completed for me.
I don't have to actually do anything with this case other than take a peek and say, I'm going to send it off to the health plan. And there's a couple of things I'll point out to you. You can see that the acute level of care has been met, and you can see we have some gray text to the left of it here with some arrows. EHR updates complete. This means that the AutoReview capability has run for 24 hours or more. Once it runs for 24 hours or more, you'll see that it's complete. And if it was still running, meaning it was less than 24 hours, you would see that this circle, these arrows would be turning in a circle, and it would say "EHR updates are being gathered." So it's continuously gathering data. So as additional data comes into the EHR, maybe it's imaging results or lab tests or other orders, it's going to continue to collect that information until the 24-hour mark.
But in this [inaudible 00:18:25] of care was met and somebody decided to complete the review, and that's going to stop the AutoReview from running. And in this case, acute level of care has been met. When I click on acute level of care and expand, I can see that it says "Pneumonia confirmed by imaging," and it's a both rule. And I expand that, I'll see the findings and the intervention. So I'm just going to expand a little bit more so I can show you here what we're looking at for the OBS level of care. And if you look at "Pneumonia confirmed by imaging," you're going to see a file folder next to it with some little dots in it. That's called an ellipsis. You'll also see other criteria points have folders next to it with a plus sign. That is a visual cue or an indicator to let you know that there is EHR data that has been collected relative to that criteria point.
And if I were to click on this one next to "Pneumonia confirmed by imaging," it's going to pull up for me the imaging results. So this is the imaging, test imaging narrative. I can see that chest CT angiogram was done. I have the ability to click on these little plus signs next to it. And you're going to be able to see the narrative summary. You're going to see some text that might be highlighted that the AutoReview capability is focused on. In this case, it's saying "Bilateral multifocal brown glass opacities and nodules likely reflecting multifocal pneumonia." If there's multiple results, you're going to see multiple results in there. And so it is confirming that there is likely a pneumonia by imaging. So that one was checked. You're going to see that some criterion are outlined, but they are not filled in. That means that the AutoReview capability found data, but it either did not support the criterion or we were unable to make a full interpretation, and the user needs to come in and take a look at that.
I can take a look at these two criterion and see what's happening in those folders if I want to, but I don't even have to do that for this case, because this patient is meeting at the acute level of care because they have a pneumonia confirmed by imaging. They are meeting the CURB-65 criterion, and they are meeting the imaging component... Sorry, the intervention component. Excuse me. If I were to look at the CURB-65 criteria, we can see that the system auto-selected four components. There was no confusion that we mentioned in our clinical scenario, but we did mention that he had a BUN of 42. So that meets this criterion. And if I were to click on that file folder, it's going to tell me what the code name and description are. It will tell me what the recorded values are, and if there's multiple values, those would be listed in here.
This is just a demonstration, so the numbers might not be accurate here. This is just pulled together for demonstration purposes. But it will show you all of the results for a BUN, it would show you all of the results for the respiratory rates. So any recorded values, date and time stamped, for what this individual's respiratory rate was, what the value was, where it was found in the record, and the timing of it. So we know that he was tachypnea, we know that the blood pressure was on the low side, and we know that this individual was elderly. So from the facts of the case, looking at what was found in the EHR, this is exactly how it would work. It would auto-select the criteria points. And we know that this patient was also receiving anti-infective. And again, we could pull this up, we could see that he's on ceftriaxone, one gram, and 50 milliliter piggyback, and how many times it was administered at the time the data was collected, date and time stamped.
So it's going to pull all the information, whether it comes from the MAR, whether it comes from vital signs, whether it's a diagnosis, it's really going to pull all the data that it can to be able to satisfy that review. So that's an example of a case that's fully met. And the user would simply take a look at this and say, "Yep, this all seems great. I'm done. I don't need to do anything. I don't need to hunt in the EHR. I don't need to find any data points to pull together for this review. I'm free to send this off and move along to my next case." So I'm going to close this one. I'm going to come back into our homemade application here, and I'm going to open up another case that was only partially met. So I want to show you what it would look like if the review was only partially met.
In this case you'll see it says partial, so it did not fully meet the level of care. And I can open up any of these levels and see what data it was able to gather. So if the request is for the patient to be inpatient, we'll start here again. And again, it's got "pneumonia confirmed by imaging," it has some of the finding criteria, and it has that intervention for anti-infective. So it did meet for the intervention, it did meet for the CURB-65 criterion. And then there's a couple of other things that maybe couldn't be confirmed. We can look at the imaging study for pneumonia, and we can see that it is able to pull some of that data and be able to read what that imaging narrative is, and we can see that it does say "Right lower lobe pneumonia infiltrate as with underlying pneumonia."
So it's telling us that it is believing that this is pneumonia. And for this case example, it wasn't able to fully read that, or read it with enough accuracy and confidence to be able to select that criteria point. But as the user, I can go ahead and select that and say, "Yes, I want to select that criteria point because I am verifying that that is accurate and it is true based on that imaging study." And I don't even have to go out to the record to find that. So it is able to pull some of that. Same thing with this one here. You can see for two lobes, there's a file folder, and I can pull that open and take a look at what it says. And it doesn't say that there's two lobes, it says it's a right lower lobe. So this criteria point is not met, but it is providing me that EHR data in there to go along with my case and help me paint that picture.
So that's how it would work if it was a partially met case. I would come in, I would look at the case, I would see what was met, see where we maybe weren't able to find criteria or maybe where we weren't able to satisfy it enough that we could check that criteria point. And I can finish the review myself, but I don't have to go hunt for the anti-infective. I didn't have to go hunt for the CURB-65, I didn't have to go hunt for the imaging narrative. It's all been pulled in here for me, and I just need to verify it and complete it on my own. So fairly straightforward, fairly simple. Those are just two examples of how the AutoReview capability works and how it looks. So let me close out of this and I will stop sharing that screen and come back on over to the review here.
So those are our two examples to walk you through around how the AutoReview capability would work. Depending on what system you're in, like I said, we're able to do some things a little bit more robustly in Epic than we are in Cerner, but we certainly can provide information in Cerner that helps you to complete that review. But we're still working on evolving the capability. As I mentioned earlier, there is no perfect capability that exists out there in the market. These technologies with AI and robotic process automation are continuing to evolve. So we keep growing our roadmap and keep building functionality and capability to help evolve things as time goes on. Today, we've got somewhere around 150 hospitals or so using AutoReview in the market. And when it comes to UM program transformation with automation, there's a tremendous amount of lessons that we've learned. We've got lots of hospitals in various stages of implementation, and as we continue to grow, we're seeing over 25,000 automated reviews occurring on a monthly basis.
And that number is just continuing to tick up. But as we implement and integrate our customers, we're learning a tremendous amount about how we can tweak and massage things to make them work better, how we can help our customers to do things different or better. So we're learning from our users, we're continuously improving this capability and evolving our solution as the industry standards evolve and change as well. So really exciting to think about what we can do, and to see some of the successes that we have within the market. So when it comes to automating with a capability like Interqual AutoReview, with those 150 or so hospitals that we have, we've learned that when it comes to UM program transformation with automation, it's really a three-legged stool to reach success and value. And the three legs of that stool are really looking critically at your systems, really looking at your processes, and looking at your people.
And we're finding that if you're not focusing time and attention on any one of those stool legs, if you will, it's really hard to see the success and the value that you want to get. So let me talk a little bit about that, because when I say clinical systems, I'm referring to your current technology infrastructure. And this really has to be the starting point. Because if your technology isn't ready for transformation, the processes and the people, those legs of the stool, really don't matter, right? You've got to have technology that is ready and it's right for receiving the AutoReview and being able to drive those efficiencies. So some questions to ask yourself is, has your EHR been upgraded in the last 18 months or so with fire servers and web service availability? Those kinds of things. We really need to make sure you're on a current EHR version or if you are thinking about upgrading, keeping that in your mindset as you head up on this journey in terms of the phases and stages of getting to automation.
Also your UM or CM workflow tool, are you on the latest version? Is it compatible for integration? And will it allow for this type of automation capability? So lots to think about there, for sure. And then when it comes to processes, it's really important to step back and understand the impact that the automation is going to have on your processes and your workflow. Really thinking about what you want your future state program to look like, because now is the time to be able to make some changes and maybe tweak some processes to help optimize how the capability is going to work. And then the last piece, last but not least, is the people, right? When it comes to people, they're really going to be your key to success. We've learned that change is hard, and change comes hard to some folks, especially where we've got an aging nursing workforce. And we often don't spend enough time or invest enough energy in preparing our teams for this type of change.
So I think it's critically important to ensure that you've got a really good go-live readiness plan, that you're thinking about allocating your resources in the right way, and that you're really clear with your goals and your key performance indicators or metrics of measure, what metrics matter to you and how you're going to measure those to define your success and bring your people along on some of that journey with you. You can have the most advanced technology on the market out there, but if you don't have the people that are willing to embrace it, and really stepping up to be champions to envision this future state, can really make or break your process. It's also a really good time to be thinking about staff competency and what else you can do to bolster people and get support around moving towards automation and technology. People get afraid that when you bring in a technology or a capability, it's going to diminish their value or potentially reduce what is needed from them.
And that's not the case. We are just not finding that to be the case. We often talk with our customers, or our customers that are thinking about the AutoReview capability, in terms of the efficiencies and the time savings, which can translate to a lot when it comes to FTEs or resources. I can tell you, though, we've never encountered a customer that's decided to cut their resources because they've been able to employ a capability like this. I think we all can appreciate that with staffing shortages and challenges, we don't have enough people to do the things that we want to do, and it's very infrequent that we encounter a hospital that's able to do all of the medical necessity reviews or the due diligence when it comes to other functions for UM or CM or discharge planning, or other programs that you're looking to do, because you don't have the resources to do it.
So we definitely are not seeing that there's a resource attrition, but we're seeing that people are able to reallocate resources in places or do support programs where they can really have an impact and make a difference. So super exciting to think about the potential, right? If you think about taking some of the routine ropes, basic cases off the plate, really the impact can be transformational to free up your resources. So let me share a little bit. This is a compilation of some of the real world results that our customers are achieving and seeing today with the Interqual AutoReview capability. We have an organization that's seen a 76% decrease in medical necessity denials over one year. Now, is that a hundred percent related to Interqual AutoReview and what that can deliver? No, probably not. But it's a combination of utilizing the Interqual AutoReview capability, and them employing some clinical and technical workflow improvements.
So bringing our capability in really gave them some support and guidance for really digging in and rethinking some of their processes in ways that they could do things different, do it better, and do it with more accuracy. And those results are translating to real-world dollars for them. We've seen an organization decrease their condition code 44s by 56%. The automation is really what allowed for them to be able to do more reviews earlier on in the process, and therefore patients were being placed in the right level of care the first time around, or cases were being escalated to a physician advisor with partial information earlier on in the process. So if you're getting it right from the outset, you don't have to go back and make changes after the fact. So reducing condition code 44s by driving to a more accurate level of care from the outset.
We have an organization that has had 6.2 FTEs, and it translates to somewhere around a million dollars in annual savings. And again, not that they were cutting staff, but they're able to increase their staff productivity with review volume, enough volume that it's equating to somewhere in the order of 6.2 FTEs from their old manual processes. So 6.2 FTEs that they don't have to hire. Doing more with less. It's translating to over 40,000 reviews more a year that they're able to do, saving them some, again, real dollars in being able to take their staff and stretch them further. So really exciting results we're seeing with that customer. We have another customer that has had 78% of reviews being automated. This customer is really exciting because when we say automated, we mean automated either fully completed or partially completed, but they achieved this result by rolling out AutoReview, recognizing that the results that they were getting or hoping for were not coming to fruition.
And when we were able to dig in with them and help them understand what the root cause was around that, they needed to change a single process that they had with their physician documentation, and help them optimize or really ignite what was being able to be automated. So they started out with 7% of reviews being automated, and when they made this change to their process, they went from 7% to 78%. So really impactful changes just by digging in and looking at the data saying, "Why the heck aren't we getting more automated reviews here?" So really super exciting to see where that customer has been able to take AutoReview and really help them on their transformation journey. We have a customer that has had somewhere between 30 and 40% decrease in the time to complete a medical necessity review. This is really what we're seeing on average with our customers.
We can really cut the time to do a review down. So if you think about those partial reviews that I mentioned, where we're able to get some of the data, but not all of it, they're able to complete that review in significantly less time than what they were doing previously. And then the last statistic I have on here, is that we have a customer that has seen a 13% overall decrease in the time it takes to conduct that first review. And this is really exciting because if you come in to start your work day as a UM nurse, and AutoReview has been running, and you're looking at your work list or your work queue, and many of those reviews are already fully completed for you, and others are partially completed for you, well, you can just see how your work day can be much easier, and how you can get to more reviews quicker, reduce that lag time, and really be able to increase your productivity.
So super exciting results, and these numbers are just going to continue to grow as we evolve our capability and learn from our customers. But that robust reporting capability that we have is really what's helped us to help our customers dig in and really be thoughtful about making meaningful changes, whether it's to their systems, whether it's to their processes, or whether it's with their people. It could be any one of those. And again, that's the three-legged stool that we've seen to really help ensure and drive success. Okay. So just in summary, what I've shared with you today around AutoReview, really AutoReview is designed and intended to help you reduce administrative task burden by driving efficiency, really reducing the burden of that manual review process by integrating directly into the workflow. So you're not going outside of a medical necessity review to be able to find this information.
It's pulling it right into your workflow. So really having that integration in there is really going to eliminate the need to toggle in and out of disparate systems and bring efficiencies. We also are driving to accuracy. Interqual AutoReview is not a black box capability. There's many black box capabilities on the market with promises of AI, and promises of having you eliminate the need to be able to do a medical necessity review overall. We don't believe that that's the route to go. At the end of the day, Interqual and AutoReview is founded on the gold standard, evidence-based InterQual criteria that many of you have been using for a long time.
It really creates transparency and leaves no guesswork for health plans as to the validity of the need for care at whatever level is being requested. So when we compare results of AutoReview with manual case audits, we know that the automation really brings accuracy in the form of getting to the right subset. We're looking at the codified admission diagnosis, the driver, the reason for being there, and we're getting to the right subset. We're driving to the right level of care and the right criterion, being selected and supported with the source of truth, really to ensure accuracy. And then lastly, this capability really is also designed to help foster collaboration and trust. We know that there is still a lot of challenge between payers and providers in the market. We write InterQual and sell InterQual to both sides. We don't write it for one side or the other.
We really try to toe the line and write the criteria based on the evidence. And our goal and ideal state is to help foster collaboration by providing a capability that both sides of the equation can use and can trust. And I know that when we're out talking to health plans, they have a real interest and intent to automate their off decisions based on data that comes from the source of truth that they can trust, that's not been manipulated by a human. So I think our future and where we're headed from a strategic trajectory is really exciting to think about those cases that we can just take off the plate. No one's arguing if a STEMI needs to be in a hospital inpatient level of care, whether you're the hospital or the health plan, we're sort of all in agreement with that.
These patients are sick and they're complex. And yet we're still doing medical necessity reviews on the hospital side, on the health plan side. There's a lot of back and forth, and looking for clinical information to validate and support it. If we can take those things out of the equation, we're really going to be able to make some significant strides, and really automating on the front end has such a tremendous capability to help transform how we operate in the future. And it's really just the tip of the iceberg when it comes to meaningful transformative change. So I hope you found this helpful. I think we're going to pause and maybe take a couple of questions here, but I hope you found this helpful.
InterQual is here to help you along that journey. And for our customers that do choose to license Interqual AutoReview, we don't integrate this capability and then leave You on your own, we do provide consultative services to ensure that you're optimizing the use of it, and that we're really helping you be thoughtful about your people, your processes, and your systems, and making small adjustments to make sure that these kinds of capabilities can really help you and really drive meaningful efficiency. So would love to see you consider Interqual AutoReview. So Heather with that, I think we're going to pause and take a few questions.
Heather Vollmer:
Yes. Thank you so much, Laura. Before we get started with the Q&A portion of today's webcast, we'd like you to take a moment to remind you of the survey located beneath the slide deck area within your audience console. We'd love it if-