May 24, 2023: Diana Nole, EVP and GM for Nuance shares how they, alongside Microsoft, are shifting the healthcare technology landscape with DAX Express. How is AI changing the landscape of clinical documentation in healthcare? What are the features and capabilities of DAX Express that make it an appealing solution for physicians? How can standardizing data and improving information exchange between payers and providers enhance the selection of appropriate patient cohorts for clinical trials? How can AI assist in resolving issues related to waste, errors, and payment discrepancies in healthcare, particularly during the prescribing process? How can AI assist physicians in guiding the differential diagnosis process and continuously improve through machine learning?
"The Future of Care Spaces" is an upcoming webinar that explores the latest healthcare technologies and solutions transforming care spaces in America. Hospitals, clinics, and at-home treatments are all affected by the advancements in healthcare technology, which can improve workflows, treatments, and patient outcomes. What are the latest remote monitoring tools, advanced telehealth solutions, and other innovative technologies transforming care spaces across America? Join us June 8th, 2023 1:00 PM ET and Register Here
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This transcription is provided by artificial intelligence. We believe in technology but understand that even the smartest robots can sometimes get speech recognition wrong.
Today on This Week Health.
I continue to say the patient is probably the most underutilized piece of the patient care journey cuz most of us at patients. We go to the doctor's office, we try to absorb everything we can, and then we leave and maybe we go back to our portals and ask questions, but it's just hard to track.
Today we're doing a solution showcase and I'm excited to have Nuance communications Here. We have Diana Nole, E V P, and GM of Nuance Healthcare, which is a Microsoft company. Diana, welcome to the show.
It's great to be here with you again, bill.
Well, I'm looking forward to the conversation.
As you said, again, we did record this at HIMSS and when I listened to the audio I was so sad cuz it was such a great conversation. But we're gonna try to reprise it and cover some exciting things that are going on. I know a lot of discussions around this space. In fact, I can't escape the discussions around this space, and there's just a lot of things going on, but maybe you could level set us a little bit.
Can you explain maybe in simple terms how AI is changing the landscape of clinical documentation in healthcare.
Well, as bill, artificial Intelligence has been around for some time. I mean, we've used artificial intelligence in terms of conversational AI for decades, for many years, with our Dragon Medical One solution.
And then three years ago we went into more ambient artificial intelligence, where we introduced our World service DAX solution, dragon Ambient experience. I think why it's back in the news and is so top of mind everywhere is with the what people will refer to as generative ai, and it's just the level of computing power and the elements of how many components can you run in these models Now, these large language models and the levels of sophistication, The empathy, sympathy, the almost human traits that they're exhibiting is just the continued journey from what we've been on.
But it has been around and now it's just getting, again, it's just getting better and more sophisticated and able to handle even more complex problems, if you will.
It's interesting because in healthcare I just read, Stanford's going live with a Microsoft well actually a partnership with Microsoft and Epic around responding to notes and that inbox problem has been around for a while and it's reading the notes and it's creating the draft message for the physician to look at.
And these models are evolving. Pretty rapidly, it feels like. Yes, it's been around for a while, but it feels like they're evolving more rapidly. Is that just is that a, an accurate feeling do you think?
Yeah, I think it is an accurate feeling. And in fact, when they talk about the patient notes, I've read some of the same articles and they talk about the level of empathy, right, that these models can demonstrate, which indicates how much they're trained on and so quickly, And with Dragon Medical one as an as one solution that's gone through this journey.
It took probably 10 years to really get to the level of accuracy that allowed the the clinician to, to do almost no edits at all once they did it. So the level of accuracy, again, took 10 years. This latest technology that's around if it's around generative ai. Is probably half that time. It could be less.
I mean, it's just the computing power combined with these ability to run these large language models on so many more parameters. You're very well your thought processes really sound in terms of thinking that this is happening so much quicker. So where we're gonna be in two to three years is even more exciting cuz it's finally also getting to the point where, A lot of AI has been used on niche solutions, very focused areas, sometimes back in more research areas, and what I think everybody is excited about now is the scalability and sort of the forefront of the things that it can solve.
Around these tasks, these administrative tasks bringing forward insights into the clinical documentation, looking for misinformation, at least offering suggestions. Now where it goes and how far it goes is the other end of this spectrum, right? Where people say, how far can it go? How far should it go?
That's kind of the other side of things. Yeah.
Talk to me a little bit about DAX Express. So, There's pilots going on this summer, and I know I've talked to a bunch of CIOs. They're excited to get in line for this pilot. Why are they excited to get in line? I mean, we have DAX today. It's highly accurate.
What is Dax Express gonna do over and above what Dax does today?
Yeah, so Dax Express again, the latest solution in terms of really focusing in on this administrative burden. It's a workflow integrated, fully automated clinical documentation. It's the first to combine our conversational, our very proven conversational and ambient AI trained on millions of healthcare encounters, as you said, with high accuracy, and now it's combining it with G P T four, the newest and most capable.
What it does is it creates a draft standardized clinical note automatically and securely in seconds, and it's immediately available for clinical review and completion by the physician. So it's technology that's presenting it right after the visit. Where the physician is still the one that goes in, confirms everything is accurate, has the ability to edit it.
The other thing that we've done with this is because there's 550,000 physicians using Dragon Medical one today, and that's already enabled with many of the electronic health records. And it has a tool set that people are very used to. We have enabled it through Dragon Medical one. So you can do things with Dragon Medical one, perhaps pre-visit.
You can use Dax Express Ambiently in the visit, and then you get to use the same tool sets after the visit to do a quick review. And so what's really different about it from what we introduced three years ago is three years ago, We introduce something that does have a human reviewer in the process in terms of a quality review in addition to the position reviewing it.
And so the turnaround time was a little delayed because of that. The other thing that was a much more rich, customized documentation. And so if that's what you want and you're not able to, really go with a standardized note, then full service tax is still the way to go.
So Dax Express, is that in specific areas?
Are we seeing it in primary care? Are we seeing it in some of the specialties? Is it limited in any way at this
point? Yeah, so what we're gonna come out with is we're gonna really focus on family medicine, which is the, probably the biggest area that has burnout. But we expect to introduce. As you noted, we're gonna do private preview in June.
Hope to have general availability more in the early fall timeframe, and that'll really focus on family medicine, but we expect to introduce it just like we did with full service stacks to probably 30 or more specialties, and that'll continue to ball just like Dragon Medical one did.
Well, when the announcement of Microsoft and Nuance coming together I was really bullish on it because I just saw the synergies and the capabilities that Microsoft is gonna bring, and then they bring in G P T four and and it's really playing out.
Well talk a little bit about the impact of that partnership Microsoft and Nuance and really it's ability to improve healthcare outcomes.
So we're also very excited. It's hard to believe it's been over two years since we made the announcement. And the announcement was really leveraging partnership that we had already had in place.
We worked together on the first version of full service decks together, and that allowed us to get to know each other and understand the cultures, which have been a great great match. And what we're really focused on is, Our respective capabilities and how we can bring those together and actually do more with those.
So obviously everyone knows Microsoft leading the leader in technology, they have the cloud for healthcare. They have their cloud infrastructure of Azure that's really optimized for these AI solutions. They have built stacks in terms of capabilities around getting data out in an efficient manner.
And then we have all of our clinical applications that sort of sit on top of that, whether for the physician, the radiologist, and so it's really answering all of those key questions. At least in our mind, that we think customers have, how's my users going to use this? But then. How do we get the data and insights out of it, and how do we really know that it's set up in a way that's scalable, it's secure, it's protected, it's highly compliant.
All of these things that sort of go up and down, the questions that get asked by our customers.
I really wanna take this to where this is gonna be used. What's the feedback you've gotten from physicians? Who are utilizing these solutions today? I remember early on it was kind of, we had some hit and miss kind of things.
I'm going back 10 years at this point when I'm thinking about that. But we had some hit and miss, but recently I've been talking to some physicians and they're at a point, it feels to me like I can't live without it kind of stuff. Can you talk a little bit about the experience and what you're hearing from the physicians?
Yeah, so I think along this journey we've learned a lot of things. So, for example, when we first introduced full service stacks, the question was will patients consent to it? And we've had very high levels of patient consent. I think now we're at a spot where people know that there's security around us and what it's used for and who owns the data.
Those questions have really been grounded and people have kind of gotten to a point where they understand how to do that, where it works in a very instrumental way. But what I think now, the big buzz around HIMSS was how applicable this is in all different use cases, some of which we're going to obviously serve around clinical documentation.
You raised the one around potentially with. Microsoft and an electronic health record company like Epic was announced where they were looking at the patient responses, the emails, which is a heavy burden. The other burdens that we've seen can come up in many different areas. An example in radiology is how can we make it easier to get all of the information, the pertinent information?
From prior reports up to the radiologist that's doing the current report how can we look at the clinical note and say, well, based on this clinical note, is there intelligence and insights that I can give to the physician or the care team around what this might be that the patient. Situation is any kind of insights, guidance, things that might be missing, questions that should be asked.
So it's just coming straightforward into the actual, workflow of the patient and along that patient journey. Many different ways. I think the other area is around nursing. Nursing has not really been focused on as much, but heavy burnout, shortages, not really a focused area for technology.
People still writing down. Things, when they transfer shifts, they write stuff down on Post-It notes. They don't have a lot of communication, collaboration tools. And so all of these things are kind of coming together, some of which will probably be based on G P T four, like, models and others the evolution of just existing models.
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now, back to the show.
I do wanna talk a little bit about futures, and I know you're limited in some of the things you can talk about with regard to futures, but when I think about how much, how far these tools have come in the last couple of years the AI tools dragon Medical One, DAX they're all evolving pretty rapidly.
I would love to ask you, where's it gonna be in five years? That would be wow. Who knows where. That's a long ways out. Yeah, I know. Where's it gonna be in, in two to three years? I mean, how is it going to just speculate how might evolve a little bit.
Well, we talk mostly about the provider space, but reminder, there's the payer space, there's life sciences.
So is there gonna be data that if you can more standardize the node and better appreciate the actual patients, can you be better apt to select the right cohorts for clinical trials? Can payer provider, information pass more easily? For example, when a patient is in the room and you're
considering what kind of things to prescribe for them do you really clearly understand what's gonna get paid for? And so instead of the patient showing up at the pharmacy and realizing, oh, I can't take this cuz I can't pay for it. Kind of resolving anywhere there's waste or errors.
I just think that those are perfect spots for us to get better on. And then the other examples of course, are. Can you help guide the physician through differential diagnosis by, producing. Potential options for them to consider, and then based on what gets selected, that keeps training the models to get smarter and smarter, that when they exhibited this, the physician always chose that, and so I think this evolution is just gonna get better.
Of course, there's always these things where somebody will say, Hey, in the future you're gonna walk into a place that doesn't have any people in it. And you're just gonna go up and you're gonna ask, I'm not sure anybody thinks that's quite there. I think what we're really focused in on, how do we just amplify the intelligence of the clinicians?
How do we take care of some of the tasks that are just, allow them to see more patients get access to more patients. I think that's what we're gonna focus on.
Yeah it's removing the cognitive load , I saw a video bill Gates was talking about this, where's G P T four gonna go?
And it was really interesting. And it was interesting because he said, all of us are gonna have an AI personal assistant. And as he was talking through this it started to sort of materialize cuz I've been playing with G P T four for a while. And it's things like he goes, you know it, it's gonna read your calendar, it's gonna read your email with permission, but it's gonna read those things.
It's gonna read your health insurance policy, maybe even look at your bank accounts and that kind of stuff, and you're gonna say hey, I'm being prescribed this, your medical record I'm being prescribed this. Do I have enough money for the, I mean, you're gonna be able to query things like, Hey, I just was in an auto accident.
What's covered? And it's gonna respond to you and say, well, based on your insurance policies, this is what's covered and this is who you should call. And I heard him sort of talking about this personal assistant and I thought, man, every physician should have that. Personal assistant with them at all times.
It says, Hey, I read this Journal of American Medicine article. Are you're treating this patient today. This might be relevant information. I
think that bill not only from the physician side and that would be wonderful because what's the latest research on something, right?
I have a patient I've been following. What's the latest thing if that's not working well, I think about as a patient, all the things cuz I, I continue to say the patient is probably the most underutilized piece of the patient care journey cuz most of us at patients. We go to the doctor's office, we try to absorb everything we can, and then we leave and maybe we go back to our portals and ask questions, but it's just hard to track.
And then if you're also helping parents or another person with their care, how do you actually do that? So I think that it can help everyone in the patient's journey. I'm hoping it can also help the information that flows between the care team so that a lot of the most complex cases, a patient is treated by multiple people, whether it's a surgeon, an a, a medical oncologist, a radiation oncologist, and being able to monitor the patient more seamlessly and effortlessly and identify things where they may be falling through the cracks I think is really critical for the overall outcomes and also the, just the reduction of cost as well.
This is this is definitely an exciting time. My closing question, I'm gonna go back to, we've been doing this show for about five and a half years. One of the earliest shows I did was with Dr. Lee Milligan, and he was talking about he's waiting for the Star Trek moment within healthcare.
You know that they walk in, they walk into the room and they go, Hey, computer. What's the, or can you do or whatever. And when I, the first time I used Dragon, I have to admit, was a long time ago. And that was my hope, was that I'd be able to interact with my computer in that way. We've seen some of that with Siri, some of that with some of the other tools that are out there interacting with the internet, pulling information in how close do you think we are to, to that Star Trek moment?
I definitely think those examples that you've commented about where you can use voice and in your own way, ask questions. We definitely have some of those capabilities today in simplistic form. Like, Hey Dragon, bring up this, Hey dragon place the order. Hey, epic, or Hey Cerner, whatever the, the voice word is, and so some of that's going to be there.
I think where you're going to is how. How complex can you get with that? Yeah I just,
Right. I just wanna query the EHR and say, tell me the results from the last five visits and boom, there's the screen.
That's right. And so I think we're closer to getting to that with capabilities like this being able to query what the information is.
Now, what has always hindered healthcare is not all of that information is exactly in one system, or it's not in as structured of a format. So I also think one of the evolutions specifically in clinical documentation is that there's more acceptance of the benefits of getting to more of a standardized note.
And once we get to a standardized note, queries like that and the benefits of that can outweigh maybe something that's heavily customized.
I love that you end on that because that is one of the things that, that people don't recognize that, like why is healthcare so hard? And it's the standardization of that data.
We still have sort of data governance problems, but if we can solve it on the front end, like you say with tools that are going to generate that for us in a very standard format, that is, that's gonna go a long way cuz doctors have said it. I'm not saying it about doctors, but they're not really good.
Data entry clerks, they, that's not why they got into medicine. And tools like this really take it forward. Diana, I want to thank you for your time and thank you for for recording this again. I really
appreciate it. Yeah. Well it's wonderful to spend time with you, bill, as always.
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