December 1: Today on the Community channel, it’s an Interview in Action live from HLTH with Peter Durlach, Chief Strategy Officer for Nuance Communications. What innovations are Nuance bringing to healthcare in the fields of clinical documentation, diagnostic imaging, consumer experience, virtual assistant technology and documentation integrity?

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I'm the Chief Strategy Officer for Nuance. And that is sort of a classic strategy. What markets we want to play in, what we want to compete in, what we don't. I also, when we do large disruptive new product incubations, that's also done under my team. So we do big new innovation projects for new products.

Number one question people keep asking me about nuance is Microsoft. It seems like you came together, they left you alone cuz you guys seem to be operating on your own, but you're still taking advantage of each other. Offerings and technologies bring to bear is that that's what we're seeing from the outside.

It's generally accurate. So when the companies came together it's often a mistake by the acquiring company that they buy a smaller company and then distribute and kind of kills it. So we were very cognizant both sides of that early on, that we didn't want to take away the magic of you the things that Nuance does, does well.

So yes, our whole core healthcare business moved in as. Our CEO that I report to, reports to a guy named Scott Guthrie who runs cloud and AI for Microsoft. So they kept us as one unit. The other thing we've done though, is they had a healthcare engineering team create, and they merged that into nuance.

So nuances really on the product side become sort of the healthcare vanguard for Microsoft. Obviously all the horizontal Microsoft stuff is still managed in the core thing. And then the other piece that we've done is the, the, the thesis of the deal really. Bring the power of the horizontal Microsoft technology cloud platform with the vertical expertise in healthcare of nuance.

So that's really horizontal meets vertical is the way we like to talk about it. So part of what we've been doing too recently is working together on the next generation of Microsoft Cloud for healthcare, which is the overarching strategy for the combined company. So technically, yes, we're sort of a separate thing inside of Microsoft, but we've also worked very closely with their healthcare team to do it sort of a unified strategy going forward.

we've done a lot of interviews with people from Nuance and your customers, and they love Dragon Medical one. They love the Daks platform. We talk a lot about that. But you and I were talking a little bit earlier of the different areas that you guys really focus in on, and at least one of 'em surprised me. So could you break out the three areas that you guys really focused on?

Sure. So there's, there's really four major areas that we focus on today. So number one you mentioned, which I won't spend too much time, is kind of the core business. Clinical documentation, reducing clinician, Bing Dragon Medical, one Dragon am experience of that. Couple other is we have a big imaging business, diagnostic imaging, which is one of the other foundational pillars of nuance. So the products best known in that space are PowerScribe. About 80% of all radiologists in the US use PowerScribe for their diagnostic and purporting process. And we have a product called Power Share, which is the largest image sharing network in the us.

Removing. Images related information around. So that's a big other business. One of the new things we've announced there is we have a technology we call the Precision Imaging Network that leverages those two foundational pillars and then builds a capability on Azure to host third party pixel AI models from the ecosystem of developers and research is building models.

Cause one of the challenges in that space is people build these AI models and they can't get 'em into the clinical workflow, which I know you're super familiar with. It doesn't matter if you build a great. How do you make clinical impact? So since we have 80% market segment share, we can host those models and drive them directly into the workflow, both in our own products within radiology, but also downstream into the ehr. So that's another big,

so is that a platform play? Would you be partnering with others?

Yes. It's a platform play. So we provide the infrastructure. Okay. And then we don't do the FDA models on the AI side, nuance and micro. But all the developers who are building those models can deploy on that infrastructure, and then all the researchers in life sciences and providers that are building models can deploy on that same infrastructure.

So when you build this model, you put it on the Precision Imaging Network, and then it leverages that 80% footprint in the last mile. So yeah, it's a platform play, and there's some really cool stuff like impact from a patient point of view, some of the most exciting advances in ai. On the imaging side, I can go into more detail late if we have time, but that's the second bucket.

The third one, which we're probably least familiar with, is we have a division of nuance that does consumer experience, virtual assistant technology, omnichannel. So what that means is big companies like FedEx, SS a JP Morgan, Humana, cvs, they use our application to do conversational ai, voice and text interaction with their consumers across the iv.

Texting, email and website. And the big advantage is it's one common platform. So what clients do is they model their consumer journey once, and they deploy that across one common platform for all the channels. So if someone's calling their IVR or you're texting, or they're going up with a chat on, it's all the same infrastructure.

You do everything. Everything won. So we brought that into the healthcare business market a couple years ago, and providers are using that to help modernize their digital front door. Classic patient access. Care gap, follow up, et cetera. So that's bucket number three. Okay. And there's a fourth. And the fourth is we have a clinical revenue integrity business, so around documentation integrity.

So this has to do with CDI coding, HCC capture things that where clinical care meets how you document to get paid and measured. That also can drive things around prior auth and UN on the health plan side. So that's the fourth part of the business.

All right. So we got about five more minutes left. I do want to.

To the clinical ai, but I, I want to stop first at the experience. The experience is interesting to me. I was at a presentation this morning, advisory board, and one of the slides you put up was the, and I think we've all seen this slide. It's the McKinsey slide that had by industry most digitized and consumer digital experience and healthcare was second to the bottom.

That's good. We used to be in the bottom, so we made progress.

Yes. But it was three rungs below the government. Scary. What's it gonna take for healthcare to take that next step?

It's a really hard problem and it's not really a technology problem as you probably know. There's technology from us, others that do other things. The problem is the incentive, my view. It's the incentive problem.

So it's an economic. Yeah because except in very small cases, you don't get paid for better experience and you don't know health systems well, they're struggling. Right? And so besides doing Press Gainey surveys for hcaps, for C caps with a few other things like the patient access center is getting a lot of attention.

Why? Because you can drive unused appointment slots and drive better experience and revenue. So the challenge is, why does it matter? Everyone wants to do the right thing. But they don't often get paid for it and given it's economically so constrained. So I think what's gonna happen is you're seeing some leading health systems put some real effort into that the disruptors are gonna cause more and more grief for the traditional health systems because they're coming in with a much more consumer focus thing from the beginning.

And I think it's gonna take some of that disruption and possibly some payment reform that's more than what's been done today. Because the tech can do a, I mean the tech that the other industries are using. Is no different than what healthcare could use. The difference is if they don't do a good job there, they lose clients.

Right. And here the question is, when will health systems, well, I would predict they are losing clients, but they don't know they're losing them because they can't track like leakage and referral patterns in any systematic way. So the challenge is how do you align the importance of keeping that client the patient and make and seeing the economic value?

Then it will happen. And that I think is actually the biggest, that's why it's.

I, yeah it's interesting. I think way too many people are saying, Hey, it was the pandemic and now it's the recession or increased inflation. And they're saying that's why our numbers are down, and I'm not sure we'll know.

Or they will know for another couple of years that, Hey, no, no, this is a problem. You're being dis remediating. There's new options here for remote care, telehealth and I mean, all these booths are people who are trying to. Care outside the four walls of the health system. Totally. And, and just take one patient at a time.

Yeah. I mean obviously the inpatient volume went down a couple, but you're right, I saw stop like 40% of patients switch providers during Covid. And as they release, I don't know if this will continue, but if they really let loose on the credentialing thing on the physician's side, which they haven't totally done yet, is a go from, that'll change everything.

Cause once you don't need to be. Credentialed in the state. All the low acuity stuff, you don't have to go see, you don't have to go. It's crazy. Yeah. You could stand up a call center and fill in the blank. A hundred percent. So I, I think you're right. I think these things are all gonna happen and it's, I think the health systems that they have to worry about this now because over time it's gonna be easier to get care, at least for the low acuity stuff. And if you don't have a better experience, then people are gonna switch.

📍 📍 All right. We'll get back to our show in just a minute. We have a webinar coming up on December 7th, and I'm looking forward to that webinar. It is on how to modernize the data platform within healthcare, the modern data platform within healthcare. And I'm really looking forward to the conversation. We just recorded five pre episodes for that. And so they're gonna air on Tuesday and Thursdays leading up to the episode. And we have great conversation about the different aspects, different use cases around the modern data platform and how agility becomes so key and data quality and all those things. So great conversation. Looking forward to that. Wednesday, December 7th at one o'clock. Love to have you join us. We're gonna have health system leaders from Memorial Care and others. CDW is going to have some of their experts on this show as well. So check that out. You can go to our website thisweekhealth.com, top right hand corner. You'll see the upcoming webinars. Love to have you be a part of it. If you have a question coming into it, one of the things we do is we collect the questions in the signup form because we want to make sure that we incorporate that into the discussion. So hope to see you there. Now, back to the show.

📍 📍 was there an announcement today or,

yes, we did. So, yeah, so the imaging thing I'm pretty passionate about. I have an imaging background, but, but one of the cool things is, I dunno if your reader, your listeners know this, but approximately 80% of hospital visits and over 23,000 condition, the pathways often starts with a medical image along with lab data.

So 80%? Yeah. So the, the diagnostic journey of a patient, the physical. The image and the lab really drive where you go in a pathway. So imaging's really important as many people know. Secondly, in ai, 75% roughly of all FDA cleared apps are in imaging and radiology. So it's one of the leading. But the problem with that is you have all these people building these apps on imaging, but they can't.

Again, as I earlier imagine, they can't get 'em into the workflow cuz they have no footprint in the workflow. So we did an announcement within Nvidia today. And the announcement is the follow Invidia has has worked on solving the other big problem, which is building these models, preparing the data, annotating it is also a real big pain.

So they focus on an open, an open toolkit to build imaging data sets to do build the model, the AI model. Okay. The problem is once you build it, you still can't get it into production. So we announced a partnership between us and Invidia where we connected to their platform called mo. Which is this developer environment to our precision imaging network.

So it's all running on Microsoft Azure. So you can build a model in Monae, basically click a button, create a Kubernetes container that runs on precision imaging network, and then you're connected to the 80% of the market in the US without having to do custom deployments for different infrastructure. So we're connecting much like in in like drug discovery.

You talk about how fast they get something from the bench to the bedside. Conceptually, it's the same thing. The bench here is in data. Versus the physical bench, but it's conceptually the same thing. How do you translate in inventions that can do that? I'll give you a couple quick clinical examples. So Mass General Brigham's one of the first clients that's connected there.

So they had a a breast screening algorithm that measures breast density and one of the key issues there that helps determine whether the person has cancer or not. So I'm waiting, instead of waiting two or three days and being really nervous, they can produce results in 15 minutes while the woman is still in the facility.

Big advance. Oh yeah. Another example. There's AI that can look at stuff in the pixel, the human eye can't see cuz it's quantitative. You can't actually see it. So there's a, there's a set of AI models that look at the abdomen. If you're getting like a CT of the abdomen to, let's say, some cardiac thing, they can look at data that the human eye can't see and do better predictive scoring for a future cardiac event by looking at your calc calcification of your key arteries that the human eye can't see.

So you could do earlier screening, earlier detection of things clinically that can go wrong. So there's all this data locked up in the pixels that aren't getting enumerated.

So I'm a former cio. Yes. What you just described to me is really attractive cuz first of all, 80% is using Power scribe. So that's the platform. Then you're saying to me, Microsoft Cloud, I'm already a Microsoft customer, they're all Microsoft customers. It's just a checkbox. We're in Azure and that kind of stuff. Invidia, Kubernetes. I'm already a VMware shop. I mean, all these things you're saying I already have, right? You're saying there's gonna be this marketplace of people that are just developing these applications, and I can literally just go in and go, yeah, this one, and deploy it fairly rapidly.

Exactly. And the challenge right now, just in medical imaging, they're expected to be 10,000 algorithms for the different modality, body top combination. The biggest company now for FDA clearance has seven. So imagine you're the. . Yeah. You're basically ending up with multiple one off infrastructure, do all your DICOM routing, all the integrations, all the security review, and then one day vendor X has the best lung nodule detector tomorrow, someone else, you're gonna have to rip out the whole I you're gonna, you're gonna shoot you're not gonna do it.

Right. This is where platform, so it's, it's a platform play to try to accelerate innovation from the ecosystem. And also in the academics, they have all these researchers building their own algorithms. So it's not just commercial stuff, it's also all the stuff they do under, I. That they want to deploy from their own research team into the clinical environment, and they're just stuck.

There's this big wall between the innovation side and the clinical side, as from living in that world.

But they also wanna monetize that stuff as well.

A hundred percent. So, yes. So perfect example. So every health system is looking for ways to create all the revenue streams, a lot of the leading sites, or say, we have all the clinical expertise, we have all the data. Why don't we build models? And then the problem is, how do you. Right. So this is the same platform they can use for internal deployment and validation. They can then deploy clinically for other and make economic value from that. Now, nuance is not taking the, the manufacturer record FDA responsibility, so they have to solve that.

There are a number of companies that are looking to aggregate that together for, for people that are building models on the provider side, but from a deployment side, they just use the same infrastructure on the nuance precision imaging. So we're very early business for us on this piece, but super exciting and also, The patient impact.

I mean we do a lot of good things at Nuance. We're very proud of, and we sort of help physicians have more time to take care of patients, but we don't historically do as many things that have direct. This one is right down the sweet spot. Like we can really help people have a better life. So it's, for us, we are healthcare people. It's kind of an important thing. It's fantastic.

Peter, thank you for your time Bill. Thank you very much. 📍 Appreciate it.

Another great interview. I wanna thank everybody who spent time with us at the conferences. I love hearing from people on the front lines and it is Phenomen. That they have taken the time to share their wisdom and experience with the community, which is greatly appreciated. We also want to thank our channel sponsors one more time, who invest in our mission to develop the next generation of health leaders. They are Olive, Rubrik, 📍 trx, Mitigate, and F5. Thanks for listening. That's all for now. 📍