May 26, 2021: Microsoft and Intel engaged World Wide Technology to develop a hybrid cloud solution to demonstrate the power of Azure Stack Edge Pro’s edge compute and AI technology. Dr. Sanaz Cordes and Dr. Eric Quiñones from World Wide Technology and Chris Gough from Intel are here to talk about this advanced technology that is transforming healthcare. The locus of care is shifting to remote venues and really into the home. What kinds of challenges does this bring to health IT organizations? What are some of the use cases that are moving to the home? And how big is the need for real time data and real time interaction? Many health organizations are stuck on the challenge of compliance, privacy, latency and getting the right data into the hands of physicians without overwhelming them. How does a solution like this address these challenges?
Showcasing Healthcare Transformation with Advanced Technologies with World Wide Technology and Intel
Episode 408: Transcript – May 26, 2021
This transcription is provided by artificial intelligence. We believe in technology but understand that even the smartest robots can sometimes get speech recognition wrong.
[00:00:00] Bill Russell: [00:00:00] Thanks for joining us on This Week in Health IT. This is a Solution Showcase. My name is Bill Russell, former healthcare CIO for a 16 hospital system and the creator of This Week in Health IT, a channel dedicated to keeping health IT staff current and engaged.
[00:00:19]All right today, we have a Solution Showcase and we’re going to talk about some really cool advanced technologies in healthcare that is transforming healthcare. We have Chris Gough with Intel, [00:00:30] Dr. Sanaz Cordes with World Wide Technology and Dr. Eric Quinones with World Wide Technology as well.
[00:00:37]I want to thank WWT and Intel for sponsoring this solution showcase. It’s a great conversation, a lot of really cool solutions they’ve come up with for healthcare. If you want to learn more about this, you can hit the website wwt.com they have a lot of really great material for healthcare professionals out there.
[00:00:56]If you want to be a part of our mission, you can become a show sponsor as well. The first step [00:01:00] is to send an email to [email protected]
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[00:01:51] Today, we have a Solution Showcase. We have Chris Gough with Intel, Dr. Sanaz Cordes with WWT and Dr. Eric [00:02:00] Quinones with World Wide Technology as well. Good afternoon everyone and welcome to the show.
[00:02:05]Dr. Eric Quinones: [00:02:05] Thank you. Pleasure to be here.
[00:02:07] Bill Russell: [00:02:07] Yeah. I’m looking forward to this conversation. There’s an awful lot of talk right now around the locus of care and this shift during the pandemic to remote care venues and really into the home. And we’re seeing some of the payment models start to follow that.
[00:02:21] So let’s start with this question. What kind of challenges come along with that change? And what kind of challenges does this represent to healthcare [00:02:30] and to health IT organizations. So we’ll start with you, Dr. Cordes. What are your thoughts about the change in the locus of care?
[00:02:38] Dr. Sanaz Cordes: [00:02:38] No, I think that there’s sort of the tactical logistic challenges, but there’s also the mindset the philosophy of really shifting the way health systems think about care.
[00:02:49] Typically it’s been episodic and reactive care, right? Patients come in and access care points in time. And then we react to it, to this model of [00:03:00] continuous proactive care. I think that’s what the pandemic has shown us. It’s really important to be able to kind of make that shift and doing it remotely and being at home is truly the best way to capture that sort of continuous data and find out information before Before it becomes a challenge and you need to intervene medically.
[00:03:19] And then I think from sort of just day to day execution of that the access to the care beginning with just the digital engagement, do they have a portal set up properly? Can [00:03:30] patients have that retail sort of experience that they expect to be able to get on schedule, launch their remote engagement have their devices at home feed in seamlessly and then the connectivity we serve a lot of health systems at World Wide that have rural locations or various communities that don’t necessarily have access to wifi or devices that can allow them to have some of this care. So making sure that they can do what they can to [00:04:00] solve for that.
[00:04:00] And sometimes that involves things like putting up stations and communities libraries and things like that, which we’re helping folks do too. Be able to come in and access telemedicine. And then of course, for the CSOs of the CIO’s and all the folks on the IT side of the organization, the data, getting the data, aggregating the data, putting the data in the right place and the security around doing that as more and more devices become part of the remote plan, making sure that that that patient information is passed [00:04:30] through securely.
[00:04:31] Bill Russell: [00:04:31] So as a follow on to that, do you think this is going to be a permanent shift that really was accelerated through the pandemic? I mean, we saw this happening prior to the pandemic, but as the pandemic has sort of accelerated, do you think it’s going to continue at this kind of pace following the pandemic?
[00:04:52] Dr. Sanaz Cordes: [00:04:52] I do think so. I think we’re sort of in a different phase now where that kind of rush to have a lot of [00:05:00] telemedicine visits and completely not coming to the hospital, as we all know, that’s kind of, we’re past that and people are feeling safe and coming back in. But I do think that these new models of care are here to stay and will probably continue to grow.
[00:05:12] I think some of the industry, changes, suggest that CMS is providing more and more reimbursement and programs for hospital at home. There’s grants that continue to pop up around this. So I do think that it’s, it’s here to say and stay and it’s going to [00:05:30] continue to evolve and we’re probably going to see version 3.0 roll out in 2022. And I’m excited to see what that might look like.
[00:05:38] Bill Russell: [00:05:38] Yeah, me too. So, Dr. Quinones, so let’s talk a little bit about the use cases. You know, what are some of those use cases which are moving to the home that have a need for real time data and real time interaction.
[00:05:54] Dr. Eric Quinones: [00:05:54] Yeah. Right. Maybe Dr. Cordes actually, touched on a few, but you know, [00:06:00] particular to CMS, they have the acute hospital care at home program, which is an expansion of the CMS hospital without walls launched what in March, 2020. So the immediate goals of that was to really allow what experienced hospitals to, quickly expand care to their Medicare beneficiaries as well as, the hospitals themselves are required to submit, [00:06:30] this monitor data on a per month basis. So that’s, one, one prong or one thing I see another thing is but at the end of February, I believe Humana Humana’s Medicare advantage population will have in network access to mercy virtual, which is the hospital without without beds out of the St. Louis. [00:07:00] So staff with. Greater than what 300 clinicians providing a proactive remote patient monitoring for patients at home, in the hospital setting as well that are being monitored again by mercy virtual. And this is really a value-based care play with Humana, for their patients in I believe it’s Arkansas Kansas, Missouri, and Oklahoma as well.
[00:07:25] And then lastly, I would say on the, one of the [00:07:30] non-traditionals so big tech yeah, Amazon care, but not alone with Intermountain Health and Ascension health that you know that are founding members of the Moving Health Home Coalition and they’re really have been driving and lobbying to make permanent changes to the home care health reimbursement policies, so that’s very huge. They also have additional members that’s moving health home initiative. They’ve got landmark health, [00:08:00] Amwell signify health and several others. So there’s a lot of forces that are driving these initiatives to be to moving health home.
[00:08:10] Chris Gough: [00:08:10] I think today, if you look at just simple doctor, patient virtual visits or remote patient monitoring the home for chronic diseases as Dr. Cordes said, that is those, those require kind of discrete measurements, maybe a few times a day as these acute services shift into the home over [00:08:30] time, we think there’s going to be a need for more, streaming, telemetry and continuous data.
[00:08:36] So that will Cause some additional challenges and technical requirements to accommodate those that different kinds of data acquisition and home.
[00:08:46] Bill Russell: [00:08:46] Yeah and that’s the direction I want to go. It’s interesting that you said hospital without beds and it actually has beds.
[00:08:51]There are beds, right? There are beds and home. As a CIO, I used to get asked all the time, how many beds does your hospital have? And I guess for Mercy, they [00:09:00] have to say this many acute but they also have to say you know this many people are being monitored from our, virtual hospital in their own beds really. It’s kind of interesting but so what Chris was, was talking about what kind of conditions are we seeing sort of emerge at this point that, people are using this kind of real-time data real-time tracking and delivering that to a care team so that they can provide care [00:09:30] for that population.
[00:09:31] Dr. Eric Quinones: [00:09:31] I think initially there’s one can try to boil the ocean and try to look at all chronic conditions. That might be a little too much. If you focus on what we’re seeing and what I’ve seen. It’s focusing on those chronic care conditions that we spend a lot of money on or there’s a lot of opportunity there to be more proactive with that population.
[00:09:59] Those are the [00:10:00] kinds of conditions that, that I see this really getting in front of. So for example congestive heart failure diabetes, hypertension, and things like that, things that are some of the most common conditions we see that we’re spending our most dollars on in health care to be proactive with those patients.
[00:10:20]And taking corrective action before they end up getting at a bad place and having to be whisked off to the ED. Those are the kinds of conditions that [00:10:30] I’ve seen.
[00:10:30]Bill Russell: [00:10:30] Chris, I want to come back to you Microsoft and Intel engaged, WWT to develop a hybrid cloud solution to demonstrate the power of the Azure stack edge pros edge compute and AI technology. Tell us a little bit about that project.
[00:10:47]Chris Gough: [00:10:47] Yeah, sure. Well, as we’ve engaged with healthcare organizations, We have seen a common need for like an intelligent edge solution. If there’s always going to be an edge in healthcare, that’s where the [00:11:00] patients are. That’s where datas is originally acquired.
[00:11:04]And there’s some applications or use cases that really are more appropriate for, to be deployed in that physical location. So that could be driven by latency. so for example, if you’re looking at a large imaging study and you want to do some image analytics to find a feature in that data you want to make a decision there at the point of care quickly. You don’t want to send the data to the cloud, process it, send the answer [00:11:30] back. Video is another good example of that you don’t want to send for, cost and complexity and speed, like raw video streams to analyze that kind of data. And then also from a regulatory perspective depending on what country, state, or province you might be in, there’s different rules for how the data is regulated and where it can reside, where it can be processed.
[00:11:51] So for all those reasons like a hybrid, we feel like a hybrid cloud solution. Let’s see the health organization [00:12:00] run certain applications or workloads there at the edge at the point of care. And it could be like, for example, fall prevention analyzing video. We see that use case quite a bit.
[00:12:13] And then for applications that are more suitable for the cloud, like maybe a longitudinal population-wide study. More of a health research use case. They can decide to run that there. So the hybrid cloud solution really lets the organization decide based on the requirements of that particular [00:12:30] application or workload.
[00:12:31] Do I want to run this on the edge at the point of care, go out and run this in the cloud and that, that flexibility is appreciated.
[00:12:39] Bill Russell: [00:12:39] Absolutely. So many health and Dr. Quinones I want you to comment on this many health organizations are stuck on the challenge of compliance, privacy, latency, and really getting the right data into the hands of the physician without overwhelming them. How does a solution like this address these challenges?
[00:13:00] [00:13:00] Dr. Eric Quinones: [00:13:00] Sure. Simply put this helps identify the signals from within the noise. Clinicians are slammed and they’re just overwhelmed with the amounts of data that is humanly impossible to manage.
[00:13:14] It’s share cognitive overload by numbers. Tools like this, get the right data about the right patient to the right clinicians at the right time in order to be proactive and to be supportive in [00:13:30] their critical clinical workflows.
[00:13:31]A tool like this can it can be configured for chronic care management populations, post discharge care populations, behavioral health even rapid response teams that are in the hospital. The responsible for surveillance of acute care populations. Most rapid response teams are activated after the fact after something bad has happened.
[00:13:57] So tools like this can definitely help in real [00:14:00] time triage patients and get them admitted to the right place in the hospital. An example of that would be a patient being admitted to the floor for observation from the E D many times there’s a changing disposition with a patient like this because they’re waiting for bed for a long period of time.
[00:14:20]Having a tool like this, to be able to bring these insights to the forefront so clinicians can make adjustments and make sure the patient gets transferred to the right level of [00:14:30] care. Perhaps the ICU is very important and these are things that we need today to really change the outcomes time is everything early recognition.
[00:14:42]A patient decompensation driving early intervention leads to better outcomes and costs, and all this can be done using your organization’s clinical protocols and even developing advanced analytics models that are tweaked by their organization’s governing [00:15:00] bodies that provide even higher positive, predictive value and negative predictive value at the individual patient level.
[00:15:09] Bill Russell: [00:15:09] Dr. Cordes I had to laugh when I was reading about this. I love the challenge that World Wide Technology was given. January of 2021 they were given this challenge to deliver a fully functional proof of concept by the end of February for the Microsoft ignite conference in early March. Talk about how that is even [00:15:30] possible.
[00:15:31] Dr. Sanaz Cordes: [00:15:31] Nothing we love more than a deadline challenge World Wide. Yeah, no, it was phenomenal to watch the team in action. I mean, we have such a diverse team we’re really fortunate to be able to just quickly assemble the right folks. So we were able to bring.
[00:15:46] Physicians with practice experience like Dr. Quinones, myself physicians and nurses who have health tech experiences who deeply understand how the electronic workflows work, where does information need to go and [00:16:00] needs to, as Dr. Q is saying what notifications go, where et cetera. We have data scientists.
[00:16:06]We have dozens of PhD, data scientists on board. We have AIML experts, our software developers, we have UX designers, product managers. So we were able to quickly assemble this group, this really great team to start working in a sort of a iterative model to identify the use cases. Vet them have really great collaborative discussions and you [00:16:30] know what World Wide, our application services team we have agile methodology to see that in action and see how valuable that is to be able to, to roll things out this quickly. I think this, this project really brought that to light. So yeah we did it. We were able to kind of roll that out and we also were able to tap into some of our customers we at World Wide touch one in five patients in the us when you look at our reach of, of our health system [00:17:00] customers. So I actually was able to meet, and I think Dr. Quinones might have as well met with a couple of our health system organizations CMIOs and others to, to get some feedback along the way, which was really helpful.
[00:17:15]Bill Russell: [00:17:15] Give us an idea of what was developed. So clearly you didn’t develop it for all chronic conditions. It was probably focused on one, given that timeframe what was actually developed and what did it showcase?
[00:17:30] [00:17:30] Dr. Sanaz Cordes: [00:17:30] So we so first of all, clinically the use case that we landed on was heart failure. Heart failures costliest condition in the U S to care for I think $70 billion a year spent the number one cause of death in the US so we sorted through several chronic diseases and that one made clinically. And also, as we looked at what’s a data rich environment for someone potentially at home.
[00:17:58] And of course [00:18:00] this solution can work in a lot of other settings and we can touch on that. That’s not just at home, but in this first model a data rich environment, a heart failure patient may be able to We would be able to monitor multiple devices like blood pressure, cuff and scales and pu lse oximeters and EKG.
[00:18:21] So it made sense that this would be a good starting point use case. And so we’re starting with that. We were able to create [00:18:30] protocols and Dr. Quinones has led most of that effort using practice guidelines and things through evidence-based medicine to sort of create the protocols of what it would look like as we monitor a patient at home the normal abnormal and what’s the beauty of this solution.
[00:18:48]Abnormally, trending normal, which you don’t normally get to do when you’re doing point in time data collection. So when a patient comes in, you’re just seeing their blood pressure when they’re there. And it’s probably high because they’re [00:19:00] dealing with white coats and the stress of being at a doctor’s office.
[00:19:03] And so creating the solutions so that the AI and machine learning could then come in and say, well when the pulse ox is still normal, but it’s trending this much below where it was the last five days. And the scale indicates a slight weight gain that’s still normal. And you marry that with X, Y, and Z.
[00:19:23] Now we are getting some data rich insights, and now we can take proactive steps. And so that was [00:19:30] all kind of put in place. And then from an actual user interface perspective, we had a very beautiful design that our app services team created that was sort of the red, yellow, green model of showing trends and then being able to actually show notifications.
[00:19:45] And it was a great dashboard that was configurable to, to what physicians want. Would want to use or case managers or anybody that would be accessing the information. And that was the initial sort of prototype that we rolled out for the ignite [00:20:00] conference.
[00:20:00] Bill Russell: [00:20:00] Fantastic. So Dr. Q what potential outcomes for care. As Dr. Cordes was talking you can apply this at the home, but you could also apply it within other care settings. What kind of outcomes for care do you anticipate as a result of this type of solution?
[00:20:16] Dr. Eric Quinones: [00:20:16] I think taking a step back a little bit thinking about, where it actually helps, right? So if you think of a solution like this really helps us scale and it helps us to have greater optics for the patient [00:20:30] and the population longitudinal journey.
[00:20:32]Clinical resources are thin right now. We see the numbers that are entering med school that are starting to increase a little bit, but still you can’t train a doctor overnight or nurses overnight. It takes time. The AAMC, I think said last year at sometime noted that shortages between 21,000 to 55,000 for primary care physicians.
[00:20:57] And I think somewhere around [00:21:00] 34,000 to 87,000 for surgical and medical specialty positions by the year 2033. That’s really significant and then with US aging, US population, that’s getting older that’s just more chronic conditions that we have to care for. So we need advanced technology solutions like this to help bridge that gap. And integrating multiple data points not just the data points that Dr. Cordes talked about, but, as [00:21:30] data points become. greater, not just by those labs, but very wearables, the genome, social determinants of health environmental and ecological data to solve drives us down that proverbial precision medicine road that we’re all striving for, and I think this can have a tremendous impact in cost outcomes, patient satisfaction, and clinician experience. For sure. with this [00:22:00] level of data can also help drive the acceleration of research in life science. So there’s a lot of outcomes that I think that are going to be coming from this.
[00:22:11] Bill Russell: [00:22:11] This is a great example of a partnership between Intel and WWT. How can people really tap into the solution? If people are interested in this, how can they find out more information?
[00:22:22] Dr. Sanaz Cordes: [00:22:22] Yeah, they can absolutely find out more, they can reach out to anybody on this on this podcast right now, Chris, Eric, [00:22:30] myself, we also are in the Microsoft marketplace. So there’s a engagement there that folks can review and click on and sign up for where we can help them with learning more about the solution and customizing it and ultimately potentially rolling it out for their use cases.
[00:22:48]Bill Russell: [00:22:48] I was looking at another use case that you guys you have on your website. I want to talk about it a little bit as we come to the end of the podcast, but it’s really interesting. And I think it also [00:23:00] accentuates your partnership and that’s the machine learning in radiation oncology at Wash U school of medicine.
[00:23:08]Who wants to give us some background on that project? It looks really fascinating.
[00:23:13] Dr. Eric Quinones: [00:23:13] World Wide Technology. We collaborated with Washington University School of Medicine in St. Louis to utilize machine learning, to really develop methods, to predict radiation treatments for patients with cancer.
[00:23:28] About one half of [00:23:30] all cancer patients receive radiation therapy as part of their treatment plan. And radiation oncologist coordinate with oncology specialists to review appropriate treatments for their patients, what we call multi disciplinary tumor boards they use national and international guidelines, patient history details of that patient history and physician clinical experience with various [00:24:00] treatments and available resources.
[00:24:03] That they have at their facilities the radiation or radiology oncology treatments have become much more complex as a result of all this precision of this type of treatment is really critical and needs to be unique to the patient. Radiation not only kills cancer, but it also kills healthy tissue as well.
[00:24:25]So there’s no room for delays in treatment. [00:24:30] Time is critical. So this led to Washington University and World Wide Technology working together using high fidelity diagnostics, clinical, and treatment data to author, machine learning algorithms that quickly predict the optimal radiation oncology treatment orders for head neck and lung and prostate cancer using this platform.
[00:24:58] Radiation, oncology, [00:25:00] oncologists specialist the, that are specified, excuse me, the details of the cancer. And they specify the details of the cancer, the patient. And then as a result, the machine learning algorithm is given the radiotherapy planning, target volume, the frequency of treatment to prediction percent with explanation, which is very important for the clinician the patient body [00:25:30] positioning during treatment sessions.
[00:25:32] All these things are super important and the type and frequency of radiology imaging needed. So that all takes a lot of time. And so this really has a potential to expedite a time consuming process and radiology oncology orders with the goal of greater efficiency as well.
[00:25:53] Also from I believe Washington U school of medicine is offering an academic paper on this. So we’re really [00:26:00] excited to see what comes of this amazing collaboration and technology.
[00:26:04]Bill Russell: [00:26:04] Chris as I listen to this, the precision aspect of this, getting to the N of 1, as they say this kind of precision, these kinds of things create massive workloads and their compute intensive, their storage intensive. I mean, the processing obviously is significant. What advances has Intel made to handle these kinds of workloads and what can we expect moving forward in this area? This [00:26:30] is exciting stuff to get closer and closer to that promise of precision medicine.
[00:26:34]Chris Gough: [00:26:34] Yeah, absolutely. We work very closely with the healthcare ecosystem, both the partners that brings solutions to market, but also with what we call the end users of our technology hospital systems. Pharmaceutical companies, et cetera, so we can understand their requirements. But in this case, in the case of what we’re talking about today, understand how they use or could use machine learning to improve what they’re doing [00:27:00] and we’ll, we’ll weave those requirements right into our right into our technology that we’re bringing to market. So we’re known as a CPU company we actually have an XPU strategy. So depending on what kind of artificial intelligence it is or what kind of machine learning it is, there could be different hardware that’s more appropriate for that task. And then beyond the hardware working with the software ecosystem to opt, to optimize all that software, to make sure it’s as scalable and efficient as it could [00:27:30] be. And as in take advantage of all the, underlying features, and then of course working very closely with partners like WWT and Microsoft to weave that innovation into the solution like the solution we talked about today. So that from the end-user’s perspective, it’s sort of invisible and just works by performance and it can accommodate the machine learning task, whatever task is put to it so.
[00:27:55] Bill Russell: [00:27:55] Yeah. So Dr. Cordes anytime we talk about machine learning, anytime we talk [00:28:00] about artificial intelligence I wander back to some of the conversations I’ve had with physicians and there’s still a reticence by some physicians to adopt this kind of stuff. How do physicians view this and the use of this technology and what’s going to take it forward do you think?
[00:28:21] Dr. Sanaz Cordes: [00:28:21] it’s interesting. I started started my health tech career in clinical decision support when I stopped practicing and I moved over to the corporate [00:28:30] space I worked for an organization where we sold just static order sets to CPOE orders.
[00:28:37] That’s in the early 2000s And yeah. That started my journey of managing physician cultural adoption. And it’s really interesting to look back now, 15 years later, 16 years later, and we’re still. Doing that, right. I mean, if you asked a physician now, like how do you feel about just a path of asthma order set or CP?
[00:28:59] They’d [00:29:00] say, yeah, of course I’ve been using that for over a decade, but at the time it was very challenging, right. To get this adopted and become part of the workflow. And so I think we’re just same story, fifth verse now, as we see more and more AI and ML, and that becomes more commonplace and more organizations are bringing it on board.
[00:29:21] So. Yeah, there’s nothing magical. It’s just the same kind of formula we need to make sure that whatever solutions we bring forth in this case, AI [00:29:30] ML, there is a, that we’re able to demonstrate a solid clinical ROI, cause that matters more than anything to the physician. So having those success metrics in place.
[00:29:40] So with the case study that like Dr. Quinones has just described with radiomics being able to point back and say, with a 97% accuracy, this, this and this was identified in these 200 patients and by measurement they’re length of stay or any other adverse outcome was decreased by X percent.
[00:29:58] And so I think [00:30:00] that we know that now, right? Like 22 decades into it, you really need to present that to clinicians. And so I think health systems should keep that in mind as they roll out solutions, putting in those metrics and a plan to measure them. And then I think engaging stakeholders early and often bringing positions to the table, making sure that their voice is heard and that, they can help.
[00:30:24] Become part of the process and become sort of invested in it, I think is really [00:30:30] important. So, it’s nothing magical. I think it’s just what we’ve been doing over the years. And I guess the third thing that helps us, there are the folks that are early adopters, they embrace change, they want these solutions.
[00:30:43] And so getting them to be advocates to their peers has always been really helpful to me, bringing solutions to. Two organizations. And so, yeah, I think a combination of those things, and we just keep learning from what we’ve done in health tech over the years, and [00:31:00] growing on it.
[00:31:01] Chris Gough: [00:31:01] We found that when you’re rolling out new technology like say like a machine learning model, that’s going to predict patient risk for some type of condition.
[00:31:10] If it can be done in such a way that it minimizes the disruption to the current clinical workflow, like maybe putting that risk score right in the electronic health record, as opposed to requiring the clinician to interact with some second application that also can help with adoption and receptiveness quite a bit.
[00:31:28] Dr. Sanaz Cordes: [00:31:28] Chris that is such an [00:31:30] important point. Absolutely. Physicians, nurses, and clinicians spend 10, 12 hours a day in the EHR. That is their user interface. The thing I’ve learned over the over the decades is yes, they absolutely don’t want to open seven other apps. They do not want to have multiple user interfaces.
[00:31:46] And so being workflow congruent is absolutely crucial. So great, great catch on that.
[00:31:51]Bill Russell: [00:31:51] We’ve talked about how people can get more information on these solutions, but as a former CIO, I’m sitting here thinking what if I had an idea, what if our [00:32:00] health system had an idea? Is this the kind of thing that we could tap into you guys and say, look, we’ve got this problem. We’ve got this challenge. We’re thinking of this. Could we give you the same kind of challenge saying, hey, it’s January. And by by March, we need to roll out a solution around this.
[00:32:15] Dr. Sanaz Cordes: [00:32:15] Absolutely. We have 500 engineers. We have several dozen PhD data scientists, and when they’re not involved on an active engagement which doesn’t happen often, but when it does we have a [00:32:30] very robust R and D mentality at World Wide.
[00:32:33] And so we have actually done recently a lot of work around computer vision, reverse image look up and the MRI brain tumor space. And that was all based on kind of what you just described, bill, where we had a health system express interest in that and ask questions about it.
[00:32:52] And we. Brought that back to the organization. And those guys just took it and ran and the AIML team, our business analytics team, and [00:33:00] were able to build the solution. And so we are always excited to discuss solutions and then work with our customers. And again we can reach out to Eric or myself or anyone at World Wide and in our organization to learn more about that.
[00:33:16] Dr. Eric Quinones: [00:33:16] And one more point to Dr. Cordes’ comments. So at World Wide Technology, we have a platform that really helps expedite this stuff. So the Advanced Technology Platform, it’s, boy, I [00:33:30] think the initial investment was about a half a billion dollars with our OEM partners such as Intel and others. They have the ultimate sandbox, if you will. So a health system can duplicate their environment within the ATC, and if they’re planning to bring on new technologies, they can do that. Or they’re going to do data migrations or. Any core it infrastructure changes and things like that.
[00:33:58] They can do it [00:34:00] quickly add with an agile mentality, to be able to come out with an outcome and help them with the decision. So that’s the same saves time and money.
[00:34:11] Bill Russell: [00:34:11] Fantastic. And they can get more information at wwt.com. Yes. I’m excited about this. I’m glad you guys came on to talk about this.
[00:34:20] I mean, these two solutions are interesting in and of themselves, but I love the fact that we can brainstorm together, that we can get into a room [00:34:30] with with data scientists, engineers just different partners, Intel and others, and come up with solutions. And that’s what it’s going to take, it’s going to take that creativity of the group getting together and bringing our skills together to come up with new ways. I think the pandemic taught us that we can do things that we didn’t think were possible before. I hope that pace of innovation continues. So thank you very much for coming on the show. I really [00:35:00] appreciate your time.
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