Welcome, and thank you for joining today's webinar, The Benefits of the Cloud in Medical Imaging, a Clinical Perspective. Today's webinar is brought to you by Merge by Meritiv. This webinar is one of the many ways that RS&A supports radiologists at every stage of their careers, offering educational resources and tools to increase knowledge and foster innovation. Hello, I'm Dr. Kent Hudson, a neuroradiologist and the lead artificial intelligence technical consultant for Radiology Partners. Today, I'm joined by four panelists who will talk about implementing cloud technologies and radiology in their organizations and clinical practice. You'll learn firsthand about the benefits, challenges, and opportunities to integrate cloud-based technologies to improve your workflow, address physician burnout, and improve patient care. Panelists, if you could please briefly introduce yourselves. We'll start with Martin. Hi. Thanks, Kent. I'm Martin Sadler. I am an IT director for the National Health Service in England, and I run the IT for a trust that serves 600,000 residents and three major hospitals in Birmingham. And Linda? Hi. I'm Leonard Santos. I'm the director of information technology here at Multicare Health Systems. We have hospitals throughout the eastern and western part of Washington State. Great. I'm going to access. Good afternoon. I'm Linda Bagley. I'm the senior innovation executive at Merge with Meritiv. And I'm last. Hello, everybody. I'm Thomas Doherty. I'm a senior innovation executive also at Merge by Meritiv. Happy to be here to talk cloud today. All right. Thank you, everyone. So we really want to get a feel for what the cloud is, what the cloud does, and I think we need to start out by defining some of those terms that people throw around when they talk about the cloud. So if someone could fill us in on some of this terminology of cloud native and what that stuff really means. Shall I go for that, being an IT director? So what the cloud is essentially is a whole bunch of servers which are hosting your images and maybe your software as well, and are looking after it all so that your IT team can focus on other things, but really it gives you the opportunity of sharing your space with other users of it so that as your need for space grows or your need for processing power grows, that's really easy to apply to your services. So as images get more complex and bigger, instead of having to wait for someone to build another data center or to put some more servers in, if you've got everything that you need on the cloud, you just ask your cloud provider to do that for you. So it's called the cloud. It's always been called the cloud, but it's not really a cloud. It's somebody else's data center. Simple. That's the simple explanation. Yeah, and to add to that, right, it's like your cell phone, right? Like if you have an Apple device, right, you back your things up to the cloud, which is, you know, up in where Apple does their, saves their data. So it's part of our everyday utilities that we use. So to help us give a visceral example of the transition from whatever it was before the cloud to using the cloud, can any of you give us a real-world example of what you did to implement cloud technology and why? Well, I'll give you our example. So I joined the hospital trust five and a half years ago, and we had two data centers. One was on a piece of ground that we'd sold, and the other one was underneath a car park, which flooded. And they'd been there for 20 years, these data centers. And the choice was, wasn't really to build another one because they're really expensive. So in order to make all the images that we were storing safe and in order to improve the service for radiologists, because they were really, really old computers, really slow, we wanted to go for the latest technology so that they didn't, well, nobody has to worry about where the images are stored. So what we actually did was, because the cloud is essentially sending the files outside of your organization, the first thing we did was put some massive data pipes coming out of our hospital into the World Wide Web so that we would never suffer with traffic. Then we upgraded everybody's computers so that if there was a problem with the actual cloud storage, we knew it wouldn't be the network or the computers that were looking at the images. We knew it would be the cloud. So we did those two things first, and then we carefully moved all the images that weren't really for live and active patients first so that we'd learn from our mistakes. We didn't make any mistakes. We didn't lose any images. And then what we then did was we did a switch. Every new image that we took went to the cloud rather than our own storage, and then we migrated all of our current patients' images over to the cloud storage. So that's how we did it. It took two years. We wanted to do it carefully. We made sure that we kept all the data protection, got all those things lined up first so that we didn't lose anything. And all of our images now reside on the cloud, and they actually reside in two locations in two different data centers. But we don't know that. We don't notice that. We don't care where they come from. And because we increased the network bandwidth and the speed of the computers, actually having our images on the cloud, and I know that England's smaller than America, and therefore the distances to send files is shorter, but the images come down at the same speed as they... Well, actually, they come down faster than they used to when we had them in our hospital under the car park. Yeah, that's a good approach, Martin. And, Dr. Hudson, from our side, you talked about terminology in the beginning, right? So folks may be hearing about hybrid model, right? So that's the approach that we are going to be doing. We're going to do a hybrid model where we have a subset of years on-prem, which is it'll be on our storage, it'll be at our data centers, but the rest of the images, say anything past five years, will be stored on the cloud so that the priors and retrievals from our standpoint at the beginning of our journey would be pretty instant. But when we talk about the cloud, though, I mean, the experience that we're going to get from a cloud version or on-prem is in theory going to be the same, right? Because Martin mentioned he increased his piping. That's pretty important, right? It's how do you get that pipe bigger so that the access to those images will be pretty quick so that we talk about that technology and hybrid model where you're eventually going to move to a full cloud. We're right behind you, Martin. Excellent. And Kent, kind of to go back to some of your original question there about even like kind of what is cloud, you know, like we're seeing here, Leonard and Martin do that shift to cloud that there's kind of different varieties or flavors of the cloud, right? You know, somebody can host a VM within the cloud and you can do private cloud, you can do public cloud, kind of depending on obviously how those organizations want to do those different styles, right? Those kind of exist. I think one of the terms, Kent, that we hear often is the term cloud-native. Really, what does cloud-native mean to the end user? And cloud-native isn't just necessarily taking your on-prem servers, right, and moving them to the cloud. It's more about taking the software and re-architecting them, right, so that they actually can then leverage cloud technologies. I think that's an excellent point. That's a really good point, that the cloud is not cloud. There's a difference between just implementing something that replaces your data center versus reworking it into a cloud-native way that allows it to be scalable and adds a lot of other capability. When I talk to my colleagues about cloud and there are a couple of recurring themes that come up, some kind of questions and insecurities, and the first one is, what do you do about security when you're moving all of your stuff from in your data center up to some cloud data center? Somebody address security for me. I'm hoping we'll get to the radiology questions afterwards when I get a break. So the first thing we do is we encrypt them on the way out and encrypt them when they've arrived. So if anyone's somehow looking at the pipe of data, if they do get an image, then the image won't be of use to anybody because it'll be encrypted. And then the other thing we do is we send the patient details separate to the image and we link them back up at the other end. So I couldn't find, Kent, your image and your details in the same file. So that's how you do the security. Then obviously, well, not obviously, is it? Then only the right people can get into the cloud environment. Only the right people can get into your hospital environment because you have security, you have firewalls. So the key is to make sure there's encryption and to separate anything. Well, in the UK, the European rule is patient-identifiable information. And actually, most internal scans are not patient-identifiable information. It's just if it's got your name and your date of birth on it that it's patient-identifiable. So the key is to separate the image and to encrypt it while it's in transit. Yeah, for us, right, we have a very, like, very strong eye security department. So if we're even going to move anything outside of our network, there's a subset of questions that has to be answered as well as their infrastructure, right? So we, you know, besides make sure things are encrypted end-to-end, we make sure we monitor who has access to our instance, right, our bubble, who has access to that, and make sure that we understand, you know, what's that, what are the logs, who has access, when do they have access, and we should be the one to grant that access besides the maintenance and stuff. I think from a security standpoint as well, right, is that the investment that other, like, you know, other security departments have may be more than those smaller organizations, right? The investment in their security departments may be substantially more from a financial perspective as well as resources. So that is one of the huge benefits of it, right? You put that security lock and management to other organizations who are investing a huge amount of money to it. So what I'm hearing is that actually moving to the cloud is likely more secure than the old-school way of doing it. Yeah, and healthcare in general, right? Healthcare, you have a subset of security requirements and, you know, guidelines that we have to abide by just from a healthcare perspective. But, yeah, I mean, the security, in my opinion, is way tighter than what it would be. Okay. So one of the other questions that comes up is the sense that you're losing control of your data, that somehow your data is leaving you and it's not, you know, in your... Again, it's not in your data center, so you've kind of lost control of it somehow. Anyone care to address that question, that concern? You've got a contract, yeah? It's still your data. If you contract for it to run, it's still your data. You can get it back anytime you like. Yeah, and actually the benefits of the cloud are when you're on a platform that's huge, that's bigger than your hospital could afford to build, you can then overlay software and you can overlay services that will actually benefit the patients, benefit the radiologists, benefit the work you're trying to do, will allow you to look at thousands and thousands of similar images, which means that you could look at artificial intelligence, you could look at aggregating and finding out common themes, which you'd never be able to do just on your own in your own hospital. So while your data is somewhere else, actually what you're doing is you're releasing your data to do great things. God, it's hard to do that when you're on your own. Yeah, I mean, think of it as an expansion of you, right? And with the thought of if you wanted to, you can focus on your strategy and your growth and without thinking about, oh, do I have to increase my infrastructure? Do I have to add more servers or hardware? Now you just add resources, right? Because another organization is assisting you with managing that. So it's really just adding the resources instead of having to worry about maintenance, annual maintenance and support costs that are associated with that. So, Leonard, you bring up a great point because in RP, scalability is very important to us. And we're cloud, and we run all of our AI through cloud-based systems and all of our images for clinical review run through cloud-based systems. So let's talk a little bit more about that, the benefits that you get from cloud that you might not realize if you're relying on a system running on your own data center. So anyone have any stories from the scalability standpoint? Linda, I think, did you have your hand? Yeah, I was just going to say, just going to the point of availability from the cloud. When you have your own hardware out there and you have your long-term storage, you have all your archived images, you don't have access to them. And I think that's one of the things from a physician's perspective that if you're waiting for your priors, they're on some server that you have to restore those images, you can't get to them. So it's that availability and access to those images. Even though someone else is taking care of that for you, you have that access. It's real time. You're not waiting. You're not impeding patient care. Everything's there available for you. I think, Ken, one of the other things about scalability to talk here, is generally when you think of on-prem data servers and services like that, if you're backing out those servers to meet how many users you have, you turn on those servers and those servers are always on. Where in the cloud, when you talk about scalability, you're talking about the ability to grow your server environment based off of the number of users that you have within your system. So if you only have one or two users in the system, then your server scales down, so you're not using as much compute power, which saves you then, of course, money, since cloud is really based off of compute. And then as you have more and more people come on in the middle of the day, then your servers can scale up to support that amount of people there. And really, that scalability then also gets you when you think about like software upgrades, right? Zero downtime on a software upgrade, because you are scalable in the cloud and you can shift to other environments within the cloud as well, and then just also no interruptions or disruptions for radiologists who are reading simply because we're trying to do an upgrade at some point in time. Yeah, and to add to that, Thomas, right, is that the redundancy that's going to be behind that, right? It's going to be backed up to a backup, to a backup probably in a different region within the nation. So from a cloud perspective, you'll have multiple redundant database copies throughout the system. You touched on a couple of different benefits of cloud in there, the scalability part. The other one that's intriguing is that you can potentially save costs. That's what I'm hearing. And let's look into that a little bit more, because I'm saying that you scale the compute resources or the cloud resources that you pay for according to what you need and then not necessarily pay for more than you need, which would happen if you were trying to implement it in your own data center, quote, on-prem, on-premise. Any more comments on that, the cost aspect of cloud? In the UK, there's concern about the cost aspects of cloud, but over the last 10 years at least, definitely 20 years, well, over the last 10 years, the cost of cloud as a total cost of ownership of storage has just dropped in the UK. And as more people come onto the market and as people start trying to compete, they're big organizations. So you've heard of Amazon Web Services and Google and Microsoft, but there are a hundred others who will offer you storage and cloud storage. So because it's a healthy marketplace, the cost of cloud actually is going down rather than going up. And also, you can have different costs for cloud. So they have glacial storage. So for images that you are probably never going to use again, the cost of keeping those somewhere for the next 20 years, some of our images we have to keep for 20 years, it's, I suppose you'd say, cents. It's cents a year rather than dollars. And then the ones that while you're actually taking it and moving it is when you cost. But the cost of compared to running your own data center, having your own staff, check it all, making sure that it's cyber secure, cloud costs work out cheaper in the UK. I'm not sure what it's like in the United States of America. Well, you know, it's access to the hardware, I think, is a thing too, right? Everybody has experienced the lack of hardware that we're able to purchase, right? And the lead time for hardware, that can in turn set back a huge project, right? If we're waiting on server hardware, you know, storage, that can affect a project as well. When you talk about the cloud, it's just you tell them, hey, I need more resources. They go, okay. Click, click, and here you go. I don't think it sounds like that, but it's kind of like that. It is like that. From my selfish point of view as an IT director, I don't have to worry about anything that's on the cloud. Like I used to have to worry about it when it was in my own data center and some nasty actor would try and get into my data center. When it's in the cloud, when it's in a big company in the cloud, that security, the cyber security is their bag. That's what they have teams and teams of people protect because they're protecting not just mine but all of their customers. And so the cyber issues are minimized. Yeah. I mean, there's also kind of other areas, right, that you can save on cloud or save on cost when you shift to the cloud. When you think of, again, your on-prem footprints, right, you're going to save cost and happen to buy new servers every couple of years when they go end of life, right, and have to do a whole hardware refresh. You can save cost as well then on your own internal IT teams that are managing these on-premise data centers. I mean, nobody really wants to hear about necessarily losing jobs per se, but from a hospital looking to save cost there in those areas or some cost savings there as you shift to the cloud. And as Martin was kind of mentioning, in the cloud, you're paying them for a managed service, right, so to speak, and they're managing those servers for you and managing the software and the OS patches and things like that, but then you don't need to buy additional staff to do on-premise for you. So some other cost savings areas there too. I think from a staffing perspective, right, it's really shifting resources to where the organization needs them, right? So they may not be managing server hardware. They may be doing some other shiny, cool things for the organization. And one thing I always go back to is that the ease of use for customers, for our patients, right, allowing them to have the ability to view their images externally with ease. I think that's hugely important, and I know the partners that we're working with, that getting access to them, to their images, wherever they're at, is super important to them. And I think that's one of the benefits of being on the cloud is that you don't have to worry about, you know, configuring, you know, a server in a DMZ or whatever it is for them to get access. It's really a click and here you go. Yeah, I was just going to – oh, sorry. I was just going to reiterate what they said there too is, you know, we know we're resource constrained across the board, you know, with resources. And to be able to free them up, you have that cost savings, but then you also have that opportunity to have those resources work on more important projects within your organization, leaving, you know, the vendors to take on the resources needed for the cloud so you don't have to. So cost savings across the board, allowing you to continue to move forward with other priority projects. So what I'm hearing is that it sounds like, in general, you start out with kind of a transition phase, moving from the traditional on-prem solution to a cloud solution. And in that transition period, there must be something that has to change, some training, additional training, or something that your existing IT team needs to train up on to get used to cloud, make it work. Any experience from that? And can you share a little bit about that transition? Digital skills are changing all the time. And actually, I find – well, I've found that it makes my staff more sticky because we're moving to the cloud, because they're picking up cloud skills, because they're doing things that are exciting, compared to looking at old servers and what they refer to as TIN. It's been helpful. We did send them on training courses, but I tend to send my staff on lots of training courses because it's just the right way for IT teams. Otherwise, we'd still be in 1993 when there were 16 websites in the whole world. How long – in the experience of all of you, how long does it take to make that transition to train people up to be able to move over? We did about two years. We could have done it quicker, but the actual migration was taking two years as well, and we wanted to plan it and make sure we had enough staff trained up. But we've still got the legacy equipment to look after as well. So you can't just say stop doing that because there's still information. And then as the information moved across, everyone becomes a bit more pro-cloud and starts to resent all the other servers they have to keep looking at. That's what we found. Yeah, and really, it helps employee engagement, career growth for fellow employees. A lot of times you would see and be able to talk to folks who really had an interest in it and who had really been studying or going to school for it, and they'd just been doing some other work with an organization. It opens up career opportunities, and that's key to keeping your employees happy. That's super important as well. And just kind of add to another point of that, and maybe not from an education, but I think every organization's journey to the cloud is a little bit different. Some are slower and take components to move to the cloud, while others are more aggressive and willing to go immediately all into the cloud. I think it's a little bit different at every organization. So we've covered a lot of reasons to not be afraid of the cloud and reasons that very strongly favor going to the cloud, good reasons going to the cloud. I'd like to do a round-robin and ask each of you to give us the top three reasons why you feel organizations should move to the cloud and maybe a little bit of reasons behind that and any kind of personal experience that may help in our conversations as clinicians with our fellow radiologists and our hospital administrators. So, I'll start with you, Leonard. Yeah, so my top three, in my opinion, right, is scalability, availability, and being able to meet the strategy of the organization, right? I think, you know, when we talk about ease of access for our patients and even, like, rural areas, right, some of them, you know, it's hard to get to them. I think that for me would be the top three. And from my experience, it's a lot of it is adoption, right? How do we get our customers to adopt the cloud? And, you know, what does that education look like? How does that, you know, how do we get our operational staff to really better understand like what this webinar is, right? How do we get our customers and our other organizations to adopt cloud solutions? Linda? I'll probably repeat ourselves here. So, I think security is a top one, scalability, and then availability. You know, from a physician's perspective, that availability to read anywhere at any time is huge that being cloud native applications that allows them to be remote, be able to get to their images. And now it's not just, you know, you have those advanced viewers, you have access to AI when you're in the cloud, it gives the complete capabilities to our physicians here, so that they can improve the patient care that's out there and actually, you know, hopefully have a better work experience during the daytime. But Martin, I'll let you go next. I've got to bring it home now. It's all those things. But it just makes everything a lot easier. You get the right cloud provider, it takes away 60 to 70% of the job of managing any PAC system, any imaging system, it takes all of that heartache away, which means that you can then start improving the software, you can be more responsive to the end users. And, you know, it just builds a platform, which allows you to start doing the exciting things that help the patient journey, help the clinicians, and innovate. So we wouldn't have been able to do the research on AI, if we hadn't have had images on the cloud. And Thomas? Yeah, I would say my top three, probably my first one, I think is going to be around improved security. You know, I think we're all very well aware about cybersecurity these days. And from a healthcare perspective, how critical and important that is from, you know, the patient's perspective and maintaining, you know, security of the patient's data. There's just a natural security oftentimes in the cloud, those providers have spent years building up security that sometimes we get better security than we would if we were on premise, of course. I think that my second one is going to be about reduced capital costs. You know, as you shift the cloud, oftentimes you're shifting to a SaaS model, which is maybe a little bit more budget friendly, it's a more predictable pricing model, then trying to come up with capital costs every time you need to do a hardware refresh or purchase an upgrade or things like that. I would say my final one is probably availability. We haven't really touched on availability yet as part of this conversation. And I think that's also important. You know, being in the cloud, those images then become more available to the end users, basically being able to access those images at any time at any place, whether you're on the go or whether you are within the hospital network itself. So those would be my top three. And then that point about changing to more of an operating cost from capital expenditures, we haven't really talked about that in detail yet. Let's touch a little more on that. Any more comments on that? Martin, has that been your experience? Yeah, I'm not really sure what I can add. Does it change your budget? Does it really change the way you do your budget when you move to cloud? So in the UK, they have a weird difference between capital funding and revenue funding, because the way, you know, all of our health service is national, the government give us the money, the government give us things to give us money to buy things, which exist in there. And then it also gets us capital money, but it also gives us money to pay for things that don't exist like people's time and storage. And in the UK, there's been a problem because cloud costs are revenue, but the government likes to go out capital and the old days buying a server and buying a data center was all a capital cost because you could spread it over 10 years or the lifetime of it, whereas for cloud, it's an annual thing. But because I said it earlier, it doesn't cost as much. The argument is, well, why don't you just give me less money of a different flavor? It's a strange government thing, capital revenue. But we have better use of our budget having gone to the cloud. And long term, what we'll find is, you know, we've moved all of our images. We're one of the few NHS hospital trusts in the UK that have moved all of their images onto the cloud. I thought everybody else had done it, but I was new to hospitals. So I just thought I'd catch up. And by catching up, I found I was one of the the first cloud, which is probably why I'm on this call, one of the first cloud people going. But what we've done since moving our images is we've moved our electronic patient records and lots of you'll be using, I don't know, Epic and Oracle Cerner, they're all cloud based systems. So what the trend now is everybody's just writing things that are on the cloud. So in 10 years time, it'll be really rare to go anywhere and find a data center in or near a hospital that the hospital owns in the UK. But the costs will continue to be manageable and will go down. That's what we're seeing, what we're realizing. So I think a bit complicated from a finance point of view, but the right decision from a spending public money on government services point of view. So for our U.S. based panelists, impact on budget. Yeah, so, Martin, we still have rules like you out there, right? What can be charged capital, what can be charged operation. I think from an operational standpoint, it allows us to understand what our budget is for next year, right? So, and it's different funding, we can't tap into the other budgets, but it'll help us forecast what we need for the following year. So, I mean, we've been able to identify run rate and have a set budget for us. So it's easier for us to plan. Okay, excellent. We have a couple of questions coming in, and we'll be getting to those very shortly. Just a reminder that if you do have questions, please enter those, and in the next couple of minutes, we'll start addressing those. All right, what is the, so we talked about changing the budget. Is there any, what are the arguments that I can go to my CFO type people and tell them, hey, we're going to get a positive return on investment by switching over to cloud? What are the first things as a radiologist that I need to have in my head when I go to talk to our financial people about this? Top three points that I need to make going to them to try to convince them that this is worthwhile. I'd invite them to go and have a look at their data center and say, this is where, because they're always typically in the basements of hospitals, which are always typically not as clean as the wards in hospitals and a bit grim, and there's no light. I'd take them down there and have the conversation in the data center and say, your ability to treat patients is in this room. How happy are you that it's just in this room? How safe do you feel you are? What risks that it's just in this room? How safe do you feel you are? What risks do you think you're running by just having all of the images for the last 20 years in this room? So we have a conversation about what our options are. That's the way I'd do it. I wouldn't even go to their office because that's probably shiny. Take them to where IT is, show them what the real risk is. And that's what we did. We showed them pictures of the data center and said, everything that we're relying on for patient flow, patient care is in the wrong place. Let's make a move. So that's how we did it. But that's, yeah, I'm not sure. I'm not sure, but everyone's got that opportunity. So true story. One of the hospitals I used to work at, one day, and they had a data center on-prem, not in the cloud. And one day, one power supply went out in the data center, took down the whole hospital. That was it. We couldn't function. So the hospital administration immediately started looking at cloud solutions after that, understandably. All right, great. Any comments before we move from the panelists, before we move to the question and answer period? Okay, great. Looking at your questions here, we'll start with the first one. Can you elaborate more on if and how you use AI in the cloud? If panelists don't mind, I'll take this one because this is what I do for a living. So all of our AI is run in the cloud, and there are a couple of really good reasons for that. The first one, when you run AI inference, when you run a set of images through an artificial intelligence model, you're not using typical computer-type hardware. You're using GPUs, graphical processing units, or tensor processing units. And so it's kind of specialized, and it's much cheaper and much easier to rent those resources in the cloud and to use only what you need. So 100% of our artificial intelligence solutions run in the cloud. And since we only use what we need, it makes it, from a cost standpoint, the most efficient possible. A related question, I'm sorry, any comments from the panelists on the advantages of using AI in the cloud? You're absolutely right. Because while you're doing the research, AI does take processing power. So you ramp it up when you need it, and then you turn it off again. It's almost like a bus fare, isn't it? You've not bought a whole bus and wondered why no one's on it. You've just paid for the bus fare while you're doing the journey. And that means you're not building something that you only use once or twice, which is why the cloud's cheap. Because really, it started Amazon, who we've all heard of, realized that they had to buy enough servers for their peak times, and they started selling off their space. Because Black Friday and Christmas or whatever else you have there at their peak, but their servers still exist when nobody's doing their shopping. So we are using, in some of our instances, some of that spare capacity when Amazon aren't doing any trading, or not doing as much trading. So that's what the cloud is. The cloud's saying, let's just try and fill up all this redundant space, which is why it's cheap. And from a practical, clinical aspect, just an example of how this would work, if you look at mammography AI. So you take a mammogram, run it through the artificial intelligence model, and it tries to identify the cancers. Well, breast centers aren't open 24-7. They're open during the weekdays. That's when you need the compute power. So you spin up enough cloud resources to handle that volume during the day, during the weekday, and then you spin them down at night and weekends when you're not using it. So you make more efficient use of what you need when you need it. Let's see. Can you elaborate on the benefits to being in the cloud when looking to add on cloud-based services like advanced visualization components or AI algorithms that we may pick and choose rather than being limited to solution-native capabilities? Let me try to summarize that question. So talk a little bit about the advantage of using the cloud to get access to a wider range of services that you might not otherwise be able to easily implement if you were relying on an on-prem solution. Any experience with that? Any comments on that? I think that's hit the nail on the head. That's exactly why you do it, because once you've got your images there and they're separate from the software that you use to look at your images, the number of companies coming into the market who can actually do those things for you or can put an interface in between images is so much easier to do because they don't have to come and cite. You don't have to see whether the software works on your servers or by another server. There's a massive ecosystem now of small companies who are trying to do the thing that you've just described, Kent, which is radiology and looking at images and showing 30,000 images to a computer is a lot quicker than showing 30,000 images to an individual, and then the computer can detect patterns rather than the human being. The human beings are still better than the computers, but the computer is doing a lot more. It's being exposed to a lot more, so it can do some of the basic stuff. I was just going to say, oftentimes, as well, being in the cloud, when you're trying to add on services, it's oftentimes actually easier in the cloud, because in the cloud, we can spin up those environments faster when we talk about, again, scalability and be able to spin up those virtual environments faster in the cloud than it is on-premise. If I want to add on advanced visualization, I've got to then make sure I have servers, and then I've got to spin up virtual servers, and then I have to figure out how to install the software. Oftentimes, in the cloud, it's an easier spin-up faster to add on those additional services like AI or advanced visualization, as the customer asked about. And it's also easier to spin them down. So, say, when I can be using that functionality, we just spin it down, and we only pay for what we consume. And as Mark mentioned, there are a lot of ecosystems now, marketplaces, if you will, that make it much easier for a health organization to try out new things, and if they don't work out, yeah, it's okay. Like Melinda was saying, you spin them down, you don't use them, you're done. But that's the approach that we take. We try things out in the cloud, and if they work, they work. If they don't, they don't. And it reduces the amount of effort that we have to put in to try new things. Yeah, and I think to add to that, Dr. Artin, I think the collaboration expands outside of your organization, right? Collaboration with even AI algorithms expand beyond just our team. It goes to other teams and other organizations. So, I think that expansion, I think, is super important when it comes to patient care. Next question says, to the merge leaders in designing and developing cloud-based offerings, how do you get insight into clinical stakeholders' needs? How do you know when you've got it right to meet those needs with your new products? I'll start that one off. We work very closely with our customers, and we're gathering requirements with them, we're having conversations. But as we're going in and we're actually doing that development, they're part of the process all the way through the development. They get early access into what we're doing, be able to give us feedback so that we're on the right track as we're building these products. So, a lot of feedback from our customers. Thomas, you want to add to that? I think you hit the nail on the head, right? It's making sure that we work closely with our customers to understand their needs and their requirements. And we also go down from a merge perspective, we do like a sponsor user program where we have customers who we consider our sponsor users, they provide input throughout the development cycle itself. It's not just a, hey, go do this feature, we go do it and then come back and say, hey, we're done. It's, well, no, like, what would you like to see? How would you like it to work? All right, let's go back, we'll start to design it. They work with our UX designers or our architects. This is how it's going to work and operate. And so, that's one of the key ways that we also accomplish that. Make sure that we meet their needs, right? To meet their needs, we make sure we talk to them and understand those requirements throughout the entire process, not just at the beginning. Yeah, I'm experiencing that firsthand, so I can vouch for Linda and Thomas, right? That collaboration and partnership is definitely there. Okay, we've come to the end of the questions that were listed. One of the other questions that I hope we answered in the discussion was, are we talking about referring, when we say cloud, are we referring to fully in the cloud or an on-premise hybrid and the advantages and disadvantages of both? I hope we've addressed that. And it sounds like that a transition phase, going from on-prem to cloud and then having kind of a hybrid model during that transition is the way that most organizations are doing it. Okay, a question for Leonard and Martin. What is the dynamic between your teams and your clinical stakeholders when a new innovation turns up in the market? Are you seeing any changes over time as to an IT when a new innovation turns up in the market? Are you seeing any changes over time as to when IT leads the evaluation versus when clinicians lead? So, I think the important piece is developing a committee to talk through what is going to affect patient care, right? So, for example, an AI committee, or including operations, finance, and technology, so that we can talk through what is going to be the strategy for the organization. Because there's so many different options out there that we can't, from a management perspective, we can't just implement them all. So, I think having a committee is super important. Yeah, absolutely got to work together. From an IT point of view, we try and see what's available, but in terms of a clinical tool, we want the clinicians to choose the tool because they understand their job. They're the experts, they're the people, and we've turned it around to support the clinicians. A lot of my peers are doing the same thing. This, you know, there isn't an IT director I know who's better at deciding how to do radiology than a radiologist. There's not a single one. Work really closely with them and support them is the answer. Actually, a lot of the systems that are coming out there are being co-designed with radiologists in small IT companies. This is exactly how it should be. So, our trust did a lot of the studies. This is exactly how it should be. So, our trust did 30,000 studies, which is a paper that RSNA have published on lung nodules. I had nothing to do with it apart from to make sure that the access was there and the things were going fast enough and it was the radiologists that did all the work and so on. Yeah, let them choose. I'll say for us, we have a team that's composed of radiologists, IT, or what I call the server team that handle the cloud stuff, and then data scientists that are trained in data science. And it helps a lot to be able to speak between all three of those domains because sometimes the radiologist wants something that just isn't feasible, or from an IT perspective, something might be too costly or we just don't have access to the data. And the data science people can tell us, oh, well, yeah, that'd be great if we somehow had access to that data, but it's going to be too cost prohibitive to do it like that. So, the exchange of ideas and information between those different domains helps us tremendously. All right, we have exhausted all of our questions. I'll start doing a bit of a wrap-up here. The move to cloud has been going on for a long time, a long time. And believe it or not, healthcare is generally behind the times. And this is no exception, but we do clearly see that there are benefits and not just benefits, but real financial advantages to moving to the cloud. And some of the things we've talked about are the improved security, which surprises a lot of people that I speak with, and the improved scalability, availability, and then moving from a more of a capital-type model of budgeting to an operating expense-type budget to handle the IT resources that you need. Is there anything else that our panelists feel like should be, that radiologists should have in mind when they go to speak to their colleagues or administrators about cloud and the benefits of cloud and why we should try to move ourselves to the cloud? I can start. I think some technology is different from even five years ago. Just the advancement and just how we access data, the speed we access data is different than how it was even five years ago. So if access to images outside your network is a concern, there's definitely solutions that are out there that can help address that. I think, you know, coming from the healthcare perspective, I think we need to think about patients. We've talked a lot about the benefits of this, and all these benefits are leading to improved patient care. We have access, we have creating efficiencies for our physicians, we have availability. Yes, there's cost savings and all that, but I think it's the patient care and our patients that also get the benefit of our physicians being in the cloud and having the images and be able to turn around and have accurate interpretations. I don't, yeah, I'd make sure that you're talking about what it is you're trying to do in your profession and for your patients, and then just try and completely avoid talking about the cloud. Just say, have you got the technology in the background to support my ambitions? Because what you'll find is if they aren't in the cloud, they won't have that. So if you're trying to make a case for doing more with AI and doing more with your data and your things, you don't need to talk about the cloud. They will have to come to that conclusion themselves, and then they'll be proud of themselves. It gives an IT director something to do. All right, any other closing thoughts before I close out our webinar here? I was just going to say, don't be afraid of the cloud, right? Don't be afraid to go talk to your executives, speak to your IT, your CIOs, right? And Kent, as you kind of mentioned earlier, across multiple industries, cloud computing has been in the market for decades, right? And although we're kind of newer to it in healthcare, the technology has advanced so far these days and continues to advance incredibly far for cloud. So don't be afraid. Go talk to your IT leaders and your CIOs and start having those conversations today. All right, excellent, excellent. Well, thank you for joining and participating in today's conversation and to the panelists for sharing their knowledge and time. I'd like to thank Meritiv and RS&A for hosting this educational webinar. You'll receive an email from RS&A when the recording from today's webinar is available in the Online Learning Center. Please visit the RS&A website for upcoming education events. And thank you very much to all of you. Thank you. Have a good afternoon, everybody.

cloud technologies

medical imaging

radiology

cloud-native applications

remote access

AI implementation

cybersecurity

cost efficiency

patient care