waited for more folks to join us today. My name is Joe Sasson. I'm the Chief Commercial Officer and Executive Vice President of MedAxium Ventures. And with me today is John Kammerman, who is a Senior Product Manager over the Enterprise ECG platform at Philips. And back when I was in graduate school, my advisor had a saying, which was, "'In God we trust, all others bring data.'" And we've all heard some variation of that throughout our lives. And we really need solid data to be able to evolve our programs and to be able to make really good decisions about resource allocation, strategy, et cetera. And so what John is going to do is talk about KPI-based strategic management today. And he's gonna give us some insights from where a lot of data can come from in terms of managing your practice, whether that's arrhythmia data or program management data. And so we're gonna turn it over to John here to dive in, share some of the opportunities, of course, not only that Philips has, but really regardless of platform, the learnings that we can take away to better manage our programs. And so John, thanks so much for being here, offering your expertise and really grateful for that. Before we dive in, I wanted to remind everybody that in the chat box on usually the right side of your screen, you will find links to access the presentations. Now, we may put in that same link multiple times throughout this webinar as some folks will certainly be joining as we move forward. If you would like to communicate with any of the hosts because you're having a challenge of any kind, or when you are ready to send any questions you have to the presenter, please use the Q&A button. We will not have group chat going on in the chat box. Any questions you have will come directly to us and we will make sure that they are directed to John to be answered. And again, if it's logistical issues, or if you're having any sound or connection issues and you can still use the Q&A, we'll try to assist you through that channel. So thank you all very much for being here and with no further ado, turn it over to John. John. Thank you very much, Joe. Let's get started. Thank you again for joining us on our webinar where we'll discuss KPI-based strategic management of cardiology departments and how we can leverage the day-to-day data our teams are collecting and our physicians are producing to help us achieve our corporate strategic initiatives. I've had the pleasure to travel to hundreds of hospitals over the last few years meeting literally thousands of cardiology department managers, IDN level cardiology vice presidents, cardiology vice presidents, technicians, physicians, and the like. One thing I've noticed is that managing a cardiology department is a great challenge, but I really wanna emphasize that we're great. We're all here to provide patient care, to improve the health and welfare of our communities, but we live in this dynamic world where we have very well-defined corporate business objectives, but our real day-to-day world is living with these people that are sick and probably not doing everything we ask them to do and our staff who has a real life, they're helping their kids, their parents, they're having personal struggles, they're having personal successes, they're going on family vacations. It's a very dynamic, infinitely variable world on one side and a very numerical defined world on the other. What if we can mix these two things together using the environment that we manage and use the actual data from the clinical information systems that our teams are using to help drive our corporate strategic initiatives? At Philips, we believe this is very possible. Today, we'll cover exactly what steps we would recommend you could take to get to the point that you can easily look in a dashboard to see how you're performing against your corporate strategic initiatives, no matter what they are. Now, when I say no matter what they are, they can really be pretty much anything. These are some corporate strategic initiatives that I found on several different hospital websites. Sometimes they're very, very general, inspiring people, healthy communities. Sometimes they're more specific, retain staff, partner to transform care. Sometimes you don't even know necessarily what it's talking about. High value delivery, delivery of what? We assume healthcare, but not all corporate strategic initiatives have the definition we need to actually manage our labs. Mixing the quadruple aim with health equity is something that I think is important to all of us. So consider your corporate strategic initiatives, and for the purposes of today, try to align them with something or multiple things in the quadruple aim. If we look at the actual environment that you're managing from a data perspective, it is highly diverse. You have many different devices producing data in your environment. You have several different departments. Some of you are managing CT and MRI for cardiology. You have patient monitoring on one side. You have echo on another. So you have many different types of data. These days, that data is being analyzed by AI and algorithms before it gets to the physicians frequently or to the administrators. Then the physicians are living in cardiology applications to produce a diagnostic report, and that diagnostic report is being visualized throughout your entire ecosystem, throughout all of your hospitals, throughout your IDN, sometimes in the EMR, and sometimes in the clinical information system. And to make this problem even bigger or make this challenge even bigger, we now have patients at home that are being monitored on things like Philips ePatch and MCOT while the physician is still at the hospital or clinic. Your ecosystem is gigantic. On top of that, we manage an environment for diagnostic precision that is highly variable at one point, really depends on our processes and the standards that we put in place across our departments or in our department. We're going to look at the platform from the perspective of data. One thing that we should do with our analysis tools, the tools that we're going to be using to produce our KPIs is to make sure that we hear the voice of our people. So as we're looking at our technology platform and its capabilities, ask our people how these things are working for you, how they work in their environment. What can we do to improve your workflow and your patient outcomes? They know what's going to happen. Techs, physicians, department directors, they know their people, they know their processes, they know the strengths and weaknesses in those areas. And your vendor like Philips knows the capabilities of their platform. I propose in this environment that it would be very difficult to have a solid platform for diagnostic precision without the partnership with your vendor. I highly recommend that you allow your vendor to tell you how to best use your devices according to your standards so that you can govern the quality of data coming into your environment. The beautiful thing about your environment is that your day-to-day workflow has a wealth of strategically important data. When we consider this data today, let's just take a look at this DIKW hierarchy. So today we're going to talk about how we make wise decisions with the data we have coming from clinical information systems. But that data takes a journey on the pathway to wisdom. We have all of these devices collecting data. Our clinical information systems are collecting data. There is a flood of data, as people might say, but this is not a bad thing. If we get the right team in the right place, who knows what the data means, how it's defined. By the way, you need your vendor to help you with that. Who did it, where it was done, when it was done, and why it was done. And we have a means to evaluate the quality of the data coming in, or maybe even the difficulty of the environment. Was it a difficult patient to work with? If we can gather this information natively from the data and devices that we have in our ecosystem, then we can start making really good decisions based on high quality knowledge. Add context to information. Here we're defining data. Here we're adding context to data. You need the right team next to you to do that. So when you find that technician, when you find that physician that says, you know, if we look at this information and who took it when, and where, and why, we actually find that it's not bad that, for example, that physician took a long time on that study because they produced a very high quality study with a very difficult patient. Turnaround times might take a different perspective when you have the right team in place telling you what the information means. So surrounding your people with the right team, especially vendors who understand their data very, very well, like Philips, is a huge advantage to you. As a matter of fact, I proposed today that it's very, very difficult to make consistently good decisions that get your team excited to achieve the corporate initiatives without having that team in place to help you interpret this data coming in. But again, I think we get, we look at data as being overwhelming. It sure is not overwhelming if we can use it to make good, highly knowledgeable decisions. How do we get there? Where do we start? This is an actual tool that we use at Philips with our customers. It is very simple. Please simplify things as much as you possibly can. The purpose of this is to look across each study type. For today's example, we're going to use ECG solutions. It's actually where I am currently in my product management career. I'm in ECG solutions at Philips, so we'll concentrate on that. You'll see later that this extends to Cath and Echo as well. Take each study type across your ECG solutions and just put them in a table. If you go to your team, you'll have one person that can answer questions of which vendor do you have for the device producing this data? When you have your vendor map together, today you can see this vendor map. I have put Philips, the Philips name, where this particular hospital has Philips devices. I have put vendors that are not Philips in their own box and have colored those boxes. This will have your vendor's name in it. I typically do assign a certain color to a particular vendor. So in this case, Philips is blue for a very specific reason. And you can see that these other vendors only show up once in my environment. Sometimes this one might be purple and this one might be purple. This is not just to note which vendors you have. If you know this yourself, I recommend not necessarily filling it in yourself because you wanna have a discussion with your team. So ask your team, is it easy to input data into this system? Is it easy to get data from this device, you might ask your analytics team and incorporate it into your corporate dashboards? Is it meaningful to have this data well-defined and a ton of data here? So let's say this stress system is producing, your team says low quality data or very little data. And if it's doing that, does it really matter to my end outcomes or not? That's a decision that we need to answer later on using the knowledge and information we can gather from our team. So I'm not saying that three stars at this point is even better than one star, but hopefully having this conversation with your team, who does what and how good are they doing it? How easy is it to use? We'll give you a map and open up conversations with your team that really help you manage this conversation with your leadership team. I literally jot this down. My team said, quote, we have to call our vendor each time we build a report. I would say that's a low quality score for vendor data. The vendor cannot export that information. Maybe you hear this frequently when you're asking for your weekly reports. The data is a total mess in that system. Jot down exactly what they're saying, even if it's good when you're discussing that previous vendor map with them. This is a very, very common problem that we see. Sometimes it's really not that difficult to get the data out of a system, but only one person in your environment knows how to actually get it. Big, big problem. You can see here that it can be done across really any system in any clinical domain. Today we're talking about cardiology, but here is what you would do to evaluate your diagnostic cardiology imaging platforms. Who's the CVIS? Which ultrasound do you have? What 3D echo vendor are you using? 3D imaging vendor? Who's your nuclear stress vendor? Who's your cardiac MRNCT vendor? Who's your cath lab informatics vendor? Many hospitals have different vendors and adult in pediatrics. This is very, very easy to extend across any clinical domain. So now with this discussion on your team, you should have gathered very good contextualized data, but now let's really dig into the actual clinical data. Today, we're going to look at another map that we very frequently use, and that's a typical just workflow map. So let's take the workflow map that we have using our MCOT device, mobile cardiac telemetry, so at-home patient monitoring. The physician orders the exam. The patient is reconciled with the device. The exam is performed. The vendor produces a preliminary study report. It goes to a physician inbox where they read it and it's reported, and it is sent to the EMR where it's billed and is made available for reference to other clinicians. So if you take a look at this workflow, this could be a cardiac MRI. It could be an ECG. It can be a stress test. Nearly every single device and every single clinical study follows this exact sequence of events. Now, if we look at that sequence of events, we can also map it out a different way, and I do highly recommend reviewing these two maps with your team and asking them questions. What are your challenges in this going from this stage to this stage? What are your challenges going all the way to completion of the study? That's a more difficult question, but if your devices and clinical information systems are feeding you really good data where you can see challenges in your databases without asking your team or asking your team very precise questions, then we've really made a big difference. The devices tell us what data we can get. A study is acquired. It's ordered or it's not ordered, maybe at an emergency ECG situation. AI and algorithms process the data sent maybe to a fellow inbox if you're at a teaching hospital or it's sent to your attending physician's inbox where it's prepared to be read, organized and prepared to be read. Sometimes it's overread and it's completed and billed. Sometimes it's not billable. I made discarded and not billable pink here because these can be very, very important to you. If you know this workflow and you start to see why was it not billable? Why was it discarded? Was it a low quality ECG? We can start to ask questions. Who did it? What type of study was performed? When was it done? What department was it done in? What floor is it on? Do I have a problem at a hospital? Why was this being completed? Now we can start looking at things and giving more information, for example, in turnaround times, just for an example today in turnaround times. If we know who produced the order, what order was sent, when it was completed, and why it was sent, we can ask big questions that can start to feed strategies and corporate initiatives and department initiatives like who are my best referral physicians and what regions do I have gaps? What are my outliers and where are they located? For example, I see that I have an entire team in this department that always produces a low quality ECG. Do I have a cultural problem happening there that I need to go and address? Do I have a manager who's pushing in a certain direction and causing this by their initiatives in their department? You can start asking very precise questions. What is my team's workload? Do I have capacity in my system to add on more cases? Maybe I have capacity and I can add a new cath lab. That's an example from a hospital that we were working with that had a single cath lab. As they started evaluating the workload of their team, the referrals that they were being given, that they could very easily afford to add a new cath lab and significantly expand the services that they have. Another customer that we were working with was looking at their staff overtime and weekend hours, and they were really struggling with needing to hire travelers. In that problem, it's costing them a fortune to manage their staff. When they started seeing when their travelers were most required, what the workload of their travelers are, and the current workload of their team, and when they were working, they talked with their team and asked them, would you like to have weekend hours and overtime hours? We think you can handle that if we no longer hire travelers. They were super excited to be able to get more hours and really financially benefit. They had a really great environment where they could improve the satisfaction of the staff and lower their cost of staffing at the same time. They would argue that they also improved quality at the exact same time. Asking big questions can be super easy if you're just looking at the data from this different perspective of who did it, when, where, and why. Let me give you an example of a dashboard here. This is a department throughput dashboard. We could have multiple departments over multiple hospitals and regions here. This is a simple layout for the purpose of this webinar. This one shows what department did the study, which inbox did it go to, who signed that study. When we're looking at these things, it's not just giving us a graph so we can quickly glance at it. I can look at this graph and quickly sort it by clicking on anything, sorting it, filtering it, and looking at who is in that graph. What is the precise data in that graph? It's not just a graph giving me a general idea of what's happening. We also have the discrete data populating a table below it that can say, you know, we really do see we might have a training problem with these physicians right here or somebody needs to talk to these physicians about being more serious about the turnaround time of their studies. So it's a combination. A good analytic system should accomplish two different things. Give you a quick strategic overview. At the same time, give you detailed data that allows you to make clinical decisions and put out new policies, procedures, training plans, whatever you need to help you accomplish your strategic goals. So layout also communicates things to your team. If they see this graph, they're going to see that they're outliers. How do we manage that strategically really has to do with you and the culture of your team. This is where wisdom comes into play. Not everyone wants people to feel like an outlier. Others feel that peer pressure is healthy. Every single team can be very, very different. That's why we need to have conversations with our teams, see how they're working and acting. And that's where the real fun of being a director comes into play. I know my team. I know what initiative is going to help us improve these things and how to do it safely and produce a good culture on the team. That's a wise decision. But it's not just about turnaround times. Adding clinical context will help your team tell you more about the data. So when we add operational data and give it some clinical context, it'll be much easier for us to interpret our data to make good decisions with it. Here's an example. If I have a quality score in my data environment or I have a difficulty to produce a clean study score, which we do in Philips, let me give you an example of a quality score. If I have an ECG that is missing lead sets and I can and I can qualitatively identify that in my ECG management system using data, not actually looking at waveforms, but have it tell me exactly what studies are low quality, I can quickly drill that back to the person who performed that exam or the department that is producing those reports and say, we might need a very precise training plan for this group of technicians across my hospital system. But you can be super focused. You don't need to do broad general training that really doesn't help anyone. You can pick a few people out, maybe assign a mentor to them and really improve your staff satisfaction at the same time as improving your clinical quality. So if we have difficulty metrics, for example, if you have an echo patient that is obese, we can have those two things identified in our database and know it's a very difficult study. So maybe my physicians are complaining about quality, but quality, but perfect quality was never an option. So we really need to combine these things to give us real accurate contextual data to help us make a wise decision in our environment. So it really is about the device's ability to produce data that is useful to you. You need to choose vendors who can give you very, very precise data. For example, variability, looking at super specific aspects of an ECG to find patients within a population. Your ECG management vendor needs to think about data quality down to the device level. If we look at turnaround times again, if your vendor has not flagged or tagged that data timestamp, and if they don't give it to you in a database, there's no way for you to get it. It just cannot be gotten. So you need to find vendors that understand your strategic initiatives, why certain data elements are important to you, make sure that their devices capture that data for you and export it. And I would like to say that's one of the most fun things I have about working at Philips because we have been patient centric for so long. We have deep, deep experience getting the right high quality data at the device level and giving you options to put the workflow in place that help you get high quality studies over time. Now, of course, there is another aspect to data management, and that really gets into the scientific side of things where we start integrating EMR data, getting deep, deep, deep clinical data, like exact measurements from within our AI producing algorithms, exact measurements across, let's say, for example, every single data point in a 12-lead ECG. We're not going to cover that as much today, but you'll find in your larger institutions that if you can pick, for example, every single patient that has an ejection fraction in the 40s and a right bundle branch block, so information coming from both the echo and from the ECG, then we can start searching for patients in our patient population that may have fallen through the cracks in our care plan for them. So did they follow through? Did they come to the cath lab? Have they actually gotten the procedures that we prescribed for them, that we ordered for them? Did they ever show up? We can figure out why they're not showing up, and if we see it in a population, we can really start to get insights on health equity. Do I have a significant problem in this area of the city where patients do not sit in the ER long enough to be able to get the diagnostic care that they need? Do we need to put an e-patch on them right when they come in so that we can at least get that data if they go home more quickly? There are some very good examples that if you can see where your patients are getting care, where they're falling out of the care path, then we can put policies, procedures, maybe new devices, new services in place to help us solve that problem. If you can communicate that to your upper management, our experience is that they will invest in your department, that your initiatives tie into the corporate initiative, and you are able to track that in a dashboard. So in your daily management of your team, you can see where you stand and continuously improve by hands-on management, hands-on management being getting your solution experts in place, assigning mentors to people, making sure that your team oversees your team to go forward with accomplishing the goals of the institution. If we know we're on track and know where to concentrate and where we don't need to concentrate because we're green, we have a higher ability to actually produce the care that we desire to produce from the very beginning as we got into our positions. So what I would really like to emphasize in this pathway to wisdom is that you can get your teams excited to help you accomplish your goal when you say, let's do this team, and they say, yeah, I want to do that. I want to accomplish that goal because it totally applies to me in my life. That's usually what gets them excited when they see something that they're making a difference in their day by the clicks, conversations, protocols they're following safely and accurately. When they see that they're making a difference in patient care, they'll be excited to follow your leadership. The way that you do this is really you, right? It's your personality, the way you work with your team, the relationship that you have with your team, and that's what we want to empower with our clinical data capture, clinical data improvement and clinical data knowledge. So I'd like to say here that it really is a beautiful management thing when you're able to get the resources you needed aligned, people on board who are sharing their experience with each other, sharing their insights with you, really operating at their highest capabilities that all of your goals are aligned. And when you are able to put the standards and processes in place to highly govern your care, including governing the quality of data coming into your environment, you can help people align. You help clinicians align with IT. You help IT align with clinicians and you help administrators align with everyone. And when you have your vendor on board and aligned with you, you know how to leverage your platform to its maximum capacity and what roadmap you need over time to improve the quality of the data coming into your environment. I do propose that a single vendor is very, very helpful in that. It's not just helpful operationally from a purchase perspective. It's helpful both clinically and clinical operationally in your departments. We can help you leverage the data that you're getting to the best of its capabilities because we know our systems well. We can coach you on how to do that and train your teams how to use the systems. So you really do need to partner with your vendors to produce excellent data. I hope that you have been inspired to put great data platforms in place. We want to support you as much as possible to make wise decisions in your department. And I'm excited to see what we can do when we start thinking about data slightly differently to produce the outcomes that our institutions are requiring of us. Best wishes to you all. And I hope that you have great happiness in leading your teams to providing better patient care. Thank you very much. Thank you again for... John, thanks for spending some time to really get into the depth there and share your expertise with us. I want to remind everybody that at the bottom of their screen, the Q&A button, you can click that. And please, now's a great time to submit any questions you have for John. But John, I've got one and that is, what is the name of the dashboard? You didn't mention how you guys brand that. And I was just curious. Yeah, that is called Philips ECG Insights. And those are just a few samples of the screens and dashboards that we produce in that environment. Okay, got it. I appreciate that. Because it's Philips ECG Insights, do we need to have Philips products to use something like that? Can you integrate from other vendors? And is there a limit to the number of vendors you can bring in? What does that look like? Yeah, that's a really great question. And I mentioned this a little bit in the presentation. But certainly, it's nearly impossible for any organization to forklift their entire cardiology platform and convert to a single vendor. So there is quite a bend of vendor neutrality capability in the platform. But of course, the more that we kind of prioritize where you need your data to be best first, we certainly have more control over the data if it's all Philips applications. So it's a, yes, it sure does help if it's Philips, but it is also vendor neutral, especially in certain environments. Got it. Okay. Very helpful. And this will also help manage the implantable data. That's correct. Yes. The CIED data. Good. Again, everybody at the lower portion of your screen, please submit any questions you have through the Q&A button. I want to build just a little bit on that integration piece of other vendors. And my question is, is, you know, everybody's worried about tapping their IT resources these days. What does that integration look like in terms of how difficult is it? Is it user-based? Once IT approves the, you know, the ECG insights platform, do we need to go back to IT for all of those integrations? So what does that look like? Once I'm up and running with the platform, how hard is it as I change out vendors, et cetera, to bring that in? Can you elaborate a little bit? Yeah. I want to express two different perspectives on this. First of all, this is one of the major benefits of having Philips applications that are feeding the dashboards in Insights. And that is that when we connect to our platforms from Philips to a Philips platform, from Philips to a Philips platform, that connection is secure when it's in the server environments or the cloud environments that you're already using with us. So it's very much one quick, it's significantly easier to get through these IT hurdles of integration and security when they're all Philips devices and information systems sending information into Insights. Now, in a vendor, depending on which vendor you want to connect and which kind of data you want to connect, there are several different options. One option is that we can get data via HL7 ORU interfaces, so discrete data. If you're already sending those interfaces to your EMR, for example, that data to your EMR, there it is, you're further ahead, let's say, in the integration journey. So what really does help, and actually that vendor map that I showed earlier on where each individual device is mapped out and which vendor that is, it's really helpful to have one of our specialists come in, one of our account managers come in and map that out with you. And then we'll make a, let's say, help you prioritize which data, which platforms you want to integrate first and the difficulty of integrating that platform. Excellent. I appreciate that. That actually gives me a lot of insight into the lift that will be required. Because as you said, it'd be nice if everybody was on Philips, everything in your world, but the truth is, is that's not a reality. And so that lift, it sounds like, is not unmanageable. It's not unmanageable, and it's actually relatively quick to evaluate that. So if vendors are already sending discrete data to the EMR, that is a significantly lighter lift. If vendors have absolutely no connection and they're very isolated in their own world with no orders inbound and those sorts of things, then it is, the lift is very heavy to get that good data in place. That's why, and mentioning, partnering with a vendor to do this, we need to look at the data flow and how to organize things from the EMR. So look at interfaces that exist today, like does the system, does the device have an orders interface coming in? Those things help us align patient data more quickly. I'm not saying it's impossible to do it otherwise, but yeah, it's good to have just a quick evaluation and look at your systems to see what your roadmap would be. Got it. Thank you. Thank you, that's helpful. We have one question that just came in and it's, can you integrate data from clinical systems and financial data? So that's, if you want to connect to financial systems, that is an integration that we would need to work with you on. The thing with this platform is, is it's very, very flexible. So if you're integrating, you can integrate data from nearly any system. We just need to work with you to make that connection. We can do also direct database connections, those sorts of things. So depending on which financial system you have, how we can get information from it, let's say if we can connect directly to it with an ODBC connection, those types of things, then we can actually work relatively quickly with you to get that into the dashboard. Yeah, actually your final line feeds into the next question that was asked, which is what timeframe are we looking at from the time of approval to being up and running? Yeah, so the basic set of dashboards is canned. And I think that the beautiful thing about the way that we've designed this product and really want to emphasize it again, is that our history really focusing on the patient and Philips helps us understand workflow very, very well. And we have architected the behind the scenes databases in this environment to be very, very tuned to clinical workflow, clinical operations and scientific. That's why I broke them out that way. So the up and running on let's say an Echo and ECG or Cath Lab dashboard that is a Philips system is very quick. The dashboards typically begin showing really good information right at go live, which is quite soon. The platform itself is relatively light in your IT environment. So it really does depend on that vendor map before. Some vendors will take longer, some shorter. If you're using, for example, Philips and Telespace ECG as your information, as your ECG management system, you can be up very quickly with the dashboards. Thank you. I've got a question and a clarification that came in right behind it. And the first question was, what kind of turnaround time metrics are available for Philips MCOT monitoring? And the follow-on to that was from the time that the monitors received to upload. So what does that look like? Monitors received, upload, and then you get that turned back to you with MCOT. I'm assuming that's actually going to be closer to near real time than monitor received it. Could you address that? Yeah, that's kind of an interesting question because I want to make sure that we're talking about the dashboard side of it rather than the actual physical reply from the physicians. So the turnaround times in that particular space are order to patient reconciliation. So patient device match and from patient device match to when the physician has answered a report. So if you have an MCOT, for example, and you get an emergence report on top of that, that emergent report is shown in the system, then we know when the urgent reports have been sent and also urgent reports viewed by the physician. Okay. And then the whole system, of course, yeah. Yes, if you'd like to have any clarification to that, feel free to chime in with another question on that and we will address accordingly if we didn't quite nail that one. I've got another one here, John, that's come through about support and it's what kind of ongoing support is provided for the Insights Dashboard? If we have EMR and other vendor upgrades, will this require continual tweaking and if so, is this covered under regular support contracts? So what is this gonna take in terms of, as the organizations change, what does ECG Insights Dashboard also change and is that a normal part of your process or is that more one-offs? That is, it is a part of our contract. So as a vendor is upgraded, there can be a, so if they fundamentally change their dashboard, I mean, I'm sorry, their database, yes, the dashboard will change. That, just so you know, that doesn't typically happen because typically vendors like to keep their databases somewhat stable because it helps them with upgrading, those sorts of things. If it's an HL7 interface, there's little to no change in that interface and if it is updated, that's covered under the support contract. What that looks like is an annual number of professional service hours that are assigned to your account. So depending on the number of system integrations that you have, the more service and support is provided. If it's a Philips application, then that's covered without cost. Okay, and so let me ask a question that wasn't asked, but it extends it and that is, if I have a vendor for CID management and that goes into ECG Insights or if I have a vendor for my wearable arrhythmia monitors, as I switch those up, sounds like if I go to Philips, that would be included. If maybe I was going to somebody else that wasn't Philips, I'd love to follow my service hours, but my question is about the data. And so as I change those vendors, do I lose any of my historical data, ability to trend our performance, et cetera? Do we have to start over or do I still, even though I've changed feeds, is it locked somehow and I can continue to build on that dataset? Yeah, actually that's the beauty of the way that Insights is constructed and that is that one data model, so what the dashboard is connecting to, to actually give you those views of the data is vendor neutral, so to speak. So as you change vendors, let's say you have multiple vendors across your organization for MCOT devices. If we look at those things, they'll all come in as the count of MCOT. So it won't be that one vendor has one dashboard, another vendor has another dashboard, all vendors are consolidated into one single view. And that's really kind of the beauty of how this has been architected. Got it. So volume goes down with one vendor and up with another, or you do a complete switch over, at least you've got steady data streams that are therefore not modifying your volumes, your true volumes. That's right. So if you're at a very high level, you're looking at just the total number of studies for that study type. You drill into that, you'll start to see the vendor breakout. You drill into that more and you'll be able to see exactly how many studies and which patients were done by that vendor. Excellent. And I just, again, everyone seems to have found the Q&A button, but I've got one more to read here. So if you've got some questions that are unanswered, please now be a great time to start entering them in. What I've got here for you, John, is can you elaborate on your point regarding ordering e-patch holters for patients waiting in the ED? So not from the physician's office, but ordering from the ED patches and holters. If you want to elaborate on your point there, that would be nice. Yeah, actually, this is a great conversation for our actual team that manages those devices. They're called the Philips CCG Solution Specialists and they actually have a program for the ED that is purpose-built for this use case. It's exactly why we're saying that as a complete solution from device information system and greater, we can help you attain your strategic initiatives. So if you want to put an ED program in place across e-patch and MCOT, this dashboard is built to help you see if you will benefit from that. And once you have put that in place, if it's being strategically successful for you. So certainly there's a large program behind that particular initiative. I really recommend you reaching out to your Philips CCG Solutions account manager. Fall out of the realm of ECG insights. Fall into ECG solution traps. That's what happens is that this becomes a conversation and that's why it's so important that when you see something happening in your data, you see an anomaly, we're here to help you actually work through how to solve that problem. And that's what the Philips product lines are for, to actually improve clinical workflow. Excellent. I appreciate that. I think that for us, if anybody has any additional questions, now would be the time to type quickly. I think you've answered a lot for us. And again, we all are aware that Philips has a very wide range of solutions that fit together. And for me, what was a great message about this is that you'll meet people where they're at, whatever vendors are using, whatever their volumes look like with vendors, it doesn't matter. However, they wanna integrate with those data sets. The point is, can we take the data that we have? Can we manage our departments and our divisions more effectively by using it? Can we create better outcomes? Can we save cost? And can we improve employee engagement even in some instances? Can we do all of that by bringing that together under one unified data analytics piece? And that's what you've given us today. So I certainly appreciate the time. I don't see any additional questions coming in right now, John. So I'll leave it to you for last final thoughts or comments, and then we can close out. Yeah, thank you. I mean, you do have my email right on the screen here. So if you have questions, anything further you'd like to hear about it, certainly contact me and I can work with our team to get answers for you and to work with you. But also we just feel very blessed at Philips to be able to work with the leaders that are on this call. I'm sure all of you know your Philips reps, your Philips team, your Philips architects that you work with. And thank you very much for allowing us to give you this presentation and work with you in this space. Thanks, John. And thanks everybody for attending. This will be the end of our webinar for today. And we look forward to seeing you on future webinars. Thank you.

data-driven decision-making

KPI-based strategic management

resource allocation

Philips ECG Insights

data visualization

strategic planning

team involvement

data analytics tools