Speaking of Service

Driving Health Outcomes with Connected Data

September 28, 2022 PTC Season 2 Episode 7
Speaking of Service
Driving Health Outcomes with Connected Data
Show Notes Transcript

Sysmex Leverages the Internet of Medical Things (IoMT) to disrupt the blood testing market – Check out how!

Executing on a smart connected products strategy in the medical device space requires vision, planning and operational discipline.  In this episode, Andy Hay, President & CEO of Sysmex America discusses their path to digital transformation and how they kept a focus on driving health outcomes. 

Announcer:

Welcome to speaking of service, the podcast that uncovers practical ways to grow service revenue control costs and improve customer satisfaction. If you're looking to innovate, gain a competitive edge, or just learn about the latest service trends, you've come to the right place. In today's episode, Chris McDonald, head of AI and analytics sits down with Andy hay, president and CEO, Cmax America, Inc. To discuss their path to digital transformation. And how Cmax kept a focus on driving health

Chris MacDonald:

outcomes. Hi, and welcome to the show today. We're gonna talk about the importance of analytics as a central part of a smart, connected product strategy. And in particular medical devices presents a fascinating case for a connected strategy. Of course, elements like predictive maintenance are critical to enabling proactive. And the notion of understanding how a product is used in service can feed incredible insights back into engineering. But with medical devices, the device itself is part of enabling patient outcomes. So there's a criticality and an opportunity as well as risks that come into the value and importance of that data into transforming patient outcomes, business outcomes, and population health outcomes. And today I have Andy. The president and CEO of CSM America with us CSM max has been at the forefront of this opportunity, um, in a connected device strategy. And PTCs had the privilege of partnering with CSM. From the very beginning. I personally have had the opportunity to work closely with Andy on some incredible innovative projects at Sysmax. So it is my pleasure to welcome Andy, my friend to the show. Andy, can you give us a little background about yourself and CSM?

Andy Hay:

Thanks very much, Chris, that wonderful introduction. My name's Andy hay, I'm president and CEO of offices makes America, uh, we're a diagnostics company, as Chris mentioned. What that means is that we, uh, predominantly make blood testing equipment and all of the associated reagents, software and services that are required to, uh, provide that level of, uh, equipment for hospitals and commercial reference labs all around the America. Uh, it's a Japanese company. We're a wholly own subsidiary of Sysmax corporation of Japan. Uh, I've been with the organization 32 years. And prior to that, I was a medical technologist working in the hospital lab, myself, and many of the, uh, organization come from that background. So there's a great deal of, of, uh, understanding and, and, uh, empathy with the roles, uh, of our customers. Um, as you mentioned, Chris, uh, Look to smart connected systems as a core part of our technology. We've, uh, we've really been investing heavily over, uh, more than a decade now to make sure that we can use the, uh, the latest technology to improve the uptime of the equipment and reduce the service, uh, needs, uh, to make sure that the patients are best served and our customers are able to maintain their service levels.

Chris MacDonald:

Thank you, Andy. So at first glance, the medical device space can seem fraught with risk. I, I would love to hear your perspective on, on what some of those risks are, because they certainly are, you know, real in terms of, of liability and the fact that you're dealing with patient care, but also how Sysmex, um, had the conviction to, to begin on that journey of a smart, connected strategy and overcome some of those risks.

Andy Hay:

Yeah, I think. Risk risk is an interesting word because, uh, risk of often leads to the opportunity. Uh, but the risks really fall into two areas. Uh, firstly. The risk of the equipment being available or not being available is extremely high. Um, there's a simple blood test known as a CBC, a complete blood count. It's the most commonly ordered diagnostic procedure in the world. Uh, but without it. Hospital really shouldn't be having patients coming into that emergency room. They shouldn't be performing operations, delivering babies, running an ICU. It's such a core and important part of the, uh, the healthcare of that patient that. The inability of a hospital to produce that test really negates their ability to provide any level of, of acute patient care. So the first risk is to make sure that the instrument is functioning perfectly and available 24 7. Uh, and most hospitals would have two of those devices to make sure that they've got some built in, uh, redundancy. But nevertheless, that, that there's a huge amount of risk around reliability, uptime guarantees, and then serviceability in the event of a, of an issue or a problem. Um, the other risk, of course, and it's especially true when we start to connect devices. Is, uh, HIPAA. It is patient confidentiality. We are able to access and able to see, um, sometimes whether we like it or not levels of confidential information that really need to main be maintained, completely secure to the very highest standards. Nobody wants their healthcare records broadcast on the internet. And SMEC certainly don't want to be part of any, uh, cyber security breach. So we take the, uh, the security of the connection. Um, which is become an essential part of our ability to deliver that high availability. The high up time guarantees very, very seriously indeed, to make sure that we can maintain the highest possible levels of service and service ability with the minimum possible risk to, to security.

Chris MacDonald:

It's interesting. You mentioned that. I think. It it's very obvious to you that your devices or your connected devices essentially have, um, data about the device, but that device carries data about a patient because of the very nature of what it's doing. Can you give us a little insight on how you manage those two distinct, yet connected data streams at Sysmax or how you operationally handled that?

Andy Hay:

Yeah. Yeah. So, so the, uh, the systems have been designed with that in mind. Uh, and firstly, let me say that the amount of patient data that we see is actually pretty limited. Uh, it is, there's some data that we need to know the age, the gender, um, but we don't know medical histories. We don't have a full demographic on the patient. There's no credit cards or social security numbers involved. So we're quite fortunate that we can mitigate that risk by limiting the amount of data that we see. But then that data that's patient related, we put it in behind a firewall on the device, um, that really protects that part of the device from the essential ingredients that we need to see and access in order to perform the service functions and some of the predictive analytics and the AI engine based, uh, service tools that we've developed. Uh, so we really try to put this, this church and state separation between the highly sensitive. Uh, but limited information. And the rich environment of all of the, uh, the numerical information, uh, the results, uh, which in sell themselves can speak volumes about the health of the equipment, uh, as well as all of the, uh, the machine driven data, temperatures, precious cycle counts, all of the things that we can feed into our analytical tools to help use for the predictive, uh, maintenance and, and, and failure analysis. So, so we really try to start with that designed in, uh, separat.

Chris MacDonald:

And I certainly want to get to some of the, the innovative stuff that you and I, um, you know, could talk about for hours, but I think it's important for our listeners to understand how your connected strategy, how your understanding of the importance of data within Sysmax, um, and leveraging analytics to, to unlock value how that led to optimization, um, or innovation in your service organization in practical.

Andy Hay:

Yeah. Good. Great question. So to do that, really, we should go back to what was traditional in the diagnostics market and diagnostics is not a new business. Uh, Sysmax has been in business over 50 years. The diagnostics industry has been evolving over that time, but traditionally it's what you could call a, a break fix business. The instrument fails. The end user operator in the, in the hospital, dabbles with the stuff they've been trained with. If that doesn't work, they call a hotline. A hotline says, have you tried? This is it plugged in? Is, is the green light on a few simple triaging questions? And if that fails to, uh, resolve the problem, then we dispatch and send an engineer. And the engineer arrives on site pulls up the hood plugs in his instruments. Checks a few things looks for some leaks, cuz there's fluidic and pneumatic in there as well. And then eventually, hopefully diagnosises the problem pulls the spare part or the tool out of his bag and fixes it. That's been the way that this business has been run. A and to be honest in, in other companies, uh, still today is still running. Uh, for decades. You wait till it breaks and then you fix it and levels of reliability are. Confused with levels of service response, how good is my engineer and how fast is my engineer to get there? Uh, and that tradition in the industry, uh, was something that CSEC set out to, to, to change, uh, a paradigm change. By first of all, uh, assessing that reliability or understanding that reliability starts with the design of the equip. Don't build it cheap. Don't cook corners, use high quality components put in sensors where sensor information might help predict failure, really build instruments with reliability and high availability in mind. Then connect them through a very secure, smart connection. Thanks to our partnership with PTC for over two decades, we've been able to do that at a level that the hospital's cybersecurity, uh, offices feel comfortable with and then pull that data out. So, and put it through advanced analytics so that if we do have a failure, We're able to look at, uh, a wealth of data to help assess the ability to fix by telephone or troubleshoot or indeed, uh, what the likely, uh, cause is what tools the engineer will need, what training delivering just in time knowledge, what spare parts they might need, and then ultimately move to the next level, which we've been able to do over the last couple of years of starting to predict failure. And using evidence based maintenance to change components or make adjustments ahead of them failing. And when we combine that with some advanced analytics on our quality control, which is an essential part of diagnostics, we're able to see failures and see problems well ahead of them manifesting themselves as instrument, downtime, and react accordingly. And. Introduce maintenance levels that are appropriate to the age and to the, uh, cycles, uh, and number of samples that those devices analyze because some hospital. Maybe got 50 beds doing 10 samples a day mm-hmm and we've got other labs doing tens of thousands of samples a day. Why would you do the same maintenance on both? So we're able to use the connected systems to help predict the maintenance get ahead of the curve on failures, reduce the downtime, perform, uh, changes of components I in, uh, quiet times of the day O of the week so that there's not, we're not interrupting patient care. In doing so also frankly, reduce some of our service costs. Mm-hmm because in the middle of the night, if an instrument is truly down and not operable, and we're sending a service engineer, the cost of that visit is, is quite high. You might imagine. But if we can do that at a time, that's convenient to the customer and a time that's convenient to CMEX and when the instrument's not, uh, running at full capacity, we can do. It's a much lower cost base to everybody in the chain, uh, and without any risk to patient care. So, so we, we, we really look to the connection and the rich data mining that goes through the connection as, as an essential part of changing the way that we perform service and changing the way the industry thinks of reliability.

Chris MacDonald:

And you touched upon how, um, this strategy has already pervaded into engineering, for instance, right? It sounds like you are leveraging, uh, these data and insights that help you guess reduce cost and service. But I think even more importantly, meet the customer, um, with a service strategy that is all about them and the patient when they're operational, making sure it's operational at the right time, providing service at a time. That makes sense for the, the clinicians or the hospital or the healthcare setting that you're in. In terms of pervading into patient outcomes. And I loved that you said evidence based maintenance, right? Uh, it's another way of, of, of saying, you know, uh, predictive maintenance, but it, but it means so much more because of something you and I both share a passion for, which is really evidence based medicine. Right. And, and how a, um, a company like yourself can. Have a competitive advantage in terms of a focus on patient outcomes. Can you tell me how this strategy? Um, not only has pervaded into engineering, but has enabled CMX to be part of really transforming patient outcome. . Andy Hay: Yeah. Uh, uh, um, and let me say at the outset that we are in a heavily regulated industry, as you might imagine, mm-hmm, , uh, FDA, uh, governs and, and, and regulates everything that we do. Every test that we provide has to be, uh, cleared through a, an FDA process, um, which. Of course good and bad. It gives us a thoroughness and a quality level. That's second to none, uh, anywhere in the world. But it also means that we have to go through a fairly extensive process. But in terms of evidence based outcomes of patients, uh, where the industry is moving towards, it's a bit like predictive analytics. Can we get to a situation where we can predict. Patient outcomes, adverse events ahead of time. And CMEX is part of a, a growing medical, uh, opportunity of looking at population health screening, um, at the ability to, uh, risk stratify, certain groups of patients. So that they can be, uh, addressed more intensively or proactively. Uh, and the more that we can take that healthcare upstream from the acute event of a, a cardiac arrest or, or some other, uh, life changing, uh, catastrophic event, the more, the more that we can help maintain patient quality of life, or we contribute to that, that maintenance of patient quality of life. And also of course, in doing so reduce overall healthcare costs. You know, cardiac arrests and acute injuries, uh, and acute trauma. Those events are very expensive comorbidities, such as anemia, um, and chronic obstructive airways disease and diabetes. Those add to huge amounts of healthcare costs and make other things far more acute. Can we. In combination with the medical industry, supporting them through innovative parameters, uh, get further upstream in helping identify the patients that need that extra level of care. And the answer is yes, and, and there's a wealth of data that comes in a, in looking at patient populations as well as that one individual result on that one patient. So when a doctor. Orders a, a sample to be taken a blood drawn on one patient. You're getting one snapshot in time, but of course over time through numerous visits through our annual, uh, fitness and, and through, uh, maybe, uh, ongoing monitoring of, of drugs or disease that data builds up longitudinally. And of course that one patient's longitudinal record is part of a sea of millions or hundreds of millions of other records. Now that takes us into a world of, of huge data. Millions and millions of, of patient sample results. Of course, all anonymous, no patient records, no identification, but now we start to have, um, a, a very valuable commodity that we're working with with some, uh, healthcare partners to turn into, uh, real, meaningful, actionable information. Uh, and I can't say too much about some of those projects, um, but the, the concept. Using, uh, AI engines to perform advanced data analytics on populations, to be able to stratify that risk and identify the, the, uh, cohort that requires further attention or preventative, uh, healthcare. Is is a big part of our business and CMEX is very, very committed. And, and to be honest, you can't do it. If you're dealing with one patient at a time, one record at a time, you've got to be able to take the data out, put it into big data lakes, working with, with healthcare partners, uh, to do that advanced analytics. Yeah. And, and of course you, you know, you can't talk about the details cuz, and, and rightfully so, but I think the fact that CSM has leaned into this complexity because of, of the value is certainly something that I admire. Um, and I greatly appreciate you just sharing conceptually that CSM is thinking about these critical issues that, that do have the power over time to transform the way we think. Um, you know, blood analysis, urine analysis and patient outcomes and understanding how we can bring more and more data from not just across the single patients, but across the patient population to really understand and predict certain types of disease in their effects. As soon as we can. Right. Um, I can't help but ask, uh, on, on these podcasts when I have a, a president and, and CEO of, of CEX America, like I do today. Um, and someone I know, well, you've always leaned into complexity where you see fit without getting bogged down by too many details. But I think that's a skill. That a lot of our customers and listeners, um, as they are leaning into this journey are, are just starting this journey. What advice can you give to other executives on how to support these initiatives, to how to drive the strategy, how to create momentum and inertia.

Andy Hay:

Well, fortunately, um, I, I come from a line of, of previous CEOs who had that kind of vision as well. So, and they were all medical technologists by, at the original training. So I think my, my advice for CEOs and other people looking to make this kind of start is, is you you've. I think you've gotta think big. You've gotta dream big. Um, This is going to take time. It's going to take investment. It's going to take effort and energy, but if you start to, to bog it down by what you can do now, or, and my CFO probably wouldn't agree, uh, initially at least, uh, or by its ROI, it's self evidence ROI, then you'll think. And I think we have to think big and long term. Now I'm very fortunate. I work for a company who is willing to place big bets, long term bets, and looks at the long term direction, a long term strategy. We partner with some incredibly powerful health systems, visionary individuals and visionary health systems that are looking overall at. Patient outcomes and reduction in healthcare costs in the bigger picture. And they in turn are in discussions with big payers and, and providers. So, so I think, you know, get into the, get into the right group, think big, um, place, the big bets, make the investments, don't limit your, your vision and your, your, um, your efforts to short term fixes. Uh, and then just trust that this is, this is the right direction, uh, because. Labor is a precious commodity. It's a precious commodity for all of us. Um, it's an increasingly expensive and sometimes difficult to find commodity. So any function that requires high, skilled, or high volumes of labor, such as our service engineers, as an example, or the medical technologists in our customers, uh, locations. it can be improved. It can be automated. It can be, uh, enhanced through smart systems based on really high quality data through the connectivity, secure connectivity. So dream big, think big and place those big bets.

Chris MacDonald:

Fantastic advice, Andy I've. Um, I've learned a lot today. We heard about how Sysmex is really putting the smart and smart, connected product strategy. Um, and how for medical devices, it enables not just a critical proactive service, um, initiative that enables. You to lower costs, but really treat that labor, those critical individuals and that talent as a critical asset, how do I optimize how they're being leveraged? How do I improve the customer experience? How do I bring and create a virtuous cycle with that data back to engineering, to improve product designs, to make the next medical device even more connected, even smarter to learn from usage patterns, to learn from service patterns and critical. Innovate the very way in which medical devices, the parameters that they have, the measurements that they have can transform patient outcomes that can transform the way we handle patient population, help and partnerships, um, with leading institutions. So, Andy, I can't thank you enough for joining us today. It's always a privilege. Thank you very much for being here.

Andy Hay:

My pleasure, Chris. Thank you very much, indeed. For the opportu.

Announcer:

Thanks for listening to the speaking of service podcast brought to you by PTC. If you enjoyed this episode, please subscribe wherever you get your podcasts and leave a rating or review, and be sure to check out other episodes, to hear new perspectives on improving life for aftermarket professionals, service teams and the customers they support. If you have a topic of interest or want to provide feedback, email us at speaking of service, ptc.com or visit us at ptc.com/speaking of.