Digital Transformation in MedTech Part 2 (S2:E58)
April 27, 2023
Today, we’re joined by Dr. Richard Kuntz, a leader in medical technology and another newly appointed member of the Identiv Board of Directors. Rick discusses the transformational power of IoT in healthcare, predicting the role that sensors and big data management will play in the future of MedTech.
You're listening to Humans in Tech. Our podcast explores today's most transformative technology and the trends of tomorrow, bringing together the brightest minds in and outside of our industry. We unpack what's new in physical access, identity verification, cybersecurity, and IoT ecosystems. We reach beyond the physical world, discuss our digital transformation as a species, and dive into the emerging digital experience. Join us on our journey as we discover just how connected the future will be and how we will fit into that picture.
Thank you for tuning in. Today we're joined by Dr. Richard Kuntz, newly appointed member of the Identiv board of directors. Rick brings a significant amount of IoT digital transformation vision and growth strategy expertise to Identiv's board with his outstanding leadership in the medical industry. Thank you so much for taking the time to join us today.
Dr. Richard Kuntz (01:02):
Thank you, Leigh.
First, I'd like to mention that you have such an impressive resume. Perhaps start with just telling us a little bit about your background, your area of expertise within the industry.
Dr. Richard Kuntz (01:14):
Yeah, sure. I'm a cardiologist and I did my training in cardiology in Boston at the Harvard hospitals. That's a long program, because that also involved a subspecialty of interventional cardiology. That was my clinical training. Then during my fellowship at Harvard, I was interested in clinical research, more specifically into statistics, so I got a degree in biostatistics at the Harvard School of Public Health, a master's degree. At the time that I had finished my fellowship and started on faculty initially at the Beth Israel Hospital, then over at the Brigham and Women's Hospital, the interventional cardiology programs were taking off and the FDA was increasing the requirements for approval, so medical devices like those used in cardiology could easily be approved by a small single-arm registry. Around 1991, '92, the FDA required those devices to actually stand up to a randomized controlled clinical trial. Being a freshly-admitted statistician and cardiologist, I was called on by a lot of companies to help design their studies.
Oh, I bet.
Dr. Richard Kuntz (02:29):
Yeah. I started an academic CRO called the Harvard Clinical Research Institute, and we basically... I think when I left Harvard in 2005, we had 300 employees, and we ran probably 70% or 80% of the medical device studies in the country over the course of the 1990s and early 2000s. My background is mainly in practicing in clinical cardiology and interventional cardiology, but also in clinical trial methodology.
That's just such an interesting combination, having that medical background and then also wanting to get more expertise in statistics. How did that transition into your work with Medtronic?
Dr. Richard Kuntz (03:12):
Yeah. Part of exposure to medical trial methodology is to demonstrate that you really have to have rigorous studies to demonstrate evidence. You can easily be fooled by studies that don't randomize, or studies that don't use sham procedures of blinding. A lot of my interest was really in making sure that when there was occlusion, the evidence was solid, and that's required for any kind of medical therapy. When I was doing studies for Medtronic at Harvard, the senior leadership there asked me if I'd be interested in joining the company. Interestingly enough, my first role was to run a business. The first business I ran was the neuromodulation business, which is not cardiology, it's neurology.
That was a big business. It was about one to 1.5 billion in revenue, and we had 4,500 employees in that business unit. They took a relatively big risk because I did not have an MBA. I had very minimal business background running the CRO. Essentially, I came on as the president and CEO of the neuromodulation business, Medtronic. I did that for about five years, and it was fun. Learned a lot about devices like deep brain stimulators or spinal cord stimulators, different brain targets. It was just fascinating. And then around 2010, '11, I moved to a more central role, which is probably better for my skillset, and I was the chief medical and scientific officer for the company overall.
I was telling our other new board member, Laura Angelini, who also has a medical device background that so many in my family work in the medical industry. I'm the odd duck who they're like, oh, she does something in technology, but my sister is a neurologist and just talking with her. She started off in research and then moved into medical practice and just always fascinating the workings of the brain and the body. A very interesting topic, so even though I'm not in the medical community, it's still super interesting to me and I can geek out on that all day long.
Dr. Richard Kuntz (05:41):
Well, the neuromodulation space in particular, and that includes things like Parkinson's disease, even emotional problems like depression or anxiety, they are now and probably will be extended to be solved by medical devices, which is surprising to most people. But mainly, it's through controlled electrical simulation of different targets of the brain. It's a very complicated, very sophisticated field. It's very exciting and it's really growing. The medical devices in the brain, you wouldn't think that that's going to be the solution, but it's been very successful, and I think the future's going to be even more impressive.
I completely agree. When I worked at Honeywell, there's a whole facility that Honeywell operates on behalf of the federal government. It's Honeywell employees, and the whole facility is filled with Honeywell people, but it actually belongs to the federal government. While they focus on very specific federal projects, when they do have extra capacity and they get permission, the federal government allows them to use, part of that facility specializes in miniaturization. They have worked on quite a few brain devices to miniaturize a technology so that it can be implanted or used in the body. Again, I just love stuff like that. It's so interesting to me. Can you give us...
Dr. Richard Kuntz (07:04):
A large engineering thrust of medical device companies is miniaturization.
Oh, is it really? I didn't know that.
Dr. Richard Kuntz (07:09):
Yeah, so if you look at the history of a pacemaker, which started out about the size of a softball, and now they're so small, complete, a dual chamber pacemaker can be inserted the catheter and the pacemaker itself is the size of a vitamin pill that's just injected right into the right ventricle. When you think about what that is, that means that they've been able to take the radio, the battery, the electronics, and programming and software and take it from the size of a softball down to the size of a vitamin pill with even more features. Miniaturization, especially electrical circuitry and CMOS chips and everything like that is a large part of medical devices.
Which has to be such a much better outcome for the patient, I would assume.
Dr. Richard Kuntz (07:57):
Yeah. Anytime you do an invasive procedure on a patient, if you can minimize the invasion, the incision you make, the way that you get there, in a lot of cardiology, most of the highways to get into the heart are through the veins and arteries. You just make a tiny little stick in the leg and you can pretty much get anywhere in the body. But it also requires you to have small enough devices that fit in those arteries and veins to be delivered. I would say that if you're looking at the big trends in engineering, it is really trying to make things small.
As you make things smaller, you make them faster, too, because the circuitry doesn't have to go as far. This is something that's continued to explode. And then what's even more interesting is that I also serve on a board called Rockley Photonics, which is a silicon photonics company in Pasadena. They have chips that not only use copper traces for electrons, but fiber optic traces for photons. These are much more efficient chips. There's just a variety of new ways to that engineering and medical devices is going to continue to evolve.
Well, I did many, many, many months ago, because I've been at Identiv now just about two years and learning more and more about the different market segments. I did a lot of research on just the IoT in general and the technology stack of the IoT, and really figuring out where do we fit in in that stack and where we differentiated. Really, Identiv's RFID-enabled IoT solutions are integrated now into about one and a half billion physical things and create that digital identity for every physical object and then deliver that digital transformation across just such a wide variety of industries. When you look at that, so where do we fit in that stack? There's not a lot of agreement from an engineering standpoint on even what is the IoT stack? How many layers are there? But the sounding layer, the perception layer, the data transfer layer is really where we live. That's really where we are experts in putting data in motion and making those connections. Can you give us some personal insight into the rise and demand for more connected and sophisticated healthcare systems within that IoT stack?
Dr. Richard Kuntz (10:26):
Yeah. Well, just from a 30,000-foot level, there are all kinds of very strong secular trends happening in medicine. The biggest trend I would summarize by saying, moving from episodic care to continuous care. The bedrock of medicine with a chronic disease like diabetes or heart failure, is to see a provider once every three months or so. In that 10 or 15 minute encounter, that physician tries to predict what'll happen in the next three months and may adjust the medications and then the patient is on their own and their next interaction might be a problem associated with that chronic disease, an episode that results in them going to the emergency room, maybe an ICU. That's just not a very efficient way of taking care of patients is to push them out the door, say, hopefully you're going to do all right for the next three months, and I'll see you for my next visit.
That's the classic episodic care. It's not very efficient. Patients get in the hospital for three or four days or longer if they have exacerbation of their disease. A better way to do it is to have a much more continuous monitoring of their disease on a regular basis that can be interacted with either providers or extended providers or AI [inaudible 00:11:45] systems. That trend is exploding right now. Part of that trend is the advent of a variety of really interesting sensing devices that have been developed in the last few years and are continuously being developed. And then the second thing is going to be the connectivity, as you mentioned, between this data, leveraging a variety of different data highways into cloud, everything from the local radios to an iPhone, faster wireless systems like 5G, and then of course, machine learning and AI of that data in the cloud. That's exploding, but it's going to cause a massive transformation in medicine. Where Identiv can fit in to that secular trend, which is going to be positive for Identiv is going to be super exciting because that horse has left the barn already.
Right. The medical and pharmaceutical industry is recognized as, like you said, one of the largest global marketing opportunities and go-to-market opportunities for Identiv IoT products and services. With your experience in managing disciplined global operations for very large, multinational healthcare organizations and integrating leading edge tech into process, how do you envision our growth plans in this important market?
Dr. Richard Kuntz (13:03):
Well, the first is going to be to identify specific use conditions that will be improved for that. In medicine, that's not that hard to do. You basically pick a disease or a specific aspect of a disease where you can identify a problem. Diabetics poorly controlled and have episodes of diabetic ketoacidosis, which can be almost fatal. How can we make that better? That might be that we look at the entire episode [inaudible 00:13:35] and understand where it can data flow and how can we basically add Identiv-specific value to that chain? Almost all of it starts with identifying clear-cut problems in the existing system, understanding the use cases for those problems, and then getting your engineers and creative people to say, we can improve that use condition easily by adding this value to, say, the wireless stream or the way the data is handled.
Well, I thought your comment earlier about how seeing a patient for maybe 15 or 20 minutes at best every three months, and then they have some sort of episode rather than a continuous monitoring of their condition, I would think that in your line of work in cardiology, there's probably a lot of events that maybe they don't even know they're having.
Dr. Richard Kuntz (14:33):
Right. Well, and the classic example that is atrial fibrillation, which is now becoming much more curable than it was in the past because of the advances in mapping technology and ablation that are pretty common now. Part of it is understanding whether you have the problem or not. There have been a variety of implantable sensors that have radios that can communicate this, store data to the cloud, and then that can be available for providers to use. At Medtronic, we have a very large system like that that we manage, and then we distribute that information to physicians and they can see in real time what's happening to their patients and get summary data as well.
Does it allow for predictable insights?
Dr. Richard Kuntz (15:19):
It does, and a lot of even implantable devices are leveraging, using the familiar term called edge computing, which is where ML is done in the can, in the box itself, rather than having to go to cloud for analysis. Many of our pacemakers, for example, that also detect terrible rhythms like atrial fibrillation or even worse, ventricular fibrillation, which can kill you, they can customize to the patient, how to, say, do something called overdrive pacing when this device sees a set of rhythms that has been trained in that patient to be associated with a bad outcome.
Oh, so specific and unique to that patient?
Dr. Richard Kuntz (16:05):
Yes. Specific and unique. Well, there's two things. There's, there's going to be the cluster of all patients that give you great insight because of the samples size, and they can fine tune that further with the patient itself by using edge computing in the device within the patient. That's happening already and a variety of changeable algorithms are occurring and that's happening in not only cardiology. It's happening clearly, with our diabetes where we have a closed loop systems for continues glucose monitoring and administration of insulin to keep someone exactly in the 80 to 120 zone. And then we do also that in deep brain stimulation for Parkinson's. We have closed loop systems that monitor brain signals and alter the output based on outcomes that it can measure and trains it specifically for that patient.
How do you stay super hyper-connected? We talk about medical devices and MedTech as if it's like this really finite little ecosystem, but the truth is that within that, there's so many specializations and subcategories of topics. How do you stay on top of what the latest and greatest is in trends in MedTech?
Dr. Richard Kuntz (17:20):
Well, it all depends on what the role is. In my role as chief medical and scientific officer, I'm responsible for making sure that I'm on top of disease conditions that might be benefited from this. We have a lot of people that do that, but specifically with the physician input as opposed to an engineering input. It's easy because if you're curious, it's fun.
Right, yeah. I could see that.
Dr. Richard Kuntz (17:45):
Yeah. I'm fascinated by the physiology and pathophysiology, and so are all my colleagues that I worked with when I was at Medtronic. They're constantly interfacing with their physician customers. They attend many of the scientific meetings where they're brought up. Medtronic is also heavily involved in the publication side of things. We work with doctors on publications and we actually have our own publications and or support independent publications. A lot of the devices we have, we want to have completely independent, so we want them to write the papers, not us, but at the same time, we support them on those issues, too. Staying abreast of the literature, staying abreast of current water cooler talk with physicians, what's bugging them the most right now is really the critical inputs that you have to have that gives you the ideas. And then of course, to have the interface with electrical engineers, mechanical engineers, that can solve is ultimately the problem.
The common model of medical device in how someone solves something, which is more mythical maybe than [inaudible 00:18:57], but was at one point an important thing is that a physician comes to an engineer with a problem and the engineer solves it. In the case of Medtronic, that's how the company started in the 1950s. In Minnesota, there was a famous heart surgeon, Walter Lillehei, who did world class pediatric heart surgery, and people from all over the world were flying to Minneapolis to have this surgeon operate on them. When these kids got operated on, they had to put in temporary pacemakers because the impact of the surgery on the hearts stunned their pacemaker system, so they had to be electrically stimulated for a couple days. Back in the fifties, late forties, all the pacemakers were these big vacuum tube boxes that got plugged into the wall.
They were taking AC and transferring into DC energy, and literally, he has pictures of them. They're the size of huge carts that they would wheel around these little kids. One evening in December, there was a storm and the electrical support or power was off for a couple hours and a baby died who was dependent on an AC-powered pacemaker. Walter Lillehei talked to the founder of our company, a guy named Earl Bachan, who at that time was an electrical engineer repair person in the hospital and took care of those vacuum tube systems and asked him, this is never going to happen again. I need to have a battery-powered pacemaker. The story from this is mythical, but the story is that Earl went to his last copy of Popular Electronics, went to the back pages, and bought a circuit diagram for a metronome.
Oh, yeah. Like a piano.
Dr. Richard Kuntz (20:48):
Yeah. At that time, Motorola just came out with the first transistors, and so it was a transistor-based one. This was 1951 or '52 or something like that. He basically developed this metronome in a box he built himself with wires that came out that could be used for pacing, and he worked with them to find out the right power requirements. That was used immediately after for a couple years and every one of those patients got operated on, and that's how the company started.
I didn't know that. That's such an interesting story.
Dr. Richard Kuntz (21:23):
It is a great story. But it goes with one of the rules of how you solve a problem is you have to have the unmet need identified, and that's going to be best done by the clinician in medicine who sees this, who every day sees a problem in their practice or they get the best insight because they deal with it every day. And then to be able to translate into a problem that can be understood by an engineer who then can try to solve the problem. Whether that's in spine work where you're looking at pedicle screws and rods, or very delicate electrical work, like deep brain simulators, that's the common pattern of identification of a problem and invention and solution.
Well, I would think it's such an amazing field to work in if you like to solve puzzles and problems.
Dr. Richard Kuntz (22:13):
It is. I think we have, last count, Medtronic had 105 to 110,000 employees, and I think of about 30,000 were engineers.
Oh, wow. Wow, that's huge.
Dr. Richard Kuntz (22:24):
Yeah, and they're all pretty smart.
Oh, I'm sure. I'm sure.
Dr. Richard Kuntz (22:28):
They're used to understanding where to take the ball when a problem has been identified and to work back with the visions and with their prototypes and everything else. It's exciting.
Yeah. Well, you've had just such an amazing career. What do you see in the future overall for MedTech transforming healthcare?
Dr. Richard Kuntz (22:46):
I think it's going to be a large movement in sensors. I think that's something that's going to explode in MedTech to some degree. I'm seeing explosions right now in things like there are companies now making watches that look like they can measure blood pressure, look like they can measure glucose without using a needle, can measure a variety of different parameters that we never thought you could measure before. These are going to be wristwatches. Again, going to continuous medicine is going to be a way that we can start to look at how do we solve a problem that needs continuous input? That's going to be a big part of MedTech.
I don't think it's going to be a matter of saying, here's a $5,000 pacemaker, just buy it and good luck. It's going to be, we're going to sell you a pacemaker and we're going to guarantee you that this patient is going to be fine for the next five years, and we're going to sell you the entire system, including the sensor, the measurement, the connection with your provider as a package, because we are more interested in the outcome for the patient than selling you just a box.
I think that's going to be a big trend in medicine. I think the other big trend in medical devices is going to be management of the data. What I mean by that is the use of the word data provenance. What that is is the sticky rules and rights and consents required to be able to share data. It's very complicated. It hasn't been worked out yet, but as we see better computing power and more applications of artificial intelligence and machine learning, it's going to require a lot of data from patients. We're still working out privacy issues and the rights and stuff like that. It's a relatively hairy problem, but it will be solved. But it's just another trend that we have to pay attention to.
Well, it's not only a hairy problem, but I don't know if you need this about me, but I started my career in the US Senate. I've written and drafted legislation and I've watched people give testimony, and I'm at the point where I just want to throw things at the TV when I watch our governing bodies try to legislate some of these things and listen to expert testimony, because no one can be an expert at everything, and you have to make very significant decisions from a legislative standpoint when you're in those roles. Not only is it, there's a lot of complexity, but there's also just a level of understanding that really isn't there. Not just in federal government, but also in state and local. We also see that with some of the physical access control products that are coming out with facial recognition and biometrics and that sort of thing, that there's just not enough deep subject matter expertise guiding those decisions today. That continues to make it a challenge as well, right?
Dr. Richard Kuntz (25:46):
It is. The two issues about the data sharing component is that data sharing is going to be required for us to be able to get the amount of data where you can apply learning, machine learning and AI, and that's going to be good, but it also is going to require us to understand who is going to be managing that data? Who's curating that data? Is it going to be safe? This is something that's just not well worked out. The other is what level of consent do you need from patient to leverage their data? When you go to 23 and Me to turn in your data, they can sell that data later. People are finding out, well, this company just made money on my DNA. Why am I not being monetized on that? These are sticky issues.
It's an extension of the HIPAA issue about sharing data, but I think it's going to be very active going forward because of the massive ease of use of large amounts of data. We're seeing that already in the liquid biopsy business. These are the puppies that are looking for early signs of cancer in your blood, and these companies are really taken off. But the key is they're getting your entire DNA system set up when you're turning your blood in. The question is, well, if that company is monetizing an ability to predict cancer, and they're using my DNA, I'm not getting money for that. That's a big discussion that's going on right now. I think the data provenance issues are going to be just as complex, but also it will move forward as the technology on data handling.
The thing that I picked up from quite a few of your examples is really being able to better focus on delivering positive outcomes for patients.
Dr. Richard Kuntz (27:43):
Correct. That's a great way to put it. You're not saying, here's a disease. You need this box put into you. It's a disease. We're going to give you this outcome, which is good for you. That's widening the responsibility and accountability of the company and there are many terms for that. One term is called value-based healthcare, where you look at the patient and understand patient is the one with a disease, patient is the one you're focused on. You need to make that patient better, not just sell them a device and then wipe your hands. You're selling them a solution, so that focus on outcomes. It's always been difficult in the past because medical records were always so difficult to work with. They were intended to be aggregated. Very difficult to follow patients because if they go to a big tertiary hospital, we don't know where they're going to next.
Measuring outcomes, unless you had a structured clinical trial, which are very expensive, you really can't measure outcomes. But now, with a much better ease of use of data and data flows and systems like 5G and radio systems, we can start to get a variety of followup through the internet. If you look at companies like Verily, which is one of the Google companies, their whole focus is understanding how to leverage the internet to follow patients and follow people longitudinally. I just think there's going to be a lot more tools to be able to make some very interesting applications. I think Identiv is going to be right in the center of this, because if you look at, like you said, the movement of data and also of potential devices and drugs, there's going to be a lot better highways to attach that information on once we get through some of the technicalities, but also some of the policy issues like the provenance.
Well, thank you so much for joining us today. I know you're one of our newest board members, but I found this conversation really fascinating discussing just the transformational power of technology on the healthcare industry, and I think you brought up some really important topics and points that we're probably going to want to explore in additional, future podcasts.
Dr. Richard Kuntz (30:04):
Great. Well, thanks so much, Leigh. It was very fun.
Of course. If you enjoyed this podcast, please like and subscribe for me. We drop a new episode every Thursday.
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