← Becker’s Healthcare Podcast
Becker’s Healthcare Podcast
Dr. Tom Nguyen, Professor and Chair of Cardiovascular Sciences at FIU and Chief Medical Executive at Baptist Health Heart & Vascular Care
00:21:08
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- [00:02]
A
@ Athenahealth, we know your ambulatory practice wants healthier a healthier business, healthier care teams and healthier patients. But the complexities of modern healthcare tech make it hard for you and your care teams to focus on what matters most. That's where athenahealth can help our AI native all in one solutions reduce administrative burdens, streamline billing and payments, and deliver critical insights when clinicians need it most. That means fewer clicks, more time for patients, and stronger bottom Practicing medicine is complex, but running a practice can be that much simpler. With Athenahealth, see how simpler is healthier at athenahealth.com.
- [00:44]
B
This is Laura Dearda with the Beckers Healthcare Podcast. I'm thrilled today to be joined by Dr. Tom Nguyen, Chief Medical Executive and Director of minimally Invasive Surgery at Baptist Health Heart and Vascular Care, part of Baptist Health South Florida, and professor and Chair of the Department of Cardiovascular Sciences at FIU. Dr. Wynn, it's a pleasure to have you on the PODC.
- [01:04]
C
Thank you for having me.
- [01:05]
B
Absolutely, absolutely. Now, I'm excited for our discussion today because we are going to get into some really cool things that you're doing at the heart vascular care right now, talking about some wearable technology devices, some other things that you're doing that are really interesting when you think about heart disease and providing care to patients. Let's dive right into it. Can you tell us a little bit more about how you're thinking about wearable devices and improving detection of earlier cardiovascular issues?
- [01:35]
C
Yeah, absolutely. Thanks for having me. The problem with current medicine is that when we look at patients, we look at snapshots in time. For example, when you look at a patient's vital sign, it's a snapshot in time. It could be in the morning, in the afternoon, in the evening, but even then that's only three data points. The advantage of having wearables is that you can collect data 24, 7 and capture data and potentially capture changes a little bit faster than looking at two or three data points in one day. The other unique element about wearables is that perhaps we can pick up on certain changes in biometrics that we didn't think we should consider and look at. And it could be a predictor. So I'll give you an example. We look at heart rate a lot, but something we don't look at a lot is the heart rate variability. Or we don't look at resting heart rate because to look at the resting heart rate it takes more data points. We're working with a project in collaboration with MGH Using wearables to predict postoptive complications after cardiothoracic surgery. What's fascinating is that the group has found that there have been changes in one's biometric after thoracic surgery that happens before the patient even realizes it happens. For example, let's say after thoracic surgery you develop a pneumonia and you don't realize it until day 10, but there could be changes in your biometrics that happen at day eight. This is super important because now it allows us to predict when a complication might happen, but more importantly, be able to intervene and address the complications so it doesn't escalate.
- [03:26]
B
That's fascinating to hear. It's really interesting that we have the ability with the technology and the biometrics to see some of those things and be more predictive. Can you tell me a little bit too about how these devices are playing a role in preventing heart related emergencies?
- [03:42]
C
We don't have one directly to prevent heart related emergencies yet. There are some projects that, that we're working on. I can't tell you about. A study at FIU using devices and AI to prevent, to predict whether or not a patient could have epilepsy or could have a seizure, which is pretty fascinating. In patients with epilepsy, be able to predict when a patient would have a seizure. Could be very transformative. Right now we don't have any current commercially available devices out there to predict any heart related complications. But there's certainly a lot of trials and studies out there that are very promising that could potentially in the future predict when someone might have a heart related complication.
- [04:32]
B
Got it. That's helpful to know and really interesting that you look into the future. You can see some of these things playing out and being really meaningful. Now I'm curious, I wanted to ask you a bit about heart monitors too. How accurate are the wearable heart monitors compared to some of the treatments, traditional clinical equipment that you use when you're thinking about patients with heart disease?
- [04:54]
C
It depends on what heart monitor you use. I would say that they are reasonably accurate, but it's probably not as accurate as the medical grade, the hospital grade heart monitors that we have here in the hospital. But it's accurate enough, it's accurate enough to figure out what your heart rate is. It's accurate enough to figure out the changes in your heart rate. It's accurate enough to see whether or not your rhythm is in normal sinus rhythm, or if you have some other funky rhythm, whether it be atrial fibrillation or some other type of rhythm. It's not perfect, but I think it's good enough and it's certainly better than nothing.
- [05:36]
B
That's a great point. And definitely knowing what's coming up and being able to monitor as closely as possible, like you said, how many changes with the heart monitor can make a big differ in patients care and how they're quickly, they're picking up on some of those changes now. In what ways can the continuous heart monitoring reduce the hospital visits in healthcare costs in particular? I know that's a really big goal for a lot of hospitals and systems today is just figure out how they can improve quality but also reduce costs.
- [06:07]
C
No, absolutely. I guess the first thing is that sometimes for us to know that we're sick, it's too late. And by the time you feel like you're sick, things, you know, the cat's already, you know, out of the bag. These devices have the ability again to predict something bad happening before it even reaches your sensorium and have you realize it. From a clinical standpoint, that's obviously good because it allows, it prevents a progression of whatever you might develop. But also from a hospital financial standpoint, it has huge potential and implications to decrease the rate of readmissions to hospitals. You can imagine that we have a huge societal burden of patients being discharged and then being readmitted to the hospital, especially if we can find a way to prevent those readmissions and capturing the patient's illness sooner. I think this would be transformative, huge healthcare costs and being able to prevent readmissions. In fact, it's actually one of our quality metrics, hospital readmission, something that we look at very carefully and we track.
- [07:25]
B
That's helpful to understand that relationship between the two and really being able to leverage the technology for better care as well as to reduce the costs and overall spend. Now I'm curious too. One of the things that we've been hearing more and more about today is cybersecurity and privacy for patient data, especially as more technologies and wearables are in use. So how do you think about that? What's important for patients as well as clinicians to know when they're thinking about wearable devices and the data privacy and security?
- [07:59]
C
I think that it's very important. It's our data and we have to make sure that it is secure and does not get released. I think that this is an area that's new and growing so fast that we need some, some form of regulation to make sure that the data is secure. I think, I think there are guardrails out there. Already to prevent patient data from being released. But I think we just need to watch it very, very carefully because it is, it is our data. The flip side of that is, you can imagine to do meaningful research in this space, in the AI space, in the machine learning space, we need a lot of data. And the more data we have access to, the more efficient and more accurate the models can be. So it's a little bit of a balance because we need the data to be able to come up with these breakthrough discoveries. But we have to be cautious with the data and protect it in such a way where it doesn't leak out and get into the wrong hands.
- [08:59]
B
That makes sense. And thank you for clarifying just the state of the union of where things are at with that type of data and how we can move forward. Now, I wanted to dig a little bit deeper into as well, a collaboration that you're doing with FIU using voice technology and whether it's something that can actually be the next vital sign for patients when they're going to the doctor to help identify some issues that could be upcoming. So could you tell us a little bit more about that?
- [09:27]
C
I am super excited about this collaboration with FIU and an example of something that we couldn't do without fiu and FIU probably couldn't do without us. When we look at typical vital signs, your heart rate, your blood pressure, your O2 saturation, those are standard vital signs. But the hypothesis is that couldn't voice, or could voice be an additional vital sign? I ask you, when was the last time you talked to a friend or a loved one and you said, wow, that person doesn't sound right? You can really put your finger on it. But that person sounds like they could be sick or you yourself are sick and you realize that there's something going on with your voice. There's some objective data to actually support this. If you imagine that for me to talk right now, it requires all these neural networks to come into play for me to formulate a relatively complete sentence, but that's actually not enough. Once I have this sentence in my mind, eventually there has to be these motors that have to activate. It actually ends up, you actually end up activating about 100 neuromuscular units just to be able to phonate and articulate, to say what you want to say. In summary, it's this complex interplay of your brain be able to formulate stuff and then after that the muscles and the firing. To be able to articulate things is why you're able to hear what I'm saying right now, but something that hasn't really been explored or studied at all. The hypothesis is that, well, instead of a vital sign, a heart rate predicting when the patient's not going to do well, what if we use voice? There was a study that FIU did with high school students and they got a large number of high school students and had a good number of baseline data on their voice. Some of these, and a lot of these high school students were athletes. Then a small percentage of these students were athletes and had concussions. And they actually did the voice study after they got the concussion. And as you can imagine, their voices sounded very different. That was a proof of concept scenario. What we're looking at is let's say you have baseline information on someone's voice, they have surgery, and then you record their voice daily until. And you can imagine right after surgery, their voice probably won't sound the same the next day after surgery, it probably won't sound the same, but at some point their voice should normalize back to it was before surgery. We have now this pre surgery, right after surgery, time to normalization. But let's say we continue to follow that voice. What if by day 30 or day 60 we realize that while the voice is changing again, could it be a predictor or sign of something? That's our hypothesis, is that one. Let's define when the voice normalizes after certain operations, certain procedures. But if later on changes in your voice could then predict beforehand something bad is going to happen to you. This is why we think it's super exciting. Imagine it's a lot easier vital sign as well. Instead of having to purchase machines to latch onto you to check your heart rate and your O2 saturation, we could potentially have apps that listen to you or you record into your app and then be able to potentially diagnose what's going on. We're excited about it, more to come. But this is a great study that we're doing in partnership with FIU that's.
- [12:57]
B
Amazing to hear and really cool application of technology and ideas around how you can take some of the different symptoms or ways that our body reacts before we even know it to something that's going on or something not being right and then being able to level it up. And really, ideally, as you said, take care of some of the issues ahead of time. And that brings me to my next question is when you're looking at technology, I feel like the capacity and capabilities are so much more complex now just because we have artificial intelligence, predictive capabilities and More. So is there anything else there that you are really excited about? When you look into the future, how do you see AI and other technologies continuing to evolve, especially when it has to do with heart care?
- [13:45]
C
I think we're only at the tip of the iceberg. I think our world now will be incredibly different in the next three, four or five years. For the better, I hope we'll be a lot more efficient about making decisions. I think we'll be a lot more accurate about making decisions. I think we'll be able to retire to predict when things will happen. I also wanted to offer a word of warning as well. We recognize that sometimes too much information can be bad. You know, let's say if there is a technology to predict your life expectancy or when things, bad things will happen to your life, down to, you know, the minute or the day, that could be exciting. But is that something that we really want to know? There are technologies out there that can replicate your voice, my voice, replicate my image, and create AI agents so that you can talk to me or you with a certain level, level of expertise. So that allows me to be, allows me to scale and be a lot more efficient. But then you also can imagine that it can, if it got, if got into the wrong hands, it could allow a lot of fraudulent activities as well, where it's someone that is not me, that is pretending to be me and doing bad things. So I'm excited about the future. I think overall it's going to be very transformative and the world's going to change for the better. But I do think, and know that we have to approach it with caution and with appropriate guardrails to make sure that this technology won't get out of hand.
- [15:26]
B
Got it. That's really interesting to think about both the very real benefits and then the challenges and risks involved with continuing to expand this technology and doing it responsibly, especially in the healthcare setting. It's such a unique space and something that requires a lot of care in order to get right and high stakes as well. I'm curious, when you look at everything you're doing, I know a really big part of what you're doing at Baptist Health South Florida, as well as, you know, many health systems across the country, is looking at some of the health disparities in trying to close that gap. How do you see technology playing a role in being able to reduce those health disparities and make monitoring more accessible?
- [16:12]
C
It's an equalizer, you know, by. By being able to access technology to answer questions, to Diagnose patients to provide therapeutics at a fraction of the cost could then now allow us to spread a lot of what we know about medicine to people who wouldn't otherwise have access to it and potentially even decrease healthcare costs. We also know that with disparities, there's different levels of disparities in and medical knowledge and medical understanding, as you can imagine. But now there. There are technologies out there that we can use and leverage and be able to translate and interpret medical information. So that is digestible, not only for physicians, so, but it also can be digestible for a regular patient, or it could be translated to any other language. And I'll give you an example. You know, when's the last time you might have had a complex study done, let's say a CT scan, an X ray, an mri. And you look at it, you're like, well, I don't know really what this means. Well, there's. And the reason why is a lot of that language is written in kind of medical talk. And there's technologies now where it can take that information and then now write it in such a way where you can read it and understand it. But it's also powerful. It can do that and then translate it to Japanese, Spanish, Italian, French, whatever language that you want so that you can actually digest it and share it with others.
- [17:49]
B
Wow, that sounds incredible. And really helpful and beneficial for patients across the board, those like you mentioned who might have access issues, but then also just for anybody to be able to better understand their care and exactly what's happening in their bodies, I think that's critical. I know we're about ready to wrap up the conversation, but is there anything else you wanted to mention or share with our audience that you're excited about? Some of the ways that this technology in heart care is evolving, especially as the patient physician relationship continues to evolve as well.
- [18:23]
C
You know, since I'm a surgeon, I'll end with a surgical note. One of my mentors was Norm Shumway. He performed one of the first heart transplants in the United States. And one of his famous quotes was, the hardest thing about heart surgery is a chance to do heart surgery. And what that means. It can mean a lot of different things, but one of the things that it meant was when you get there, the actual part of heart surgery is hard. But the harder part is getting a chance to go to medical school and go through the training, but then learning how to do it and actually practicing and getting there. But what if we can have technologies that allow us to learn more efficiently, to be able to practice more efficiently and have simulators to do things more efficiently, so that the hardest thing about heart surgery isn't the chance to do it. It's actually just a heart surgery itself. You can actually make it a lot more efficient to be able to learn with that. There are technologies now that can do a lot of the things that we do autonomously. Research that Stanford and Hopkins have studied videotapes of robotic surgeries. And now, after looking at thousand, thousand of videotapes, have had these robots be able to, autonomously, without human control, do some basic things that we do in the operating room, for example, to tie knots, to pick up the needle holder, to manipulate tissue. It's amazing that it's able to do this autonomously without a human controlling that. That's just the tip of the iceberg. Then if we could do that, then when does it end? And this is opportunity where you could potentially use robots to do operations that previously were done by humans. Again, still at its infancy, but a glimpse into the potential of where healthcare and medicine and surgery might be going.
- [20:14]
B
That's incredible. Dr. Nguyen, thank you so much for joining us on the podcast today. This has been a fascinating conversation and I look forward to connecting with you again soon.
- [20:22]
C
Thank you. My pleasure. Thanks for having me.
- [20:26]
A
At athenahealth, we know your ambulatory practice wants healthier a healthier business, healthier care teams and healthier patients. But the complexities of modern healthcare tech make it hard for you and your care teams to focus on what matters most. That's where athenahealth can help our AI native all in one solutions. Reduce administrative burdens, streamline billing and payments, and deliver critical insights when clinicians need it most. That means fewer clicks, more time for patients, and stronger bottom line. Practicing medicine is complex, but running a practice can be that much simpler with athenahealth. See how simpler is healthier at athenahealth.
- [21:06]
B
Com.