Sensors: Reinventing Medicine with Jag Singh, MD, PhD

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Ultimately, there is no way to prevent the impact of these changes, even if they are not yet fully understood. Sensors and artificial intelligence, for example, are already changing healthcare, leading to questions on what their impact will be heading into future generations. We can't help but ask, is the reinvention of medicine a pending positive or perhaps a technical and logistical nightmare that will make staying healthy even more daunting and divisive.

Our next guest is a welcome expert on the future of medicine, both its promises and challenges. He's here to shed some much needed light on what we can all expect. Keep listening.

So again, as always, the best part of our podcast is when we get to dive into the subject at hand with an expert. And we certainly have an expert today on biometrics and sensors, what it means to people, where it's going, what can we expect, maybe some of the misconceptions as well. And that's Dr. Jag Singh, who is out of Boston, Massachusetts.

So, Dr. Singh, welcome to our podcast today.

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[00:02:01] John Salak: Well, just as we were discussing before we started people in general know that biometrics sensors are here. They're more important than ever, but they may not understand what the difference is and in general terms, what we're looking at. So can you start off in the broadest terms of what are biometrics. Maybe how they different from sensors, how do we begin to define this emerging technology and impact?

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There kind of digital markers of who you are to identify you. Sensors are slightly different. They are devices that respond to physical stimuli and they measure those physical stimuli. And those physical stimuli can be temperature, can be physical activity, can be motion can be respiratory rate or even sleep.

So those are all different measures that are picked up by sensors. One easier way to understand this is to understand that the word sensors is derived from the word senses. So, our touch our auditory senses, our visual senses, our taste, these are all senses and sensors are derived from these senses because there's a really cool saying from an author called Emanuel Cant who said that all knowledge comes from our senses.

So, all these senses that come into our body through the neural network, go to our graphical processing unit, which is our brain, and actually give us all of this knowledge. So I think it's important to recognize that sensors in the healthcare space are devices that can pick up these senses and give us physical attributes for them so that based off those measurements, we can then decide what we need to do for that particular patient or individual. Whether there's any information we can gather, respect to their disease or not.

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What makes these devices so powerful and are they that powerful now?

What makes this such an intriguing element?

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So there are many aspects to care, but sensors are really the central part of this whole equation of how care pathways in the future will actually look, because sensors allow us to receive continuous data about an individual, whether they're well or they're unwell, and that continuous data allows us then to understand what disease process they may have, it can help us predict, it can help us risk stratify and can then allow us to prevent disease or intervene early before something bad really happens. so really they're powerful in the form of giving us objective evidence. So in fact, if I'm seeing a patient virtually, right, over a TV screen. But if the patient can transmit their heart rate, their blood pressure, their respiratory rate, their oxygen saturations through sensors directly to me as a clinician, I'm actually being powered by objective evidence as to how they are feeling across that screen rather than just having a glorified telephone call or a virtual call with them.

So I think sensors are powerful because they can provide information about anyone, anywhere, at any time.

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[00:06:06] Jag: Let me categorize healthcare as a pyramid and divided into three levels. The largest part of the pyramid is mainstream care, which is wellness. The second part of the pyramid is midstream care, which is chronic disease, and right at the upper end is complex disease.

So now we already have sensors which are built into our watches and rings. That can provide us data regarding our physical activity, our heart rate, our sleep, our steps. And even our mental faculties and some of them they can actually assess your behavioral patterns too.

That's where I think sensors have already made an inroad. They are now being upgraded into helping us manage chronic diseases . So those chronic diseases are diabetes.

Are hypertension or heart failure. Their progress and their clinical stability can be measured by sensors that then allows us to intervene appropriately. And the third step where sensors will actually, eventually have a role is in complex inpatient care.

Some of that is already happening where you know when a patient is lying on their bed in the hospital, not only does the bed have a sensor to measure their weight, it can have a sensor to measure their respiratory status. It can have a sensor to measure whether they're in heart failure or not, what the fluid status in their lung is.

So you can imagine that sensor. Grades will be overall engaged in looking after patients at every stage, when they're well, when they're unwell, or when they're really sick.

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So what do we see these sensors at least doing now that's gonna be different than what we see in hospitals already in the near future?

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You have a blood pressure cuff that measures your blood pressure and you have ECG electrodes that have ECGs and can measure your heart rate. All of these are. Fixed variables that have been there for many years and continue to be there in the standard care of any patient. You take this one step further and you can have sensors in an in-hospital environment that can not only measure all of these things together.

But can also measure your posture. Your position in the bed can measure the fluid levels in your body, can measure your respiratory rate, as well as if you're developing heart failure or not, can measure your weight. There are ambient sensors in the room that can measure your risk of falling. It can assess for GA stability.

So there are many complex forms of inpatient care. And if you're in the ICU setting, and I was just on a call just before this, where we're actually looking at sensors that can measure cardiac contractility and cardiac output, and all the invasive hemodynamic measures that we have where you have to put catheters inside the body to measure the pressures inside the heart.

Now you can do them non-invasively by just a surface` sensor. So which can pick up these signals, interpret them using AI algorithms, and then allow us to manage these patients without the invasive lines that we've always been giving these patients and even continue to give them today. But the sensor developments are gonna simplify the way we manage these patients with the intention that a lot of these patients who require invasive monitoring and the sophisticated monitoring can actually get a lot of this care at home through home health strategies because now we can have the same objective evidence. From these sensors that can be remotely transferred across to a command station in the hospital.

So you can effectively monitor the patient while they're at home with some visiting nurse services or someone else who can kind of look after them. But you can only imagine that way you can provide access and everybody prefers to be at home rather than the hospital. So you really enhance the patient experience and potentially the outcomes.

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[00:10:57] Jag: Yeah, I think we're already seeing it in parts, in certain tertiary academic centers like ours. We're seeing it in bits and parts, but it's not evenly distributed. I, I think there's a lot of variability. Many of these sensor strategies are in their early stages of validation. And they have to be validated diversely because they have to serve a diverse patient population.

They're not all a part of some phenomenal integrated remote monitoring, sensor-based platform. That's the holy grail, that's the future. I would say we're hurtling quickly in that direction but we're still a fair distance away.

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[00:12:07] Jag: I would say yes and no. I think yes, they would be challenging to get to, but now the opportunity of actually providing them care where they are

Changes many fold, right? Because now you have sensors that and a simple iPad that can transfer the information across to your hospital network. And you can have algorithms that can help provide care to them.

So you're actually democratizing. Care better through some of these remote strategies because just imagine somebody living in a rural area for them to even make their way to the community hospital, leave alone, a tertiary center can be several hours long journeys, and then waiting in the waiting areas.

And now if you create the right infrastructure locally, which I think. Is really possible. And I think many health plans and academic centers are thinking about investing in these proactively because the overall, healthcare can become sustainable. Only when you actually democratize this care and actually bring down disease and monitor it better.

I think we are, we have a unique opportunity to actually serving our rural population much better than we did before, but I get your point. I think there is this always digital divide between the haves and the have nots and there is a large subset of our patient population that do not have access to these digital technologies.

But I think this, these digital technologies and the opportunity for actually creating this connectivity is much better now than it was in the past.

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[00:13:50] Jag: A hundred percent. I think any healthcare plan or. Organization has to start and is already paying attention to the social determinants of health. And I think we recognized that during Covid when there was a huge divide in how patients were getting care and. Which patients in the disenfranchised were actually, suffering worse outcomes but was impacting the overall healthcare system.

And I think we've recognized that we need to be better at that. And I think remote monitoring strategies and digital strategies and sensor-based approaches provide us with that opportunity to actually deliver care better.

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Are they like Fitbits? Well, or even in the future? Are they something embedded in US implanted? What do you see the options?

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But these devices have sensors that can measure the same things that I told you. Heart rate variability, autonomic system parameters, sleep, can measure respiratory rate, can measure transthoracic impedance, that whether your lungs are filling up with fluid. Now these are implantable sensors, but now you also have variable sensors, right?

So I'm wearing an Apple watch and an ora ring right now. From these, you can actually measure the same parameters that I just talked about through implantable devices. But beyond that, now we have a slew of variable sensors that can measure, for example continuous glucose monitoring that can, be used for diabetes.

There are newer sensor strategies that are being developed. To measure BNP or troponin that can measure the risk of a heart attack or the risk of heart failure. There are sensors on toilet seats. These are ambient sensors that can take your weight, record your ECG, and also assess your microbiome all at the same time.

So, so there are ambient sensors. There are variable sensors, and they're implantable sensors. And I think if you look at. The future would be kind of having all these sensor strategies integrated.

But at this point in time, even if you can have single sensor based approaches for single diseases, it's good enough because you're able to provide better individualized care cater to that patient's physiological parameters.

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[00:16:56] Jag: Yeah, I know that's a really good question. I think the ideal situation would be is to look at this as a proactive strategy, right? And I say proactive strategies because you don't want the disease state to develop. And if you can catch, for example, diabetes in a pre-diabetic stage and take care of it, we know that.

It's a lifestyle disease in many PA individuals, you can actually prevent that from occurring. And the same thing with hypertension, for example. On the flip side, that doesn't mean that you don't implant it in somebody who already has the disease state because now you can react to their clinical perturbations and individualize the way you actually manage those patients.

So, so I think it, it is both reactive and proactive, but the intent is to have sensor-based approaches that can be proactive so that you can predict, can risk stratify, and then you can prevent disease in most of these individuals.

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[00:18:00] Jag: Oh, for sure. so let's take diabetes as an example because I'm quite sure most of your listeners will recognize that diabetes is a challenging thing to monitor and people take insulin as well as medications for it, and they have to usually finger stick themselves three times a day to know what their blood glucose level is.

And they don't know what their blood glucose level is for the remaining part of the day, besides the time when they stick their fingers.

So if you, on the flip side, have an implantable sensor that is providing you continuous glucose, minute to minute, second to second, whenever you need it, you can check what the glucose level is.

You can actually check what the levels are before a meal and after a meal. So you can see what. The impact of that meal was on your blood glucose levels and how you need to really change the protein carbohydrate content of your meal so you can better control your blood sugar levels, or how do you need to adjust your medications or your insulin levels to better treat your disease?

So the idea of a sensor is to provide continuous monitoring that can then enable individualized treatment strategies. But the ultimate goal is to really empower the patient to be able to look after themselves. And this is a concept I call MYOD, it's called Manage your Own Disease.

One of the reasons why healthcare is non-sustainable is because, everybody's kind of on their own terrain. But if patients were to have some skin in the game and could take some ownership of their own disease state with this continuous feed of data and how they could regulate their disease state, you can only imagine that they would have better outcomes.

They would be able to look after themselves better and it would translate into healthcare costs, reducing over time.

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[00:20:02] Jag: Yeah, so when I talk about reinvention of medicine is what I'm really saying is that we need to reinvent our clinical care pathways. And when I talk about that, I also say that the future of care is sensors and biometrics are a small component of them, but they need to be integrated with virtual care strategies.

They need to be powered by artificial intelligence, and they need to fit into the clinical workflow so we can deliver better care. What I try to say is that we need to step away from the conventional transactional care strategies that we have. So you know when you have an illness or you see your doctor, you see them on a six monthly basis or a yearly basis.

Right now, you don't fall ill on a six monthly or a yearly basis. So what I'm saying is we need to create strategies for continuous monitoring, we have to move from this transactional mode of care into something that's more continuous so that we can predict and prevent disease and provide the best individualized treatment strategy.

So it's more of reinvention of care, but I added to that is artificial intelligence, which we haven't talked about. And I think AI-based strategies can, beyond sensors, better enable us to risk stratify disease at the same time better enable us to actually treat patients in a more individualized way.

And I think that's another part of the equation that we need to be paying attention to.

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[00:21:38] Jag: Yeah, for sure. So let's take one of the questions you could ask me is, JAG, you have all these sensors sending all this data. Who's gonna monitor the data? And how are you gonna integrate the data? How are you gonna interpret the data? And how are you gonna then take action based off that data for just one individual, leave alone scaling it at a much larger level for hundreds of thousands of individuals?

And the answer to that is that, you can have data without information, but you can't have information without data. So this is where we need artificial intelligence strategies to really help us collect. I. Help us curate, help us annotate and help us analyze this data to provide us with the interpretation and the action that needs to be delivered that can be scalable.

and this can be done for individual disease states at the same time it can be done collectively in remote monitoring platforms. So you can look at the continuous flight. Paths of different patients to see what their trajectory is so you can intervene proactively.

this is where artificial intelligence comes into play. For example, you can look into the eye of an individual. Look at the retinal photograph and you can predict what their blood pressure is, what their diabetes control is, whether they have kidney disease, or whether they're gonna develop Alzheimer's in the future.

Now, how is that possible? That's possible using, convoluted neural networks by looking at deep learning algorithms, looking at their eye pictures that can predict this. That's where AI will allow us to be better in our predictive analytics of how we look after our patients.

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[00:23:21] Jag: Absolutely. Right. I mean, all of us love to practice medicine the way we've learned it. And many of us have learned it in the traditional, conventional way where it's all about, one-on-one and meeting the patient. And it's just that with the burden of disease and the changing demographics and the availability of technology that allows us this massive processing power and connectivity.

We can provide that care, but we can provide it in an integrated fashion with human touch along with this technology. There is resistance. Obviously there are. People who are early adopters and there are people who are late adopters.

But I think folks have figured out that this is the way medicine will be practiced in the future.

We have to adapt to the times. We have to be able to give the highest possible level of care that's individualized. And that doesn't happen without all this information being curated and analyzed in a sophisticated fashion. Just the simple stethoscope of the past. May become a relic in the future if you have all these other objective parameters that are being sped to you in a more consistent and continuous way, rather than just using a stethoscope.

So, so I think the human touch component, which I think most clinicians like me, feel is really important. But have to recognize that we have to move along with the times because sensor-based approaches and AI-based approaches. Are becoming a part of how we deliver care. And I think most clinicians have started accepting that, but with some degree of resistance, which I think is gradually dropping away.

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[00:25:13] Jag: Oh, absolutely. I think there's this whole concept of bedside manners and website manners. And learning how to interact and interface with a patient on the web over virtual care strategies is slightly different from the bedside. And I think that's something that is becoming a part of the curriculum of new trainees in clinical medicine.

So I think Covid catalyzed that transformation into virtual care. And I think we recognize that's something now we need but appended to that virtual care I told you also that many of us feel that virtual care, just a televisit sometime is like a glorified phone call because you don't have objective measures at the other end of the phone call.

And that's where sensor is. We'll provide that objective evidence while you're having that virtual care phone call and will really transform the way we look after our patients. And if you have a lot of sensors with a lot of data over several months of recording, that'll be analyzed by AI that allow us to give the individualized decisions.

So, yes I think there will be some change in the pathways and the acceptance to telemedicine is certainly becoming easy. But I think the next steps of acceptance of using sensors and AI in the same telemedicine interview I think will also become a way we function in the future.

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[00:26:45] Jag: So the challenges are, obviously the hospitals look at it from a return on investment.

Is this form of care reimbursed? is it across state borders or not across state borders? And does it translate into better clinical outcomes?

Is it cost effective? Does it save us money? So many of those things I think are barriers to acceptance, which you can imagine, in, in our capitalistic society, that those things are really important. And I think those are things that were accruing evidence for it as we move along.

And the barriers to adoption will diminish. As we get that data and much of it is already, coming pretty fast along the way and. There are some things that we may not have the data for and we recognize that seems like the best way forward. And that's where I think academic healthcare centers and academic healthcare plans will have to step out of their comfort zone and say, Hey.

Let us experiment a little bit out here and see if it translates into better outcomes and reduces costs. And then we can make this, center stage.

But somebody's gonna have to be willing to take some risks to change the care pathways faster.

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[00:28:24] Jag: I think that you're spot on. As you enhance access as you try to make this more equitable the risk of privacy and security of the data comes up. And I think it's incumbent upon us to ensure that we have accountability for that, and that the right regulatory aspects and barriers and guardrails are being put in place.

And many of them are. But they're, again, early in the stages because a lot of the technology is moving so quickly, fast forward that many of these regulatory guardrails take a lot of time to implement. And by the time they have them ready, the technology's already changed and evolved. So those are things that I think absolutely this technology doesn't come without downsides.

So those are some of the things that we need to be paying attention to and ensuring that everybody's comfortable with that.

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[00:29:35] Jag: I think there are people in different phases of their lives will have different misconceptions, right? Depending on how comfortable they are with data, how comfortable they are with digital devices, and how comfortable they are with, looking at the interpretation of their health through biometrics and sensor-based data.

I. But trying to give this a philosophical view I think people are most concerned that too much of connectivity can actually disconnect us to some extent or this attempt for personalized medicine through digital strategies can make medicine impersonal. Because you're not seeing the doctor and it's all sensor-based approaches, and you're just getting your data analyzed and being told what to do.

And I think it's incumbent upon us to really ensure that there is a hybrid strategy out here that, you have the human touch. That is integrated with this digital wizardry, because, somebody smart as one said, I think it was Francis Peabody who said that the secret of the care of the patient lies in caring for the patient.

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[00:31:04] Jag: Absolutely. take a look at the book. It's very simple. It has about, I think 25, 26 patient stories. Every speculation of how care would look like is based around a patient story and how actually some of those changes already taking place. I also write about the future of the hospital and what the hospital will look like.

Much of this is in. I would say is five to 10 years away. So it's not futuristic, it's not dystopian at all. It's very clinical, it's very palpable, it's very tangible. So yes, I think this is around the corner and I think it's it would be smart for us to kind of accept it and move along with it, and then, curate it to the best of our abilities so that it serves everybody well.

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[00:31:54] Jag: Great. Thank you John. Thank you for having me.

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Signing up is easy and free. Just visit us at wellwellusa.com. Go to Milton's discounts in the top menu bar, and the signup form will appear. Signing up will take just seconds, but the benefits can last for years. So there should be no doubt by now that medicine is being reinvented. In fact, sensors, biometrics and artificial intelligence are already leaving their mark on proactive wellness care and the development of treatment pathways.

Their influence will only increase in the coming years tied to the growth in virtual care and telemedicine. However, just how fast they grow remains uncertain. Why? Well, there are a number of reasons hospitals and medical services have to figure out the numbers. Is the process profitable for reaching and easily deployable?

How fast will medical professionals embrace these new technologies? Can the industry create a service hybrid? That maintains a high level of personal care, or perhaps better said, website manners. While sensors and AI play an increasing role in treatment, finally, can an integrated remote monitoring sensor-based platform be developed and that'll tie everything together.

We suspect all these challenges will eventually be addressed and perhaps sooner than expected because the payoff in terms of positive treatments, potential cost savings, and proactive wellness care are too inviting to ignore. Besides it's already underway, medicine is being reinvented as we speak. Well, that's it for this episode of What the Health.

We'd Like to thank Dr. Jag sing for his time and insights. We'd also strongly recommend reading his book, future Care Sensors, artificial Intelligence and the Reinvention of Medicine. It is widely available online. And if you'd like to learn more about his work, please visit jagsingh md.com. That's J-A-G-S-I-N-G-H md.com.

Finally, thanks again for listening and we hope you'll join us again soon on what the health.

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