Patient generated health data and the future of wearable technology

Dan Draper (00:00:15)
Mobile health apps and connected devices, including sensors, wearables, as well as emerging technologies, like digestibles and implementables, are enabling consumers to proactively track and manage their health anywhere, anytime, and from any device. Previously geared towards consumer health enthusiasts, healthcare practitioners are now beginning to adopt these technologies for patient monitoring and to drive improved health outcomes. This panel will look at the emerging tech in this space. What are the benefits of patient generated health data? Where does it create complications, and what do people need to know about using them, including implications for their data? What does this technology mean for the future of health? Today we are joined by Brittany Schoeninger, principal at IQVIA.Brittany Schoeninger (00:01:06)
Thanks for having me, Dan.Dan Draper (00:01:08)
Harry Gasiamis, head of sales at Garmin.Harry Gasiamis (00:01:11)
Great to be here, Dan. Thank you.Dan Draper (00:01:15)
And Robert Read, CEO at MedAdvisor.

Robert Read (00:01:18)
Thanks for having me, Dan. Great to be here.

Dan Draper (00:01:20)
Thanks for joining us. Let’s get started. One in six consumers own a wearable. We’re tracking things like nutrition, sleep, stress. What’s the impact on wellness and health? Harry, let’s start with you. I’d love to get your take.

Harry Gasiamis (00:01:37)
Yeah. Sure. No doubt, the use of wearables, from my perspective, has been a big advocate for improving health literacy amongst the population. These devices collect lots of data. The data is made available to consumers in a really easy to interpret form in the apps, I guess, that come native as part of the devices. If you look at, in our case, the Garmin Connect. We’re really seeing users get to the stage now where they’re really alert to the fact that their body is behaving in a certain way, they want to keep seeing the numbers come through and it becomes something really interesting for them. I think that whether it’s our apps or whether it’s third party apps it really gets to the point of giving consumers a really simple way to understand what’s happening with their body. From a general health outcome perspective, we’re seeing really positive impact on health outcomes for users.

Dan Draper (00:03:55)
On that last point, looking at this through the lens of the health practitioners, what is this increasing data availability mean for general health literacy? I’ll start with you Harry and then perhaps go to the group.

Harry Gasiamis (00:04:09)
Having access to a patient’s biometric data over the course of a proceeding period of time, for example before they come in for a consultation, might give that practitioner an ability to get some really good information at a pretty basic level. We’re not saying, “Here, this is a medical device and it’s being used for diagnosis”, but if I came in to see my GP and he could quickly have a look to see that I hadn’t been sleeping well for the proceeding four weeks, that my activity was really low, that my stress levels were really high, just as an example of some of the data that’s available off these devices, I think that could be quite meaningful when it comes to the general consultation and understanding a little bit about what’s happening with their patient before they present in the clinic on that day.

Dan Draper (00:05:14)
Understood. Rob, your app is geared towards providing better data outcomes for patients. How does that have an impact on the health literacy of your users?

Robert Read (00:05:27)
It’s a great question, Dan. Health literacy is a major problem in Australia and, in fact, in most developed countries. The Australian government released statistics not that long away that showed that Australia had a health literacy of about 41%, so 41% of 18-74 year olds had adequate health literacy. Flipped around the other way, six out of 10 people don’t have the adequate health literacy to understand what their healthcare practitioner is telling them. That’s a problem that needs solving and that’s where we’ve seen some really big insights in terms of being able to connect patients with information that’s directly relevant to them, to the medication that they’re on so that they can understand the disease type that they’ve got, the side effect profiles that they might have, how to manage those side effects appropriately so they stay adherent to their medication. We’ve seen significant improvements in medication adherence from simply that understanding. It’s not that they don’t want to be adherent to their medications, they don’t understand necessarily and that’s where information can be quite powerful in terms of health outcomes and that’s something that we are really big on advocating for.

Dan Draper (00:06:40)
I’ll go to Brittany. There was a recent study by IBM Watson that talked about this idea that one person generates something like a million gigabytes of health data in their lifetime. It’s like a petabyte of data, which is unheard of amounts of data. Working in the field that you do, where you’re talking about data and the human impact of that data, should we be concerned about the amount of data that we’re storing on behalf of users and patients?

Brittany Schoeninger (00:07:11)
Yeah. It’s a good question. I think the short answer is no, as long as privacy is appropriately protected, so wearing my hat as a researcher, when it comes to healthcare, data privacy is of the utmost importance, so naturally, all users should be providing informed consent as to how their data is going to be used, both from an analysis and research perspective as well as thinking about who’s going to have access to that data in terms of healthcare professionals and any other stakeholders. As long as you ensure that you have the appropriate privacy protections and consent in place, I don’t think we need to be afraid of generating more data.

Dan Draper (00:07:49)
What about then transparency? We’re talking about privacy protections, and obviously there’s legislation, increasingly so, around data protection. Is there an obligation for organizations to simply be more transparent about how we’re using the data?

Brittany Schoeninger (00:08:03)
Yeah. I think transparency is key and that should all be communicated clearly through the consent that the patient provides and naturally that all needs to follow within the guidelines of the Australian privacy principles, definitely.

Dan Draper (00:08:16)
Understood. On the topic of data, one of the challenges, I guess, with data and sort of the subject of this conversation is giving more data to patients, it’s not just about providing practitioners and clinicians more data, but it’s about actually giving patients more data. I’ll go to you, Rob. I’m curious to understand, what are the risks or are there any risks of providing patients with access to far more information than they’ve ever had before?

Robert Read (00:08:47)
Dan, I’m an absolutely advocate of consumer empowerment and trying to take control of and understand in their own health outcomes. I don’t think there’s anything wrong with that. I know there’s been a very long journey of democratization of data, the new modern technology platforms and wearables and other devices means that we’re getting so much more information that can be really valuable to clinical outcomes, and I think that’s where doctors who are so time poor and they’ve got such limited space with a patient. If they can come in and in that consultation know what their heart rate’s been over the last X period of time, know that their medication adherences has been slipping on these three medications, but not on these four, or that their DNA might not match nearly with this medication. That’s all available today and a consumer or a patient can actually advocate for that and create better outcomes for themselves and better outcomes for the broader healthcare system.

Robert Read (00:09:49)
I don’t think as an industry we should be concerned about consumers knowing more. I don’t think that is a fear that has played in other settings and typically the democratization of data leads to better outcomes, better solutions and certainly happier and more satisfied patients and customers and healthcare practitioners. For me, I don’t subscribe to the theory that you need to, as a healthcare practitioner, hold back information solely for the purpose of knowing more. It’s really about sharing in that journey with a patient and we’ve sene that play out in the marketplace quite considerably. You see it in the US as well, where the richness of data that can be made available for clinical settings is significant and I think that’s something that we should be encouraging as an industry to work in partnership [inaudible 00:10:44]. I think that counts for ourselves and for our patients.

Dan Draper (00:10:49)
Harry, I’ll go to you. Garmin is on the forefront of the wearable tech revolution, shall we call it. How reliable and how accurate are consumer devices that are tracking things like heart rate, compared to traditional clinical medical devices?

Harry Gasiamis (00:11:07)
Yeah. That’s a really good question. I think, like any sort of product in the marketplace, you’re going to have a really broad spectrum of products available. The wearable space is obviously really crowded with many, many brands, and just like any other product that you’re looking at, I guess there’s going to be products at the good and the bad end of the spectrum and obviously data reliability falls into that spectrum as well. To speak about what we do, we spend a lot of time and a lot of resources and many, many years developing not only the hardware that we sell, but also the algorithms and the sense of technology of the data that we collect. It’s just as important to be able to identify noise when you’re measuring a pulse ox reading as it is to say that you’ve got a really bright screen.

Harry Gasiamis (00:12:07)
From our perspective, we do a lot of work in that vein and I think the consumer need to do their homework. You can see that’s what people do anyway. There’s a lot of options for various products that we consume on a daily basis and people are educated. There’s more opportunity to get information about what it is that you want to do today than there ever has been. Being able to access that information and make an educated decision, I think, is really key.

Harry Gasiamis (00:12:44)
The other thing that, again, speaking from a Garmin perspective, is if you’re wanting to look at a decision on what to buy and whether or not the data is any good, you just need to look at some of the relationships that exist today in the wearable space. We have relationships with leading global insurance companies who are now using the data from these devices to get better insights into the risk that their insurers pose. That isn’t something that an insurance company would do on a whim. If the data isn’t reliable and they can’t make a mathematical prediction on whether or not someone is less likely or more likely to make a claim, they wouldn’t be using the data. I think we’ve got a long way, but it’s absolutely important to understand that there is a spectrum of products and data out there and you need to be really careful about what you choose to work with.

Dan Draper (00:13:46)
Brittany, is data reliability something that you put a lot of consideration into at IQVIA?

Dan Draper (00:16:44)
Brittany, at IQVIA, is data reliability something that you think about a great deal?

Brittany Schoeninger (00:16:50)
Yeah. Absolutely. I’ll admittedly probably come at this from a slightly different angle wearing my research hat. I spend most of my time thinking about new and innovative approaches to observational research design, and actually the idea of being able to access a fully interconnected data ecosystem that enables us to track patients beyond the clinic is massively exciting to me as a researcher. You can imagine the possibilities if you were able to access a database that contained information almost in real time on a patient’s activity levels and vital signs and self-reported quality of life. This could be massively powerful in enabling us to understand a patient’s health in a way that would never be possible through a cadence of clinical trial visits alone.

Brittany Schoeninger (00:17:35)
However, the main caveat, and this is the reason why we’re not seeing more widespread use of digital and wearable technologies in the mainstream in clinicals trials is because we do still need to remain true to out core principles of evidence generation, so use of high quality fit for purpose data and use of validated end points as well. That’s not to say it’s not possible and we’re seeing some really interesting examples where sponsors are beginning to dabble in this space and dip their toes in. One of the more common ones is use of built for purpose clinical trial apps to collect patient reported outcome information in a digital or virtual way. Another really nice example is the mSToPS study that was published back in 2018, which basically tested whether use of a wearable ECG patch could improve diagnosis of atrial fibrillation relative to routine clinical care. The idea there naturally being that if you can improve methods for early identification, you can initiate patients on appropriate therapy and prevent longer term adverse health outcomes.

Brittany Schoeninger (00:18:44)
It was a really fascinating study design. It was basically a randomized pragmatic trial that was done in an entirely sightless fashion direct to participants. They recruited patients in directly through a large US health plan and the study was a success. They saw higher rates of Afib diagnosis in the patient population that was monitored using the wearable ECG patch. That was a really valuable proof of concept demonstrating now only how these types of wearable technologies can help us to improve patient outcomes, but also thinking about how these types of technologies can allow us to really reimagine research and make studies more participant centric. I guess overall, this kind of exponential growth in available patient generated data is really exciting and hold a lot of potential in terms of it’s ability to allow us to innovate and research design, but with the caveat, that is always the case in research, we need to remain true to the core science and ensure that the data is of sufficiently high quality and validated and fit for purpose.

Dan Draper (00:19:48)
Rob, how do you think about data reliability?

Robert Read (00:19:53)
We look at the data in a really interesting way in terms of what Brittany was talking about in terms of identifying patients for clinical trials. Being able to recruit them is a big barrier to getting more clinical trials into this country and finding new and innovative medicines for Australia. One of the advantages with having data, in our MedAdvisor and certainly other systems, where the dispense connected means that you can actually identify patients who are eligible and meet certain criteria. We have done a number of trial recruitment processes where we’ve been able to find the relevant patients within days or weeks, not months and years. The advantage for that is that new and innovative medicines can come down the pipeline quicker.

Robert Read (00:20:39)
From a patient’s perspective, it’s really valuable because they get access to a trial they may never have heard about before. It’s always consent and they’re opting into the process, which is really critical that it’s them driving it, but they’re being afforded the opportunity because of the insight into the data that we can provide. That includes the [inaudible 00:21:00], so the PPI, so where are they located? Are they close to the trial site and all those sorts of important criteria that can often be missed using traditional methods. Once you’re in market and you’ve got a product that’s operating, then looking at the phase four outcomes. How is the drug being used in real life? MedAdvisor has looked at the data and the global data that says 50% of people are adhering to their medications. We looked at 10 chronic medications across a large pool, at one point, 3.3 million people, and found that the adherence to those medications was about 54%. Almost one in two pills were being taken. The doctor thought that they were doing the right thing, the patient thought that may have been doing the right thing but they weren’t.

Robert Read (00:21:49)
What is the role in technology in that case? Well, the role of technology is to help educate the patient. Why aren’t you taking this medication as prescribed? Can we help you, remind you when your prescription is due, remind you when you need to see the doctor and remind you what time you need to take that medication? They’re the tools that are available today. We can actually influence patient outcomes based on the medication data that’s there and we can provide more and better insights to the clinician to help them identify areas of better care or change of medication, potentially, if there is a challenge. That’s really what we’re about is leveraging that insight and to help advance care and outcomes and patient outcomes.

Dan Draper (00:22:50)
That’s really fascinating. Harry, we’re seeing an increased tendency, I suppose, for wearables to have a connection to social media where users can start to share some of their data, perhaps for emotional support. In these situations, is there a risk of an increase in patients self diagnosis and how do you and Garmin think about that challenge?

Harry Gasiamis (00:23:18)
I think it’s a really good question, but to be honest, I think the concern about self diagnosis, for me, that ship’s already sailed. People consult Dr. Google every opportunity when they come up with the slightest something. I think there’s a lot of anecdotal evidence that it’s creating problems with the medical fraternity anyway, because people are looking at a symptom, going to Google and saying, that’s okay. I won’t worry about it and it’s a skin cancer or something. I think that’s a bit of a root point, but to go back to your point about whether or not it’s useful, it absolutely is. We see significant improvement in just engagement outcomes, in motivation. People love the social aspect and what it creates from a challenge perspective, and you look at the situation that we’re in today and we’ve had a massive of not only device purchases but usage of devices and people are actually contributing data and engaging with their friends because it’s the only way they can connect at the moment. They can’t go out for a run together. Park runs have been every weekend, they’re gone, cycling events.

Harry Gasiamis (00:24:36)
The social engagement is a key part of the success of the individual and the outcomes they want to achieve. I think it’s incumbent upon app developers, wearable manufacturers to really let the consumers know in the right way during their experience of using the device, using the app that if they exhibit or experience symptoms that might be concerning, they really do need to consult with a medical professional. It’s a responsibility that we take seriously. Our devices pick up certain alerts. There’s lot of social interaction with what we do. We create groups, but ultimately, where we have certain things that appear to the user, we let them know that perhaps you should go and see someone about this. If you get an abnormal heart rate alert during one run in a year, maybe don’t worry about it, but if it happens every time you go for a run, they should be going and seeing someone about that.

Dan Draper (00:25:42)
We’re sort of transitioning from this idea of wellness to more, I guess, vital data, such as heart rate or even ECG information. Does this put an increased responsibility on GPs knowing that their patients may be getting access to this data themselves? What are some of the ethical ramifications that come as a consequence of this?

Harry Gasiamis (00:26:11)
I could probably speak a little bit to that, I guess. This is a conversation I’ve had with a lot of medical professionals over the last two or three years because you have a section of the fraternity that really want to embrace these technologies and then for as many of those you probably have twice as many that want to run the opposite direction because they don’t want to have the legal responsibility of having to act if they see something pop up. I think it’s something that we can address in a couple of ways. In my mind, the way that these could become useful is we’ll use the data terms, pull and push. I think having an opportunity to pull data in when there’s consent from the patient and the doctor maybe is consulting or the pharmacist is consulting with that patient at that period of time or before they know that they’re coming in, I think, is something that can take away that fear and obviously the whole conversation around litigation and responsibility, and also, let’s not forget, the amount of additional workload that having a push type system would put onto a general practice.

Harry Gasiamis (00:27:22)
They would have to have people sitting there, like in a call center, monitoring the data coming in all the time. It’s just not feasible. I think having an ability to pull data when you need it for a particular purpose is the way that this would work and could alleviate the concern within the GP fraternity. Having said that though, and to prove the point, we have a number of programs running successfully all over the world and in Australia today. As a really good example, we have thousands of orthopedic patients who currently have Garmin devices given to them as part of their initial consultation with their orthopedic surgeon. Given the device, the surgeon will monitor pre and post-op activity levels and use that data to number one, ensure that they’re adhering to their rehab and to assist with building a better program that’s going to be beneficial and provide the best outcome for that patient. In that instance, again, it’s really easy. It doesn’t create any friction, there’s no additional workload. Something that’s completely built within the way that the specialist wants to consult.

Harry Gasiamis (00:28:45)
I’ll probably finish by saying, at the other end of the spectrum, there’s also probably a good need, and if the use case is right, for having got a push to someone. If you think about the example of an assisted living or an aged care facility, where someone might be in a room and they’re not necessarily being seen by a nurse every couple of hours, you could have got a push to a nurses station for that individual, or even if they’re at home, but they’re suffering from some sort of an acute condition. I think there are use cases that can benefit both, but in my mind, I see the ability to pull data when you need it is probably the majority of how this would work.

Robert Read (00:29:30)
I absolutely agree, Dan. I think we’re staying in discussions with some of the general practitioners we work with, when there’s a view of adherence that we can provide on behalf of the patient, which is really valuable clinical information, but again, that worry does prop up, does this force me to do something, and I think the expectation from our side is that really that it’s a pulled scenario that I’m about a see a patient and I want to just check their adherence, as opposed to getting it every fortnight or every month and have to dive into it. I think that’s the distinction that’s going to make ti work in the industry more broadly.

Dan Draper (00:30:12)
Do we also need to be setting patient expectations in that context?

Robert Read (00:30:17)
I think that the expectations of patients are rising hugely of their healthcare practitioner, I think, to Harry’s point earlier, some healthcare practitioners will embrace it and look for additive insights from the unstructured data they’re getting in from the various imports and use it in a sensible way, in a clinical way where appropriate, and there’ll be others who are going to resist it. I think ultimately consumers will be making choices about their healthcare and who’s participating in a collaboration or a partnership with their healthcare practitioner who’s been given doctor’s orders, if you like, and having to follow them.

Robert Read (00:31:22)
That distinction is a really interesting one that I think is going to emerge over the next five [inaudible 00:31:29] as more information becomes available to consumers about what’s going on in their body and how can they advocate for themselves most appropriately. I think that’s a really good thing, but it’s going to take both sides of that marketplace to really come together on what’s appropriate and have doctors have conversations with patients who are really out of line in what they’re suggested. It’s those age cases where these things can come unstuck and definitely is going to take some more thinking and work to make sure that it works on a mass scale.

Dan Draper (00:32:07)
It’s interesting. There are a great number of consumer apps on the market now. A lot of them are starting to generate what consumers might conceive as clinical data. Should we be concerned about accuracy and reliability here or, let me put it another way, how trustworthy is this data? For example, should we include them in electronic health records? Brittany, let’s start with you.

Brittany Schoeninger (00:32:34)
Yeah. That’s a really interesting question. I think it really depends on the data. Quite an unhelpful answer, but it depends. If there’s some data that’s being collected for a very specific purpose, so if you have a patient where you want to make sure they’re following a specific exercise regimen and you give them a Fitbit for instance.

Dan Draper (00:32:55)
Or a Garmin.

Brittany Schoeninger (00:32:57)
Or a Garmin, or any kind of wearable device to track their activity levels, that could be quite helpful for the physician to track for a specific purpose, but I think data just for the sake of more data is perhaps less helpful or even potentially dangerous because it becomes difficult to sift through the wealth of information to figure out what’s actually relevant. I think it really depends on the specific use case, in my view.

Dan Draper (00:33:23)
Harry, what’s your take?

Harry Gasiamis (00:33:25)
Yeah, I agree. Having data for the sake of data is not necessarily a good thing, but we sort of touched a little bit before. The integrity of the data is still going to be key in ensuring that you’re working and your programs are working with data and devices that you feel are trustworthy and can do what they want. It’s interesting that you mentioned electronic health record. We deliver data via our cloud, I guess, to thousands of organizations around the world who have all got their own take on what they want to do with that data. In Queensland, there’s an organization who has decided they want to integrate wearable data into their version of any easy to understand electronic health record, because anyone who has logged into the myGov health thing knows that it’s complicated, there’s a lot of information there, it’s in medical speed, so the average consumer doesn’t really know how to process that information.

Harry Gasiamis (00:34:31)
That lends itself to a few other questions that were asked before, but here’s an app that has got data that is taken from the electronic health record, it’s processed in a way that makes it easier for the patient to understand and they believe that it’s important to be able to supplement the data that’s in that app with some wearable data that comes from the individual’s device, should they choose to connect it. I think we need to remember that’s also a big thing as well. A lot of these programs, they’re not mandatory. You can do a lot of these things without having a device, but if you do get the device and you choose to connect it, then you’re going to be able to supplement the data that you’re getting and you may have a richer experience and get more information.

Harry Gasiamis (00:35:19)
To get back to what we mentioned before about reliability and the quality, if you choose to go and get yourself a $20 something that you found somewhere cheap on eBay, well, you’re probably not going to get as good as an experience if you go and buy a reliable brand that has got a lot of science and credibility and brand recognition and awareness behind it.

Robert Read (00:35:42)
I think that’s right. There’s a nuance around the data that’s going to make the difference, so the quality, the accuracy, the reliability. Again, if you can get medication data out with live dispensers that’s entirely accurate, then you’ve got a really good insight versus a patient reported outcome in that case, where I think I’ve taken it most of the time, I can’t remember or I’ve forgotten it. Those sorts of objective measures can be additive and I think as you say, Harry, you don’t want to just get a huge amount of influx of data from varying sources, because that could lose the quality of the insights out of that.

Dan Draper (00:36:25)
What are some of the tools that GPs have available that we might want to think about in order to help bridge this connection between patient generated health data and what might be considered traditional clinical data? How can the GP be the center point of those conversations?

Robert Read (00:36:45)
Certainly, from the way that we think about it at MedAdvisor is that we really feel like a GP is the coordinator or the conductor of the orchestra in terms of making sure that someone’s care is appropriately managed and each service is passed out to the relevant people. Where we can augment that, and that’s great, we certainly want to do that, part of our business is to support a GP in management of the script processing, particularly in regards to nursing home patients. We do that really effectively and potentially adds to what they might otherwise be dealing with, and certainly on a patient level in the patient consult we do want GP and patients to connect with their regular GP through a system like ours, so that they can have one GP, one pharmacist as their regular care providers and if the information goes around neatly and augmented so that they can get better information because they’ve got both end of data coming together.

Robert Read (00:37:50)
I think if we can do that, then I think there’s really strong value that can come back to the GP in how they manage their workflow and how they focus their attention on the patients has we’re going to need the most and potentially, some of those routine tasks can be more efficiently handled through the technology that already exists today. I think that’s where you start your efficiency from the diaries.

Harry Gasiamis (00:38:19)
I agree wholeheartedly with what Robert was saying. I think there’s a lot of tools in a GP’s clinic today already. There’s a lot of tools in a pharmacy that are thee. From a data perspective or a wearable data perspective, I mentioned before, we the availability to make the data available of our IPIs. It doesn’t necessarily need a complete system redesign. It’s not necessarily a complete overhaul that’s going to cost a lot of time and a lot of money to bring some of the insights that a wearable could provide into what’s being used in a clinic or in a hospital or in a pharmacy today. We’re working with people right now who are building solutions in exactly this place; in pharmacy in Australia, in medical practices in Australia.

Harry Gasiamis (00:39:21)
For me, the key is just understanding that the technology exists, understanding how you can easily integrate it and then just being prepared to have a look and see how we can enhance the experience that the patient, the GP, the pharmacist, whoever it is involved in that part of the loop, how can they enhance the experience with that individual? For me, I think there’s a lot of infrastructure already there that could be utilized quite quickly and quite easily today.

Robert Read (00:39:57)
Just building on that, I think your point, Harry, is spot on. There’s stuff there today that doesn’t require a significant amount of change. I look at what we do in the pharmacy space, it’s actually trying to identify patients of need based on the data that’s there in order to make the pharmacist do the right intervention or a better intervention that can help that patient more. It’s those sorts of things where it’s really automated, efficient and just making them better at their job that I think is going to be a transformative way in the context of potentially adjusting the workflows of these healthcare practitioners to make sure they’re focusing on the things that really matter.

Dan Draper (00:40:42)
Brittney, we were talking a little bit about data on a micro level, but flipping that around to sort of the macro, how do you take large sets of data and develop insights that might be able to be shared with practitioners or clinicians?

Brittany Schoeninger (00:40:58)
Yeah. The way that we go about it is using protocolized medical and scientific research. There are a range of different evidence domains against which you can run analysis to make use of this kind of massive data that we have available to us. It can be anything spanning from, as Robert alluded to previously, looking at medication usage patterns, analyzing pharmacy dispensing trends to understand how products are being used in practice, what’s the level of adherence and persistence, what are the most common dosing regimens? All of those types of things can be quite valuable to actually studying real world effectiveness and safety. There’s really a range of different possible evidence generation approaches that can fall under that umbrella of medical and scientific observational research.

Dan Draper (00:41:55)
One of the big things that’s come up being tipped as maybe the next big thing in wearable tech is this idea of an emotion sensor. What might the implications of an emotional sensor be in healthcare? Let’s start with you, Rob.

Robert Read (00:42:13)
I think if it’s good technology then it’s going to provide another piece of insight for clinicians to make adequate diagnoses and also be able to assess whether there’s a change in pattern. I’ve started a new medication and my mood’s gotten worse. How does that actually mean a prescriber is going to make a choice about the right therapy for that individual patient? Definitely, I think there’s a strong role to play for these types of things to start emerging. You see as well, in other companies, that have monitors to people’s face for pain when they implicate themselves as well. What’s there pain threshold? Where are they at? That’s a kind of emotional sensor that, I think, is quite relevant as well in the setting that new technology, it’ not perhaps as widely used as it could be, but those sorts of things can be, I think, very additive to the equation in the right setting.

Harry Gasiamis (00:43:11)
Yeah. I might jump in if it’s okay. We’re looking at emotion sensors is an interesting, quickest way to describe it, but we have partners that we work with today, again, who are already taking into account some of the data from our devices, like heart rate variability, for example, and using that, and we do it ourselves. We use a stress algorithm or we determine a stress score for that individual. We think about emotion and how you can measure it. Well, stress is an emotion. It comes about from a variety of different things that are going on with an individual and we have people using the data that we can produce with HRV and processing their own algorithms that are validated and scientifically proven and looking at how they can assist in monitoring people who potentially are exhibiting signs of mental stress. Obviously, it’s, again, in conjunction with a number of other metrics. We’re not saying that this is just [inaudible 00:44:30] one measurement of one wearable that does everything, but it’s, again, used to supplement additional information that perhaps provide a better understanding of what’s going on.

Harry Gasiamis (00:44:43)
A really interesting example I’ll probably share with you all is we’ve had a relationship with Mercedes-Benz for a long time, but in the last 12 months, Mercedes-Benz have taken this same heart rate variability measurement and they’ve taken their own algorithms that they’ve developed over a significant amount of time and they’re able to effectively connect a Garmin wearable to a Mercedes-Benz vehicle and the car is able to, in real time, read stress and heart rate variability scores coming off the driver’s wrist and they use their own algorithms to calculate what state that individual is in when they’re driving the vehicle. I’m not going to call it a fatigue measurement, because it hasn’t been validated as such, but they’re certainly looking to see what level of comfort the individual is in and based on the numbers that they’re getting off the wearable and a little bit of feedback out of the steering wheel, they’re able to do really amazing things with the car automatically. Things like change the cabin temperature, change the ambient lighting settings, increase the volume of the speakers when the radio is on, turn on the massage feature in the seat all in an attempt to try and stimulate the driver to have the best possible driving experience.

Harry Gasiamis (00:46:07)
In the old age, 18 months ago, that was all done by the driver going into the system, the vehicle software, and picking what they felt their emotion was like at the time when they were driving. Mercedes have taken that sort of feature one step further by adding imports from a wearable device to give them an ability to understand how they think the driver’s feeling at any point in time and make the car behave in a certain way to try and maximize their driving experience.

Dan Draper (00:46:39)
Wow, That’s really fascinating. Brittany, how would it change your approach to research if you suddenly now had this kind of data at your disposal?

Brittany Schoeninger (00:46:50)
It’s a really fascinating idea. Thinking about research specifically, I guess the low tech version of emotional sensors is use of patient reported outcome measures of PROMS, which there have been many studies that been conduced that show the benefits of collecting that type of information, even just the active recording your emotional experience and your symptoms can help assist with recall and facilitate a more rich discussion with your clinician later down the track. There’s clear value in collecting that type of information and if you could automate the collection of that type of data, who knows what will be possible. I also think it’s quite interesting in the current environment, one of the key challenges that I’ve heard from some clinicians in relation to the conductive telehealth appoints is that it’s very difficult to establish that kind of rapport and connection with the patient as you normally would in the room.

Brittany Schoeninger (00:47:49)
I guess another complicating factor is that many patients will be sitting there in a living room with their wife or their daughter or their friend a few chairs away and they’re not comfortable or as being as candid about their experience, so you could imagine this type of emotional sensor data could actually be a really valuable supplement to help you overcome some of those barriers.

Dan Draper (00:48:15)
Right. Yeah. That’s a really fascinating point. This is one of the things that I wanted to jump in on. It’s been claimed that remote patient monitoring will save something like $200 billion over the next 25 years. Where is this tech heading?

Brittany Schoeninger (00:48:27)
It’s a really good question. I think from a research perspective we’re seeing a pretty foundational shift from a model that used to be a study very much built around the site to one that’s much more participant centric where you have care being decentralized where possible, to your point, and where trials are being kind of built around the lifestyle of the patient, as opposed to the other way around. Naturally, COVID-19 has been a catalyst for change there, where more out of necessity than anything else we’re seeing an uptick in adoption of virtual trials where there can be many different components of that. Part of that is the use of digital patient generated data and part of that is things like remote trial monitoring and home treatment delivery and home nurse administrations. I think some of those positive changes will be here to stay in one form or another, but zooming in on the aspect of patient generated data specifically, I think, as I said previously, many of the use cases that we’ve seen to date have been relatively conservative in nature. For example, using study apps to collect patient reported outcome data using otherwise validated PRO instruments.

Brittany Schoeninger (00:49:43)
I think there’s a lot of room to grow in that space, and as we become more comfortable analyzing and interpreting this type of data, there should be increased applications moving forward. I think in the near term, one of the key points that we’ve been discussing is that’s a very useful supplemental piece of data, so I think it will continue to be used in addition to our more tried and true traditional sources of data and evidence, which means, in thinking about implications for trial design, prospective studies will be largely hybrid approaches where you have your traditional site based plus additional data that may be generated through wearables or apps or whatever it might be and then thinking about retrospective designs. I think, in the future, there’ll be a lot more data linkage where you’re taking your existing EMR data, claims data, et cetera, again, your traditional real world data sources and potentially pulling in this type of data to enhance or compliment the existing picture, what you can see in those traditional data sources.

Brittany Schoeninger (00:50:49)
At IQVIA, one of our key priorities is continuing to push the boundaries of clinical research to find ways to make studies more efficient for the healthcare system and for participants and for our clients alike and virtual trials will naturally continue to play a large part in that and that’s one of our key focus areas, but again, it’s not going to be a blanket or one size fits all approach moving forward. I think you need to think really carefully about which virtual design elements are going to be appropriate for a given study, given your patient population and your drug and your therapy area; thinking about the unique nuances and risks involved.

Dan Draper (00:51:33)
Rob, what’s in the future for MedAdvisor when it comes to remote patient management?

Robert Read (00:51:40)
I think it’s a significant opportunity when you think about the cost in aged-care settings, in hospitals, just even staying in hospital overnight is a huge cost on the health system. Being able to remotely monitor patients in their home, I think, is a significant opportunity for caregivers and for the industry alike, and most importantly for the patient. I think there’s more and more evidence that’s mounting the people in their home if monitored well will be able to perform better and recover more efficiently. As the same time, the insurers, health insurers, heading in that direction at the moment, based on the data that they are saying. I think this is a trend that’s going to keep growing, and therefore, the systems that are around it to support it are going to be critical. That’s from devices in the home to monitor movement, to monitor falls, to communicate more effectively, and then being able to tie up other systems that create dashboards for patients or their centralized caregiver, whether that be from a hospital, an outpatient clinic, or some other chronic health management setting.

Robert Read (00:52:51)
From outside, we’re looking to support that where we can. Of course, with patient consent and patients, of course, own all their data, in our view it’s their data, they can, where appropriate, and if they give consent, we will support them to provide it to someone who might be providing some form of [inaudible 00:53:12] to a hospital who’s providing care. Maybe start off in a much more simplistic way in the early days as we heard towards this journey of joined up data sets, but certainly when you think about patients moving in and out of hospital, one of the biggest transitionary care moments is what medication were they on, what medication are they on during hospital, and what medication are they on when they come out of hospital. Now, if we can help support that transition of care through linking that patient, linking their changes in medication with their caregiver, whether that’s a healthcare practitioner as a GP or that’s a pharmacist that we can direct that patient to the right place to get their care and keep them out of hospital and run programs to keep them out of hospital.

Robert Read (00:53:59)
I think we’ve seen studies out of [inaudible 00:54:02] that have chunked very effective improvements in readmission rates after 30 days from cardiovascular events from just simple lifestyle messaging and a program designed on a certain patient population. I think those are the areas where we, as an industry, can come together and make really good strides to make sure that people are getting the care in the spots that are going to be A, the cheapest and easiest and best place for the patient to have them.

Dan Draper (00:54:34)
Harry, same question to you. How is Garmin thinking about the remote patient management in the future?

Harry Gasiamis (00:54:44)
As terrible as COVID has been around the world, it has absolutely been the stimulus all over the planet as far as research projects, clinical studies and accelerating conversations that we’ve been having now over the last 24 months and more in some cases. In Australia alone, I’ve probably got a dozen or so projects on the go right now that have just been accelerated dramatically all to do with remote patient monitoring in one way, shape, or form. We’re talking about some of the largest research institutes in the country, major universities, enterprise groups that are playing in the medical space. I think there’s going to be a lot of good that comes from all that work. I’m really confident in some game-changing solutions that we start seeing in the next 12 months.

Harry Gasiamis (00:55:59)
From a Garmin perspective, this has always been an area of our strategy that we’ve been working on. We have a group within our business called Garmin Health and the Garmin Health team just works on work in, obviously, the health and medical space. That group has been in existence for a couple of years plus formally. Beyond that, it was around, but not in a formal sense. This is absolutely going to keep moving along in leaps and bounds. From a hardware perspective, it’s no secret we’re deep in development of software, medical devices. This, I guess, is something that the industry, to put it in some terms, needs to think about is in the next period of time, I won’t fix on a date, but 12, 18, 24 months, whatever it is, you will start seeing software as medical devices released from consumer wearable brands, including us.

Harry Gasiamis (00:57:14)
These products, obviously, will have been approved by the various regulatory authorities in various countries and the data will be considered of a quality good enough to really do things with and there won’t be all the second guessing that there is today. The question is, how prepared will the medical fraternity and the healthcare system and all the organizations that work into healthcare, how prepared will they be to start working with that data when it becomes available? We can start having the conversation now and start looking at how we can work with what we have, which in some instances is really good and to Rob’s point, it doesn’t necessarily have to be that most sophisticated solution, but it can be something that gets the ball rolling and in time, as the technology gets to that regulatory phase, then the switching from a consumer device that doesn’t have any regulatory approval to a consumer device that does all of a sudden is an easy step to take. We really need to think about that.

Harry Gasiamis (00:58:22)
If we’re going to be sitting here talking about a consumer grade product that has regulatory approval, that is going to provide the GP, the hospital, the pharmacy, organizations such as all the ones that are represented in this call today, with am instant amount of customers that they can start engaging with. Are you going to be prepared to do that at that point in time or do you start thinking about how you’re going to integrate with those consumers today? Really, I think that’s a really key theme. I understand that there’s a lot of reservation about how these things work today, we’ve covered a lot of that, but the reality is, and if you want to draw a parallel with the transporting industry, the transporting industry is one of the most highly regulated, highly monitored industries on the planet.

Harry Gasiamis (00:59:24)
They have regulations coming out of everywhere. They have sensors on vehicles that log every second of that vehicle’s journey. It’s a really good parallel to draw because the information needs to be, and we obviously work quite heavily in that space. I’m talking from experience here, but the data that is collected has to be a high enough integrity to comply with legislation that requires it. It’d be subpoenaed for use in courts of law if you get to that point. Where I’m trying to go, I guess, the medical industry won’t be the first one to come up with this sort of a system and to try to work out how to make it all happen. The transport industry has been doing it for a long time. They continue to advance and push what they’re doing. I think the opportunity for health is huge. We’ll know the benefits that it can deliver, but from a financial, from a outcome perspective, time, everything, resources. I just think there’s some really good stuff happening today. Let’s find out more about it. Let’s work at how we can embrace it and see what we can do to start making some [inaudible 01:00:47] towards 12, 18, 24 months down the tack when we start getting some more of these consumer grade software as medical device products out there, which all of a sudden present a massive opportunity.

Dan Draper (01:01:04)
Indeed. Certainly some important and fundamental challenges for our industry moving forward. Today’s conversation has been absolutely fascinating. I really, really enjoyed it, so thank you all for joining us today.

Brittany Schoeninger (01:01:14)
Thank you.

Harry Gasiamis (01:01:15)
Thank you.

Robert Read (01:01:15)
Thanks, Dan. Great to be here.