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Welcome to the KuppingerCole analyst chat. I'm your host. My name is Matthias Reinwarth, I'm an analyst and advisor at KuppingerCole analysts. And my guests today, again is Annie Bailey. She's an analyst with KuppingerCole focusing on emerging technologies again and still working out of Stuttgart. Hi Mathias. Thanks for having me. Great to Have you again.
And, and this is the second and promised part of a series of episodes that we want to do about emerging tech in healthcare. And we, we did this a few weeks ago and we started out on the one hand with looking at what are the goals that we want to achieve until 2030. And that is the SDG three from the United nations requiring that, um, we have to ensure healthy lives and promote wellbeing for all at all ages. And as we are also a technology analysts, of course, we look at what's going on in the technology sector.
And you've mentioned a few of these, um, emerging technologies, including AI machine learning, IOT, blockchain, and especially important for KuppingerCole digital identity is as key factors impacting the healthcare sector. That is where we closed down our first part of this series.
So, um, Annie, when we look at these individual technologies, let's have a look at some of the use cases where these technologies, these trends are really showing up in real life. When you start with, with AI, with machine learning, um, where do you see some real life use cases in some really emerging and benefiting use cases for the individual Patient?
Yeah, it's, uh, it's really interesting. What's going on up there. It's difficult to look at all of healthcare and all of AI, because these are both monstrously huge terms, which encompass basically everything.
And so it, it helps if we can pair this down a little bit in, in what we're talking about. And so if we can categorize at least AI applications for healthcare into those use cases, which are targeted to improve patient care, um, we can think of this as one very large category and then another category being improving hospital workflows, working towards more efficiencies. So if we take a look at those categories, um, there's use cases for improving patient care of having an impact on their treatments and their therapies. We of course have cat bots.
This is a top bots are of course not new, but they're becoming more and more sophisticated in being able to help patients self-diagnosed, um, to type into the window, their symptoms, and be given suggestions on what, uh, what that could be to, you know, other, uh, symptoms to look for, or watch out for. Um, and of course, to inform them on possible next steps, if they need to be referred to a doctor for more investigation, or if there's a home remedy, which they could try and see if that helps relieve their, their symptoms.
So this is one thing which has out there, which is impacting patient care. Another is to take a look at the way patients actually follow a treatment. Once they've left, the hospital can think of this as adherence to a treatment plan.
And AI can be harnessed here to collect some behavioral data to mark when a medication has been taken, or if certain dietary requirements have been fulfilled, and this can be collected and analyzed to help understand what behaviors lead to, uh, a patient sticking with a treatment or what behaviors lead to, um, failure to, to fulfill that treatment, which can of course then help doctors and outreach staff members to, uh, find good intervention strategies to help patients maintain treatment and ultimately continue on their, their health journey or their healing journey.
Uh, so these can be thought of as, um, AI for improving patient care. There are many, many other use cases which fall under here. If we pivot and take a look at AI for efficiencies, for improving hospital workflows, reducing no shows for appointments is a really big one because, uh, a doctor's time course is very valuable.
Uh, if they have a patient who doesn't show up for an appointment, that's simply lost time and lost money and is incredibly inefficient. And so, uh, similar to, uh, the patient's adherence use case behaviors can be tracked and analyzed to help understand which patients are at risk for not showing up, help understand why and help drive the interventions and the, the community health efforts to help make sure they are able to attend their appointments.
If it's a matter of time of day of transportation, of other responsibilities, um, help understand what is driving their choice to not show up for an appointment. So on the One hand, we are talking about improving the leveraging of existing resources, doctor, uh, caring facility. But on the other hand, we are looking and that's most striking to me. We are really, um, improving the scalability of, um, health care processes.
When I talk to a chat bot, this is really know how that has been extracted of people's of doctors minds, and that can then scale up to serve many more people at the same time, at least for a very limited and narrow focus, but this can really improve the overall, um, patient care in general. So this is really striking to me that that AI and machine learning in particular are really contributing to providing a better and a much more scalable healthcare here.
Um, so that's, that's great to hear, um, often mocked and often not well understood blockchain when we talk about blockchain in healthcare, um, can that have similar effects when it comes to, uh, using blockchain in healthcare use cases? Yes.
Um, surprising for some not surprising for others. Uh, it can be a really useful piece here and a theme that we've talked about already in this podcast.
Um, and in the previous time we were talking about healthcare privacy and the appropriate use of patient data is a really, really important factor here. And, um, blockchain is, is seen by many as a means to ensure the privacy of data and that it is handled well, and that processes are transparent, but private. So this can be used actually in some digital identity use cases in identifying a medical staff member or identifying a patient and having access to their house records.
Uh, this is something which can be facilitated by blockchain, not always, but again, it, this is one possible architecture for facilitating the digital medical ID. And so this benefit really comes from having a secure storage of proofs, being able to securely store the proof that I am, who I am, that I'm not a medical professional.
Um, I should never be hired as one because I do not have these qualifications. I am, um, in this scenario patient, and that proof, which would be stored securely is also able to be shown that it's not been tampered with that. I haven't added extra qualification to my profile that nobody else has done that.
Um, and so that's where the value of blockchain comes here in facilitating the safe transfer of data, but also presenting credentials in the form of a digital ID. This could also be useful in tracing pharmaceutical drugs throughout, um, production to retail sale.
Um, then finally to the home to make sure that the production setting and all quality controls were followed and that, uh, it can be traced from really production to use. Yeah, I think this issue of counterfeit drugs is really a large issue in several areas around the globe. And I think when we have some, yeah, supply chain controls, imply chain management, supply chain tracing, that is really an important thing, especially when it comes to such essential goods like pharmaceutics. So I think that is really an important thing. So it's supply chain control, but mapped to the healthcare system.
So if I look at my phone in the evening, I can, can have a look at my heartbeat over the complete time of day. And when I did sports, most probably not. And I can see really some information that my smartwatch took from me and communicates to my, to my cell phone.
Um, so this is one aspect that I can see in real life already when it comes to IOT to wearables, but there are much more IOT use cases that you have had a look at when you did your research, right?
So just as you say, the, usually the first thought that somebody has when they think of the combination of IOT and healthcare is a smartwatch, this is a really popular and, um, will most likely be a very fast growing section of the health market of being able to deliver this personalized care, personalized experience, uh, you having direct access to your own health information and with a means to process that and gain insights. So we can think of that category as wearable IOT devices, something which you could just have with you put on carry with you. There are also implantable IOT devices.
These are not quite so popular. It's a very invasive process, but is becoming more standard as a medical procedure. One example could be a smart retina for those who have vision issues.
Um, a smart retina could be inserted into the eye as a means of helping the eye adjust to different light intake, different color intakes, help balance stepped perception when needed help in these situations. So this is, uh, something completely different than a wearable device, which you could just put on your watch, but yet it is having a very clear impact on a particular health issue. And you also have, um, another category of IOT called ambient IOT. And this is the concepts that you as an individual could have an impact on your environmental context through IOT control.
And so this would be, think of, for example, a hospital room where you from your bed can easily adjust the lights, the temperature, the way your bed is oriented. If a visitor could come in and visit you or not. So access to the door, communicate with your health staff, query your ID, drip, to know how long it has to remain hooked up to your arm. Things like that, things where you can interact with the ambient environmental context around you. Right?
So, Um, yeah, these implantable IOT, uh, this was a bit scary to me too, to be honest, but, but yeah, I think this is something where, where we really have to go forward. Um, and, and this is something that really can solve immediate issues, and that is really a nother way of curing existing issues.
You've, you've touched it quickly. Um, there's a whole topic of digital identity is something which we might elaborate a bit on. You've talked about, uh, identifying, uh, health professionals and their qualifications, and to make sure that only those people who are the appropriate people can actually execute tasks in a healthcare system.
Um, and you've mentioned briefly the digital medical idea of the individual patients or the individual health files that you have, um, can, what are use cases, um, connected to this digital identity, um, that we should, um, look forward to or that we should expect very soon? Yeah. Digital identity is, is going to be a really critical piece in a health care journey towards digital transformation.
So at the, at the hospital level, at the private practice level to a Countrywide initiative for digital transformation, um, so we've talked about it a bit earlier, how important data interoperability will be, um, and how that's connected to a patient centered journey, um, or a patient centered process.
And digital identity is really critical to this because if data is going to be able to be moved between institutions securely and safely, the data has to be connected with the patient, um, that it, it can be unambiguously very clearly identified so that, um, there's no risk to the patient of their data being mixed up and them being treated for, um, a health condition that they do not have.
That's very important for patient safety, but also for patient privacy that although their data can be identified with them, that it could also be used without personal connection to help drive insights on a larger scale of health issues, which are happening in a region or, uh, in this scenario, how pandemic infection rates and the situation is developing. So a digital ID is really critical here to enabling data transfer, but it also has to be done right, because it has to be protecting the patient at all times, Right.
There is a concept that we see in digital identity in general, which is called user managed access or something that is entitled self-sovereign identity. I think that really comes into play here as well to make sure that just want to go to a tourist store. I have to prove that I'm of legal age to, for example, buy a bottle of whiskey there. Then it's not required to show my name or to say my name, or to show a picture of myself. There should be only the proof that I'm off legal age. That should be enough. So just an attribute based authorization.
And I think the same is true when it comes to health records, when it comes to digital medical IDs, sometimes it's not important what my name is or my age is, or how I look like, or if I'm male or female, that all does not care when I'm, when I had an accident and then I'm lying on the street and somebody has to do the initial first emergency treatment, then they should know what kind of blood I have.
And if there is any additional information to take into consideration for treating me in the first place, and this is just a set of attributes that should be easily available via a digital file or via a file that is easily accessible. But I think this is something where we really have to go forward to, to understand that we provide the right information at the right time and we keep it under control of the individual patient. Yeah. I can't agree more with you.
Okay, Great. So, um, thank you very much for talking about these individual use cases.
You set, there is much more to come and we just picked out a selection of what you looked at. And there is, as I said, much more to come.
Um, so I expect that there will be more further episodes when we look at these emerging technologies in healthcare. And in other sectors that you are looking at any final thoughts that you want to add any, when it comes to looking at the healthcare, is this something that you expect to happen very soon to get a broader and a much better way of having healthcare? Yes and no.
So, and in one sense, um, these solutions are really driven by medical research. Um, and it should be that way as you, as you mentioned earlier, the idea of implantable IOT, smart retinas and the like is really very scary. Yeah. I agree. That's beyond many people's comfort zones yes. And should be driven by medical professionals for particular medical issues. So on that end, um, it may be very slow on the other end.
There are AI solutions which are being developed now to help streamline, uh, clinical trials to help more quickly gather participants to help streamline identifying new drugs for, for new therapies, um, and help that along the development pipeline. Uh, so it's, it's a very contradictory, uh, statement to say, if development will go quickly or slowly, it will be both. Right.
So, and then usually when we talk about, um, defining the right strategy for introducing technologies, we usually as analysts talk about a risk-based approach this time, I think we should talk about a benefit based approach. So wherever technology can provide the most benefit to the, to a larger group of people. And you've mentioned these chatbots for first diagnostics, I think this is something that can quickly provide a high level of benefit for a large group of potential patients. And that is something where this development might already start right now. Thank you very much.
Any again, for being my guest today, for the audience who are listening, um, please go to our website KuppingerCole dot com and search for emerging, just in as one key word in our search engine. And you will be guided to documents and research provided by any and our colleagues when it comes to these emerging technologies around healthcare, financial services and other sectors. So thanks again any for being my guest today and looking forward to having you in an upcoming episode Soon.
Thank you, Mathias. We'll talk soon. Bye-bye bye-bye
