Neha Pathak, MD, FACP, DipABLM: Welcome to the WebMD Health Discovered Podcast. I'm Dr Neha Pathak, WebMD's Chief Physician Editor for Health and Lifestyle Medicine. Today is part three of a six-episode podcast miniseries we’ve launched over the past year. The goal is to highlight the needs of an aging population and the evidence-based models that can dramatically accelerate care improvement for older adults — which benefits all of us.

We’re taking a step-by-step approach to what age-friendly care means in the digital age and beyond, and how simple AI tools that you may already have access to can help you stay safer, more independent, and more in control of your health and well-being. We’ll walk you through safer ways to manage medications, new technology that can spot fall risks before they happen, tools you can use to improve your memory and mood, and most importantly, how to leverage these tools to track changes and ensure that your healthcare provider hears what matters most to you and understands what your baseline is — and where you’d like to get back to if you have a health setback.

If you’re curious about using technology to age well without becoming a tech wizard, this episode is your friendly guide. First, let me introduce my guest, Dr Kedar Mate. Dr Mate is the co-founder and Chief Medical Officer of Qualified Health AI, a company building infrastructure for AI-enabled hospitals.

Previously, he led the Institute for Healthcare Improvement as President and CEO, and currently serves on the faculty of Weill Cornell Medicine while co-hosting the Turn On the Lights podcast with Don Berwick. His career includes leadership roles in global health, hospital administration, and policy — all driven by his mission to improve health outcomes worldwide. Welcome to the WebMD Health Discovered Podcast.

Kedar Mate, MD: Thank you so much. It’s a pleasure to be here, a pleasure to be with you, and I’m excited to talk about this really important topic.

Pathak: We are very excited to have you. As I mentioned before we hopped on, I take this topic very seriously — or very personally — given my own life experiences currently with an elderly father, who we are seeing going in and out of the hospital and finding a lot to be desired in the care that he’s receiving. So, I’d love to kick it off to you since we’re really going to be focusing on AI and care for older adults. Start us off by explaining what age-friendly care means, and then if you could help us understand how AI can play a role in it.

Mate: Well, first of all, sorry to hear about your father’s challenges and troubles going in and out of healthcare — unfortunately, all too common for older adults as they get older in age and as they are exposed to more comorbidities and just general challenges of aging. It’s increasingly common.

So, interestingly, when we started working on age-friendly healthcare — this is in my previous role as President of IHI — we started doing that work with The John A. Hartford Foundation. The president of the Hartford Foundation, Terry Fulmer, came to IHI and said, “You know, we’ve done so much work to understand what it takes to create better care for older adults. In fact, we have lots of evidence, lots of research that’s been done on taking better care of older adults. But the trouble is that most older adults, including individuals like your father, don’t experience that better, evidence-based, exceptional care that we know matters to them.”

So, she said, “What will it take to create a national program that will allow every older adult in this country — in the United States — to benefit from what we know to be better care for older adults?” And that was the birth, if you will, of the concept of an age-friendly health system and age-friendly care.

To me, age-friendly care means essentially high-quality, person-centered healthcare that focuses on what every older adult uniquely wants. It’s not just about treating disease — it’s about achieving life goals for the older adult that matter most to them. Fundamentally, at the heart of it, if you strip away all the technical aspects of age-friendly care, it’s about centering on what matters to an individual older adult.

What’s your goal? What do you value most? What are your priorities? Is your primary goal to get to your daughter’s wedding? Is it to make sure you’re able to restart a running program you had when you were younger? Does it matter most to you to be able to take that trip around the world you’ve wanted to do your whole life? As you get older, it’s about what matters most to you — and that’s really what age-friendly care is all about.

And as we’ll get into in a minute, AI — among other things — becomes an incredible enabler of this kind of truly person-centered care. What does a good life look like for you as an older adult, and how can we help you get there?

Pathak: That’s great. So, as we’re having this conversation, in my mind, I’m going to continue to imagine my father — who’s just turned 89, actually — so I’m kind of thinking about him and his understanding of AI, which at this point, the most high-tech thing he has is his cell phone. He changes it every few months because it’s the best plan, and it essentially lays next to him when his hearing aids are off — he can’t even hear that it’s beeping. So, talk to us a little bit about how you envision optimized AI in healthcare as part of age-friendly care — just at a high level — and then we’ll dig into the pieces.

Mate: First of all, let me just say something. When I was the principal investigator and the lead for age-friendly health systems at IHI in my prior role, one of the things that made age-friendly health systems so scalable and so attractive to so many around the country — and indeed around the world — was exactly what you mentioned.

At last count (and it’s been a few months since I’ve been directly connected to the program), there were over 3,000 or 4,000 clinical sites practicing age-friendly care in the U.S. alone, and over a dozen countries around the world had picked up the concept and were running with it.

I think the reason for that is exactly what you started this program with — that every single person, whether you’re the President of the United States, the head of a health system, or a frontline healthcare worker, can relate to the notion of an older person in your life not getting the kind of care you want — or yourself not getting the kind of care you want out of the health system today.

That ability to connect the dots between abstract concepts like technology and what matters to you, medicine and mentation, and the other concepts of age-friendly care — but to connect all that to a story in your own mind of someone who matters most to you — is exactly why age-friendly care has so much traction and energy behind it.

Back to your question about technology — and admittedly, I think that’s not just the story of an older person. Most people probably relate to technology as the device they carry around in their pocket or use for Zoom (like we’re doing today).

But think of AI in particular as smart technology that basically learns patterns that can help you with daily tasks. The simplest way to think about it is as technology that understands how you act, what you think, and how you behave. It learns your patterns. It’s like a very attentive assistant — one that remembers your preferences and can understand when something deviates from those preferences. It’s pattern recognition at scale — a really attentive care partner that doesn’t forget and can spot subtle changes.

It’s nothing really scary — it’s just smarter support. And frankly, you probably already use it today in some way.

For example, if you, like me, turn on Google Maps whenever you drive to the grocery store — now, I know exactly how to go to the grocery store in my town, but I still turn on the mapping function because maybe it can save me two minutes or help me avoid a traffic jam. That’s pattern recognition assisting me with an activity of daily living — in this case, driving to the grocery store.

That’s exactly what AI technology is. It’s nothing scary — not some futuristic movie, Terminator-type nonsense. It’s really already present and active in your life today. Fundamentally, it’s about getting to know you, recognizing your patterns, and seeing where you might deviate from those patterns in regular life.

Pathak: So helpful, and I think centers another person in my mind that I’m envisioning as we’re having this conversation — and we’ll dig into sort of the four M’s — is my mother, who is his primary caretaker, and she’s 78 years old. And then you have these peripheral characters — myself and my brother and others — who are trying to participate in this care.
So, these are the folks I’m envisioning trying to utilize some of this technology and trying to envision how we might be better able to optimize our use of it. So let’s start by digging into each of the four M’s. So let’s start with what matters. How can AI help older adults, their caregivers, align with their sort of goals and priorities when it comes to what matters to them?

Mate: I mean, I think the story that you just told of your mother — and not just your mother, but yourself, obviously involved in your father’s care as well, as well as helping to support your mother — I mean, you all need a way of communicating and understanding what’s going on with your father’s care. And unfortunately, healthcare in this country is terribly uncoordinated, right? It is. There are lots of actors involved, there are lots of technologies involved — electronic health records or systems, your pharmacy, whether or not your electronic health record can talk to your pharmacy. All of this sort of stuff that is in the background of what it takes to remain reasonably healthy.

That’s not even including things that we now carry around in our pockets or wear on our wrists — the wearables and things that add new sources of information. But to coordinate across all of that, and to relate all of that to ultimately what matters most to your father, is kind of the essence of where AI-type enablement might help.

AI can, again, learn your individual preferences — again, what matters to you — and then remind your providers of those goals during your interactions with those providers, whether they’re family providers or official healthcare providers. No more repeating your story 10,000 times. You know, the system kind of learns what matters to you and keeps that front and center.

And it ensures, in theory, if we do it right and we deploy it correctly, that care stays aligned with what’s really important to everyone. So just kind of imagine this: you go into a visit, and the doctor might turn on their ambient documentation assistant. But what if the patient turns on their ambient care partner, and the AI listens to the physician? It already knows — because you’ve talked to it and trained it over the last many months of interactions — you’ve already told it what matters most to you.

And now the doctor is interacting with you or your caregivers, and the AI can alert you to the fact that maybe this plan to put you through a surgical procedure is not actually consistent with what you really wanted to accomplish this month or this year. And so that’s the kind of thing that, again, AI tools can be helpful to your provider’s documentation and supporting them to remember things. But just as importantly, AI can help patients and older adults keep track of what matters most to them and make sure that they’re not falling afoul of that original plan. So that’s a kind of example of how that could play out in real life.

Pathak: Yeah, that’s really interesting because I know I personally used a very low-tech mechanism to show folks in the healthcare system what matters by just creating a little poster with pictures of who he was before that hospitalization. So, this is him sitting up in bed or sitting up in a chair with his three granddaughters. This is him walking up a stair. This is him making food so that if I’m not at the bedside, I don’t have to explain that his goal is to get back to that level or as close as possible.

Mate: That’s right. There was actually a whole thing when we started the Age-Friendly Health System activity with health system partners. I remember very clearly at Anne Arundel Medical Center in Maryland — now part of the Luminis System. But in that hospital, when they deployed the four M’s for the first time, they did exactly what you’re describing, but they made it kind of institution-wide, right? Every older adult that came into their hospital would prepare a whiteboard that had photographs of them before they were in the hospital.

It would have preferences — you know, “Who’s your favorite sports team?”, “What matters most to you?”, “What’s your daily routine?”, “Who’s your most trusted caregiver or partner?”, “Who do you talk to every day?”, “Do you have any pets?” All that kind of stuff that really provides a little bit of information around what someone’s life was like before they got into the hospital.

Because the truth is — and you know this now from taking care of patients in healthcare systems — we take away all of that when we come into the hospital. We take away your clothes, we take away your food, we take away your pets — we take away what truly makes you who you are. And you’re now essentially a person in a hospital gown. You’re not anonymous, but you’re stripped away of what matters most to you and what animates you. That can be very disconcerting, and the care team doesn’t really have a reference point for what life was like for you before you came into that setting.

Pathak: Right.

Mate: So, to provide that kind of information — whether it’s done in the low-tech way that you’re describing or through usage of technology — there are now whiteboards that are technologically enabled so you can post pictures to them, etc., in the hospital room. But whether tech-enabled or low-tech, like you’re describing, the concept of enabling the care team to understand who you were is a central part of the “What Matters” story to age-friendly care.

Pathak: So then, let’s move along where I think I can definitely see application for AI with this second M — medications. So we’re talking about people struggling to remember what they’re taking, when they’re taking it, but also just a lot of new medications that are potentially added when you are hospitalized — those interactions, what shouldn’t be given to an older adult, and you don’t necessarily know when you’re discharged with the new prescription. So talk to us about AI with that.

Mate: Yeah, before I went to medical school, I was a community health worker, and I would go to people’s homes. The primary intervention — apart from social isolation and just interacting with people — was to look at their medicine cabinet. I can tell you all kinds of stories about what people’s medicine cabinets look like.

And I don’t know if any of your listeners can relate to this, but you come out of the hospital, you come out of clinic, you go to the pharmacy, you pick up a new set of those orange jars with the weird caps, right? And you put them in the cabinet alongside the other 20, 30, 40, 50 orange jars with white caps. And it’s quite difficult to discern which ones are the ones that you’re supposed to be taking and which ones you’re not.

So I would regularly encounter those shopping bags full of pills, medications, either in jars or out of jars — some that are over the counter, some that were prescribed — that people were quite confused by. And this is an old problem, right? It’s not a new issue, not a new problem. We’ve been talking about closing safety gaps in medication management for decades.

So I think this is perhaps one of the most exciting applications — not just for older adults and age-friendly care, but overall for medication safety in general: AI-powered medication management. It’s not just convenience. It can help us with smart dispensing, allowing your providers to check interactions quickly, help with understanding whether patients are taking their medicines, alerting family — like yourself or your mother — when a dose is missed.

All of these kinds of tools are now becoming much more readily available to us, and the consequence of that is reducing confusion for one thing, for our patients and our family members, but also candidly preventing lots of medication-related harm from occurring to older adults who, candidly, may not know exactly which jars in the cabinet to be taking the medicine out of today.

And the thing about aging is that, importantly, your body changes physiologically as you age. So a dose that you take today might not be the same dose — it might be the same medicine, but you may need half the dose a year from now, two years from now, three years from now. So you very well could have the old, higher dose in your medicine cabinet somewhere and make the mistake of taking that.

So this is really, I think, an important arena for technology in general. But AI-powered medication management, we think, might hold the promise — inpatient, outpatient, post-acute care settings, across the board, in the home — all of these arenas. I think there’s real potential. The tools are a little different in each of those settings, but the concept of using AI and technology in general to power medication management has the potential to save or improve many lives.

Pathak: Yeah, I find this piece so fascinating because I do, right after his hospitalization, there was so much titration of his blood pressure meds, of just other medications that were now added, and we’re gonna slowly titrate them off. And having a health background, clearly, as a primary care doctor, I can do that. But my brother, who’s not in medicine, was like, I don’t know how anyone does this normally, because I wouldn’t know — give him this, and give him half of this, and, you know, put this back on or take it off. So that seems like a very, very, very robust intervention, I think.

Mate: Yeah. The truth is that many people don’t do it normally, who don’t have that kind of training, unfortunately, and that’s where people run into trouble. The number of patients that I’ve admitted to the hospital with medication-related complications — either they didn’t take the medicine, or they took it too much or too little, or not in the right combinations — is probably one of the biggest sources of readmission to the hospital that there is. You know, people are left with the right instructions, maybe on paper, but translating those instructions into real-life application has been, and is, a major, major gap and challenge overall.

And that, by the way, is another application of AI — helping to simplify discharge instructions and make them much more easily relatable. Some of your listeners have probably been in the hospital and received that, you know, 20-page manual that you get when you’re discharged — half of which is useless and, you know, maybe two pages of which are really useful. AI is being used to simplify those discharge instructions, make them much easier to relate to and understand.

And frankly, you can feed those instructions to a publicly available AI to help. I’m not suggesting that that’s necessarily the easiest or best idea, but it is a way of helping to explain certain parts of your discharge instructions overall.

Pathak: Yeah, and again, I think especially with discharge instructions, I find it fascinating where tech is adopted and where it isn’t — putting “tech” in quotes here, to be an umbrella term. So when my father was being discharged, they were like, “Here, put it on this channel, and you’ll get a virtual discharge from a virtual nurse.”

And I was sort of like, that just does not seem optimal. We would like a human person to help us through, because we had some questions and we didn’t know, you know, how to set up this appointment or that appointment. So it’s just interesting, and I think we’re probably in that period of flux where we’re trying to figure out optimally, like, where is this technology gonna be most usefully deployed versus where is it that you need that human element during this process?

Mate: Yeah, that’s right. I mean, I think just because we have a technological way of doing something — a tech-enabled way of doing something — doesn’t mean that that is the right way or best way to do that thing. As much as I’m an evangelist, I think, for AI and technology enablement of a lot of things, I don’t think that replaces in any way the human interactions that are foundational to better care.

Frankly, I think that the caring steps in healthcare are absolutely not something that can be performed by a tech-enabled activity or an AI or otherwise. You know, this notion of particularly sensitive moments — I think those do need that type of human interaction.

I also believe, by the way, that AI clears the cognitive burden from the healthcare providers — potentially some of it anyway, the useless stuff — and enables providers to spend that time on those more high-risk or transition moments where there’s a lot more human interaction that’s necessary.

So in my view, there are ways of enabling that person-to-person, actual, real-life human encounter with technology in the background. But it’s not a substitute for some of those more important transition moments like you’re describing.

Pathak: Let’s transition ourselves to the third M — “Mind.” So we’re thinking here that that third M is focused on things like memory and mood. Can AI tools like virtual companions or reminders help reduce isolation, support mental well-being, and help with the “Mind” M?

Mate: This is very interesting. It’s not just, again, for older adults — like almost everything I’m saying has some relationship to care for the older adult, of course, because that’s the age-friendly concept. But part of what made age-friendly so attractive when we started it was that if you got this right for older adults, it was also much more broadly relatable as well.

Every patient needs to work on what matters, medications, mobility, and indeed on mentation and mind. So, a couple of ways in which we think technology enablement could help with mentation — cognitive decline, depression, delirium, dementia — as one ages.

First is about isolation, and this is really interesting. If you ask ChatGPT today, or any publicly available model, what it thinks it’s capable of — this is an experiment for those of your listeners that have used one of these AI tools: Gemini, ChatGPT, Mistral, Llama, Claude, whichever one you might use — just ask it what it thinks it’s capable of today and what it thinks it’s gonna be capable of in two years. It’s a fascinating experiment to perform.

One of the things it will say is that it can offer companionship to an individual. Now, whether you agree or disagree with this is interesting and somewhat confusing, but there is a possibility of offering some level of virtual companionship through an agent that understands you, empathizes with you, and provides that kind of connection.

There is a risk in this that I want to be clear about, and there’s a lot of regulation coming into play right now around this — the actual ability of these chatbots to provide behavioral health services or mental health services is a risk. On some level, there’s concern about that. There have been some high-profile cases of AI tools leading to adverse outcomes in individuals.

And so, we don’t believe that this is where the tooling is. It should not be seen as a therapy bot or a mental health provider. They’re not replacing the core requirements for mental health services, which still require human connection and facilitation. But they are potentially helping with this notion of social isolation in general — reducing loneliness.

They can also, and this is well-documented, provide technology supports that can support cognitive health, particularly with dementia. There’s some suggestion that playing specific kinds of brain games can support and help develop people cognitively. And then again, putting those games together with AI can allow for more carefully tailored programs that will help enable people’s mentation further.

So there’s a lot that’s coming online. I wouldn’t say that it’s exactly ready for prime time yet, but this is a significant growth area — a growth edge, if you will — for AI and technology tools today.

Pathak: So then our final M, before I ask you some more general questions, is “Mobility.” How do you see AI-powered tools, wearables, and smart home technology helping older adults stay safe and independent?

Mate: Yeah, I think mobility is perhaps one of the most exciting areas of the four Ms. There are lots of smart home extensions that can help with motion sensors and voice-activated emergency systems. There’s actually technology today that, using camera technologies, can identify gait changes before they become clinically apparent to either the provider or the patient, which I think is super fascinating.

Falls in the hospital or at home remain one of the biggest problems for older adults — one of the biggest sources of prolonged hospital stays, one of the biggest causes of admission to inpatient rehab, and obviously a big cause of fractures of the hip or lower extremities, as well as head trauma, etc. So, they’re a huge problem in older adults, and these cameras can actually understand — this is, I think, one of the coolest examples of how AI can help us.

We’ve always had cameras available to us in healthcare for a long time. Now, being powered by these algorithms that can help detect gait instability and gait changes before anyone else can see them — before the patient is even aware of them — that allows us to intervene earlier, provide physical therapy earlier, and provide occupational support if needed.

That allows people to potentially correct the deficit that would eventually cause a fall and sort of avoid the fall altogether. So that is, I think, an example of how we’re moving from post hoc — somebody has fallen, now we’re going to recover — to something that’s proactive and predictive. That’s really going to change how we address a leading cause of morbidity in older adults. For me, this is perhaps one of the most exciting areas in technology and how it might influence older adult care.

Pathak: There are two threads I want to pull on, because I think you said many things that are super interesting. One is just how applicable a lot of what you’re piloting in age-friendly care is for anyone at any point in the lifespan.

And we know, and your work shows this, that when you focus on those most vulnerable populations and get it right in terms of optimizing them, it’s downstream so beneficial to others who may not necessarily see themselves as vulnerable or be in that sort of vulnerable category. So I think that point I really wanted to highlight that you made.

And then the second — I want to think about in primary care and in any type of medicine — we always say we don’t want to check for something unless we can intervene on it appropriately. So, if we identify that there’s a shift in gait or there is something that would benefit from early intervention with physical therapy and occupational therapy, where are you seeing the best practices? Where are you seeing this prescription for physical therapy happening earlier on? Can you point to some of those best practice examples?

Mate: Yeah, and I'll take them in order as you presented them. So the first one—yeah, you're absolutely right. I've been talking about this and thinking about this idea of what’s known as targeted universalism—having a universal goal. Everyone should age independently at home. A lot of people have that goal, but focusing on individuals who have the least opportunity to do that—and if you design for them, in theory, you would benefit everyone. You know, like the technologies and opportunities you would create would benefit everyone.

It’s a similar kind of concept, by the way, to going for the moon or going to Mars—the notion that, in the act of pursuing this kind of very difficult goal, you actually create technologies and opportunities that benefit a lot of people. Like, the microwave and radio and a whole lot of other things came out of our pursuit of the space program, which has nothing to do, in theory, with how I warm my food at night. But it turns out that those pursuits actually created ancillary benefits that have benefited millions—billions—of humans around the world.

That concept is, I think, very resonant here. So by focusing on aging and older adults—as I said, what matters, medication, mind, and mobility—all four of those concepts, and all of the innovations we’ve talked about in this program, not only benefit older adults but also benefit literally everyone, including kids and pediatric situations where we need to understand medications and a focus on mind is really important, etc.

Again, everyone benefits from a better appreciation of what matters to the patient or the family. So I think, in the end, this concept of targeted universalism is very resonant here.

Your second question, or thought around primary care and where this is actually taking place today—you know, as I said earlier, age-friendly health systems are now in over three to four thousand health systems around the country. If you’re an older adult listening to this, I would say: ask your provider today if they’re a practicing age-friendly health system. If they’re not, ask them to become one, because all these types of benefits that I’m describing here potentially would accrue to you.

As far as how these technologies are playing out—there are companies that are working on, for example, fall cameras, algorithmically enabled cameras that identify falls earlier. Several companies are now working on that—deploying them, I would say, in relatively small-scale pilots right now. Often in places like academic medical centers that are testing these things, trying to understand whether they’ll have the kind of effect that we want them to have. Assuming they do, we’ll see greater expansion of those ideas.

Medication technologies are much more widely distributed. So, the notion of smart pill dispensers and things like that—very widely distributed at this point, because they’re, in some ways, the previous generation of technology that’s being used. And there are lots of people trying to solve the problem of AI-enabled behavioral health services.

Again, I wouldn’t say that they’re ready—we wouldn’t advise anyone to think of them as being independently useful—but there are some technologies that are starting to become more useful at this point in time.

Pathak: So that’s really helpful in terms of just what is happening—what are real-life examples of how this technology is being utilized today—and what you’re anticipating as the next generation. Let’s talk about some of the concerns or challenges. I’m thinking here about cost, stable internet access, being comfortable with technology—you know, not pulling your hearing aids out so you can’t hear the alert. Can you talk to us a little bit about how some of these challenges are being addressed?

Mate: Yeah, I mean, you named, I think, probably the top two or three major concerns here. I’ll add one to that—apart from cost and digital divide and access-related concerns, I think the other challenge we’re trying to understand is trust. Fundamentally, whether people can trust these technologies.

Again, I don’t think there’s anything peculiar about older adults necessarily and their trust of these technologies, but I think in general, every generation—because of the pace of advancement of technology—has a different original exposure to it. My parents’ generation didn’t natively grow up with smartphones or the internet. I didn’t grow up with the internet as a young person. So, fundamentally, we each have different levels of comfort and trust in these technologies.

Every generation of technology essentially has to earn the trust of the people who are going to use it—and today’s AI is no different. It is very much still earning the trust of all of us, frankly, at this point in time.

By earning the trust, I don’t mean that everyone has to understand the minutiae and details of how ChatGPT actually functions. It’s a matter of understanding the outcome and whether there’s an external party helping to validate that outcome.

My analogy is: probably none of us really understand exactly how a pacemaker works, right? Or exactly how your antihypertensive medication works in your body. We trust that the regulatory agencies that have put in place frameworks around certifying those devices or medications will ensure that the people who make them produce them in a way that is safe for us to consume.

We are still articulating that for AI. There is not yet, I would argue, a comprehensive regulatory framework that fully enables us to have the same level of confidence and trust in some of the AI tools that I’ve been describing—or that you’ve been hearing about. There are obviously a lot of strong business reasons why we want AI to be trustworthy. But until we have that type of trust framework established, what we need to be doing is—at the prescriber level, at the health system level—putting in place safety, security, and ongoing monitoring guardrails that allow health systems using these technologies to distribute them safely, and to assure providers as well as patients that they are safe to use.

That’s the additional thing I would add. Cost is a very serious concern, although I would make the argument that the cost of technology is exponentially falling while capability is exponentially rising—it’s scaling logarithmically, not linearly.

For example, the cost to do a million chats is now a tenth or a hundredth of what it used to be when ChatGPT first released. So we’re seeing costs come down, which should make it more accessible to everyone.

Pathak: So let’s bring it back to the listener—the older adult, the caregiver who’s listening. What’s one simple piece of advice you have where they could start exploring AI tools for their health in their daily life?

Mate: I think the most widely distributed form of AI that’s available today is what’s already in your devices. It’s already on your phone. If you have one of those little speakers in your house—Alexa or Siri—try using those voice assistants.

Use them for basic health information. Use them to help prepare you for a visit—like, “I’m going to see the doctor for this condition; tell me what questions I should ask.” Write those questions down and then ask them. It’ll help you prepare for your interactions with healthcare providers.

Set medication reminders using those voice assistants. There are lots of things you can do with those assistants that are ultimately a form of AI. They’re not the most sophisticated form, but they’re a starting point that many people have access to today and can start to use.

Don’t put your personally identifiable health information in there yet—but get comfortable asking general questions about your medications or your health. Start using that to prepare yourself for interactions with the health system.

Start building that kind of digital confidence with the tools we have today. They’re well-vetted and well-tested, and at the very least, they can be a helpful assistant—which is exactly how you should think of AI in your life. It’s not replacing some basic function that you have; it’s just an intelligent assistant that’s trying to help you get the most out of your healthcare interactions.

Pathak: Looking ahead, what is exciting you the most about these AI-enabled tools?

Mate: I’m super excited about AI tools becoming a true partner in what it means to age well—understanding your individual unique patterns, predicting and anticipating your needs. What could be better than that? Keeping you connected to care, to members of your community, family, and friends—people who are going to check on you.

Hopefully, these tools will help you maintain independence as you age, which is a widely held goal for older adults. Hopefully, these tools will help maintain independence for longer—keeping families connected and informed.

I’ll add one last thing about mobility, which I didn’t say earlier: even tools like Uber or Lyft are actually helping older adults maintain their independence for longer. They don’t need to drive to appointments or visit friends or family. You can imagine how that could grow over time as we have more self-driving vehicles and other advances.

Helping that ability to maintain independence for longer is part of what I’m expecting or hoping out of the current generation of AI tools—and the potential to extend what people call healthspan. That’s what we’re working on at Qualidigm Health. That’s what a lot of people are working on in the AI world, and that’s what I hope for with AI becoming a true partner as all of us get older.

Pathak: This is such a great conversation. I’d love to spend the last few minutes handing it over to you. If you could close this episode by speaking directly to our audience and giving very concrete things they can think about doing in their life with their AI assistants.

Mate: Everyone has a story of someone that matters most to them as they age. I think about my parents now—or my grandmother before them—who did not have access to these technologies in their lives, and the challenges they faced as they got older. People didn’t understand what mattered to them or help them with some of the core things we talked about around mentation, medications, and mobility.

Today, the thing to do is try these technologies. They’re already in your life in some way. You have Alexa, Siri, or some other digital assistant on your phone or speaker at home. Use those devices, as I said earlier, to help you plan for your next health encounter. Get ready for your next doctor visit. Ask questions about your current condition. Try to help yourself become more educated about your health in some general way.

There are also ways to use these tools to start setting reminders for yourself—about when you’re supposed to do certain aspects of your care. Use the technologies you have to stay connected to your caregivers—they’re often using these technologies, whether they’re family members or providers. Use the tools we have in our lives to communicate and keep them connected to what you’re doing today.

Ultimately, the basic message I’d like to send is: test and try. That’s the primary message of all of this. These technologies are becoming much more available and less difficult to use. There’s actually a focus on older adults now—buttons are easier to read, they’re bigger, hearing assistance is being provided directly through these technologies.

So the whole idea that technology has to be scary or difficult to use doesn’t have to be true. Talk to your friends about it. Ultimately, technology can be fun—it can be a community activity, not just an individual sport. Use these technologies, try them, and talk to your friends about them.

Thank you so much for being with us today. We had an incredible conversation with Dr Kedar Mate, and the hope is that it offers you a new perspective on how technology can support—not replace—proactive healthcare.

Neha: There are a few takeaways that I’d like to highlight.

First, age-friendly care starts and ends with what matters. It’s not just about treating a condition or multiple conditions—it’s about aligning our healthcare with the goals that make life meaningful for us at any stage of our lifespan.

Second, medication management is a safety challenge for so many of us, but especially for older adults. There may be multiple confusing regimens, complex instructions, or potentially harmful interactions. Technology and AI have the potential to reduce and prevent errors, provide timely reminders, all with the goal to avoid hospital admissions and readmissions.

Third, these tools also have the potential to reduce isolation and provide cognitive support. While no one’s saying this replaces human interaction, mental health services, or in-real-life connection, these tools can serve as ancillary support that helps older adults stay connected and mentally engaged when alternatives aren’t available.

Fourth, we have smart technology that can support and track mobility goals and changes—often noting shifts in gait or balance, offering an opportunity to prevent falls and find support or physical therapy before an accident happens. As a primary care doctor, preventing a problem before it happens is so, so critical.

Finally, we acknowledged barriers to access, including everything from Wi-Fi and digital literacy to platform training and exposure to rapidly evolving tools. So many of us—whether we’re older adults or not—may be confused about how to use these tools, and Dr Mate really helped us understand that some of these tools are already in our pockets.

So whether you are an older adult, a caregiver, a clinician, or just someone thinking about your own future, the message is clear: the right tools, used the right way, can help us age safely, more independently, and more in line with what truly matters most to us.

To find out more information about Dr Kedar Mate and his work, check out our show notes.

This podcast miniseries is done in collaboration with The John A. Hartford Foundation. To check out more information about their work, make sure to check out our show notes.

Thank you so much for listening. Please take a moment to follow, rate, and review this podcast on your favorite listening platform. If you’d like to send me an email about topics you’re interested in or questions for future guests, please send a note to [email protected].

This is Dr Neha Pathak for the WebMD Health Discovered Podcast.