Ep 71: AI in Business - Healthcare Use Cases

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How is AI going to change the healthcare industry? Well, there's probably a lot of ways and that's one of the things that we're going to be talking about today on Everyday AI. This is your daily livestream, podcasts and free daily newsletter to help everyday people like you and me. Not just learn about what's going on in the world of AI because there's a lot, but how we can also leverage it. Right, because that's the important part. We can read all the news stories and look at all the new tools and techniques, but if we can't put it into use in our day to day lives and understand what it means, then we're just going to get left behind. So let's keep up together and let's first, before we bring on our guests and we talk AI and business and healthcare use cases, let me just remind everyone this is a live show, so if you have any questions, please drop them. But before we get to that, let's first talk about what's going on in the world of AI news. So Warren Buffett came out and said that unlike just about everyone else, he's not all in on AI as an investment yet. So we talked about this earlier, but how just kind of the AI related companies are really driving the US stock market. And you know, Warren Buff, the esteemed investor, essentially said even though he's amazed by ChatGPT, he is still cautious about investing in the AI industry. All right, second, Instagram kind of a leaked memo just showed that they will be warning users of AI content. So this is again a leaked document. A leaked document just kind of came out and it shows that they're testing labels to warn users if the, if the content generate was either generated with or edited via AI. So that one's going to be interesting just to see how they even label it, how they warn other users. But I think that signals a bigger shift, right? I think we're going to start to see this a lot, especially with images, video and audio. I don't know how it's going to work, especially for text. But Instagram here, one of the first bigger companies, you know, kind of announcing this. All right, last but not least and kind of relevant to our show today, Google and DeepMind. So DeepMind is kind of Google's AI arm, so to speak, but they announced Med Palm M. So we've talked about Med Palm on the show before, but without getting too technical, but we'll actually dive into it maybe a little bit today. MedPalm is a new multimodel large language model. So that's a mouthful, but think chat GPT for medical, that's Med Palm and they just announced Med Palm M, which is multimodal. So what that means is, you know, the ability to process text images and even genomes. So wild.

Right.

So, you know, this new MedPalm M will be able to encode and interpret biomedical data. Very exciting things happening in the, in the medical field with AI. So speaking of that, let's talk that. And we already have a lot of comments coming in. Fantastic. So as a reminder, if you have questions for our guest today, if you want to know about AI in business and healthcare use cases, please drop a comment. But very excited to bring on our guest for today. So maybe you've seen her in the comments for the Everyday AI show before. Maybe not. But regardless, very excited to bring on Dr. Nadia Butawi. She is the founder of Nano Nairs Inc. And entrepreneurs for healthcare tech. Nadia, thank you for joining us.

Absolutely. Very happy to be here to move from the comment into the stage with you.

Yeah, absolutely. That's something I love about the Everyday AI show is we have people, not just even here as an example, we have Dr. Harvey Castro jumping in the comments here saying, glad to be here. He was on the show before. You know, Nadia, there's a lot of things going on in the AI world, right. It's, it's kind of hard to keep up even on a daily show. Right. What are your thoughts specifically with what's going on in the healthcare field and AI? Because there's, there's so much going on. What are your thoughts on some of these recent developments?

I think AI is here to stay. It's not going to replace humans, but a person who knows how to leverage AI will replace somebody who doesn't. In the healthcare field. The Accenture, they estimate that AI applications can generate $150 billion in annual saving for the US health system. So that's huge. Especially that the US health system is among the most expensive in the world. So there are so many areas that, where AI can bring value, not only improving the outcomes and also improving efficiencies for the healthcare systems.

Yeah, absolutely. And that's even that right there. Right. I have friends and family who work in healthcare, and efficiency always seems to be one of those major words that comes up, you know, when we talk about how can AI help in healthcare or, you know, large language models even. Right. Because from the patient side, you, you know, one thing I think we always talk about is, hey, it's so hard to get in to see my primary care doctor or to schedule a time with a specialist. So how do you see that improving in your field, even for, for, you know, I guess the, on the patient.

Side, I think you hit the nail on it on its head here. I think AI can improve operations for electronic health records with using large data analysis to help the medical professionals identify the high risk patients and move from intervention medicine into prevention. So if somebody is flagged for some reason that they may have an asthma episode in the coming six months, instead of doing the intervention, when they show up in the er, they can be flagged to see their pcp, the primary care physician, or even the specialist even before they get worse. So I think that's one potential application. Another one is for having chat boxes that can help with scheduling and removing that friction of availability to of the specialists that we know. They are very tight on time so they can better manage the delivery as well as the satisfaction for the, for the patient. Another one, a lot of people, especially in the US There is an aging population and they would love to age in their homes instead of, you know, in other facilities. And having those monitoring over time can help identify almost in real time their conditions, especially chronic conditions such as diabetes, heart disease and so on, so they can get the care they need before it's too late.

That's so important because it is all a timing thing, right? Yeah. And just real quick because I do want to follow up on that, but I do want to shout out those of you joining live. So thank you, Juliet, for joining us from Connecticut. Carlos tuning in from Spain. Thank you. Carlos Ellington. Wow, so many people this morning, Woozy from Kansas City. Lynette, thank you. I can't get to all of them, but if you do have a question for Nadia about AI and healthcare, please drop it now. So one thing that you mentioned that I think is going to be paramount really in how we can actually use AI and all these advancements with large language models, but is caring for the elder, I'm not even going to say the elderly. I'm going to say aging, aging people in their homes. Right. Because that's, that's a reality with the baby. At least here in the U.S. you know, we have the baby boomer population is aging and that's going to be a huge issue. So how do you, I guess, what would be your recommendation to People maybe who are starting to look for those options. And now you see all these advancements in AI and I'm sure in the next year or two there's going to be, you know, options to somehow integrate or chat with a doctor like that to be able to care for your elderly in the home. So how do you see that playing out and what advice can you give to people to balance the, I guess the very personal level of caring for an aging person versus these new technological advancements?

Yeah, I think the AI powered virtual assistants and chat boxes, they will become the norm in the future where patient, they will have their own virtual assistant to track that is trained on their data, on their history, on their genome, so they can track their blood pressure, you know, sugar levels and so on. And they can give them almost feedback instantly whether to flag it in a way that you may need to see your PCP in the coming, you know, week or two. The key is to keep this technologies accessible so that it will be used by these aging population. These chat boxes, all chatbots also they can support and ask the questions about their medication. Medication compliance is also an issue. Many people, especially with chronic conditions, they, they don't, you know, adhere to their medication regimen. So they can help them with, you know, potential side effect if they are on multiple drugs. So that can prevent an adverse, adverse effect for these aging population. They also can help them with streamline their appointments and their care. So I think another, another one in terms of wearables and so on. We will move from the wearable technologies where you have a device on your body to technologies that are within walls in smart homes. So, so they will monitor almost 24, 7 and whenever there is a change in their patterns, it can directly send a signal to their healthcare provider to contact them. So I think that's the two main applications I see the key for technology is get feedback from the users that are going to use your technology. So it's based on the problem they experience, not your assumption of the problem they have.

Yeah, so, so what you talked about there Nadia, for someone like me, you know, I'm a, I'm a self admitted dork. I love AI, I love data, but that's not the case for everyone. Right. So when we talk about that future, right, where it is, you know, your data is being monitored and you're able to have much more personalized healthcare and maybe almost like a chatbot that's trained on your data to help treat you. Right. One thing that comes in my mind and Ben here has a Question as well, which I think is great saying, is there a barrier or, sorry, a higher barrier in healthcare to overcome mistrust of AI and hallucinations. Right. Because for anyone out there who has used a lot of large language models, hallucinations are a problem where essentially you get inaccurate or just straight wrong information. So you know, when we talk about that application in healthcare, that's obviously something a lot of people are going to be worried about. Like what if my personal, you know, chatbot that's trained on my health data gives me wrong information? Like how can we address that just as society? And you know, because it's exciting to think about but obviously, you know, big, big things to, to take into consideration.

That's a great question. Thank you, Ben. I believe that for any advanced data analytics tool or AI, there should be some human oversight. So whatever the recommendations that gives you, it's not, it will be run, checked by a physician or a trained professional before giving the get go for the treatment. That's one. The second is when it comes to hallucination and for chat boxes especially, I think having that human oversight will mitigate that. The second thing that a lot of people worry about is the safety of their data for especially, you know, could it be accessed by a third party, especially with hipaa. I think it's very important to de. Identify the information and, and to have diversity within the development teams to avoid biases. Because we know if these chat boxes or these AI models are trained on existing data that may have embedded biases, it's going to be amplified. So having that diversity even in the development stage and having a trained professional to have the go, no go from that output is key.

Yeah. And I was kind of thinking when you were talking there about just privacy and data and kind of related and I think when people are hesitant maybe about AI or large language models in healthcare, I think so many times when I'm seeing my primary care physician or something, that person is then just turning around and googling something. A lot of times. Right. So even with that, you know, is this, you know, is using large language models in healthcare that big of a step forward? If you know, so many times, you know, physicians, you know, nurses are just turning to the Internet anyway, so I guess how different is it or what other implications are there that maybe the average, you know, patient may not be aware of? You know, when starting to think of a future of more large language models in healthcare, Are you still running in.

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I think, I think technology is here to stay. And as humans we've evolved to adapt to new technologies. In some cases there are tight regulations, especially in, in healthcare. So there's this resistance to applying or you know, the, these new tech in, in their workflows. And it's a very, not only the regulation, but the burnout is real when it comes to healthcare providers. And if for instance, your tech needs a 10x to be adopted in a different field, it needs to be 50x in order to be adopted in workflows in healthcare. Because those, when you think about adoption, it's not just applying that technology, it's training the personnel, changing the workflows. So the cost of acquisition is not just that. Purchase, initial price, the service, maintenance, the safety, the HIPAA compliance, the regulation, it's way more complex. And because of that, healthcare is a little bit on the back end. They are not the early adopters of new technology because of that.

Right. Which I guess, you know, makes sense, you know, because you know, when you think about your data and privacy, I think most people go to two things. They go to their personal health information and they go to their money. Right. Which is maybe why we've seen maybe faster implementation in other sectors versus you know, some, some areas in finance and, and just medicine in general. So you know, you mentioned appointment scheduling is maybe one area that is I guess ripe for some, some innovation, what other? So whether it's, it's on the physician side, you know, aspects of this new technology that may help physicians or even just the relationship on the patient side. What areas do you Think given what you just said about how, you know, in, in medicine or in the medical field, it's not always early adopters for tech. But what, what else do you see happening, you know, maybe first or next in, in, in your field?

Yeah, I think you meant, you mentioned DeepMind by Google. There's also IBM, Watson. So supercomputers are using very large data sets to do predictions for chronic diseases. Personalized treatment for cancer treatments, that's another area that we'll see a lot of advancement. And cancer research and personalized medicine in cancer treatment is generally at the forefront of innovation compared to other areas. So I see there will be a lot in that area also when it comes to combining genomics and electronic medical records to create new drugs. One example that come to mind is a collaboration between Regeneron Pharmaceuticals and Geisinger Health System. So few years back they sequenced up to a quarter million people, their whole genome and the health system had the electronic medical records for years in that region. And that allowed with the large, large data analysis to find druggable targets for new drug development. So I see a lot of that also moving forward. Collaborations to create more personalized drugs for specific populations. Because we know what's on the market now was largely developed on white populations and it doesn't work as well for African Americans or other ethnic groups. So we'll see more development in that area too.

Yeah, and I do think that that piece is exciting. I think it's much needed. So, you know, one, one other question that I had for you, Nadia, is, you know, we've talked about different applications in the, in the healthcare field. You know, like medical technology, like personalized medicine, so many things. But I know that you also have use cases on the business side as well. So, you know, maybe I actually know that we, we have some listeners who have their own pract. You know, maybe they, they work in a smaller healthcare system where maybe they have a little bit more flexibility to grow their business. But even on the business side, you know, real quick, maybe what are some of your, maybe personal use cases or I guess different aspects of GPT and AI technology that has you excited for growing things on the business side?

Absolutely. I think you can create chat boxes to answer FAQs based on your data instead of going to the Internet. This way it's personalized to the people you serve. It's based on feedback from the patients you serve. So that would be one application. Another application is segmentation of your patient population. This way when you create, let's say leaflets, if you're serving a Latino population, it will take into account their culture, the, the language that they, that would resonate the most with them. So having that personalized communication in medicine is critical processes look at your supply, your not supply chain from like the get go, but internal processes find bottlenecks and use AI to relieve those bottlenecks. It will free up your time, it will increase the utilization of your staff. So if you have a bottleneck and you know that you get only 50% of usability out of, you know, a nurse or a PA or so on, and 150 in a different step of the process, you can strategically move your staff around. It will help you with retention, it will increase productivity and it will reduce burnout for your staff. And we know it's a big problem across.

Oh Abs. Absolutely. I think anyone who, who has a family member or friend in healthcare, I think burnout is usually one of the first things that comes up.

Right.

And I think that the AI technology is hopefully something that can, that can help in that. A couple questions wanted to get your thoughts on here, Nadia. So Dr. Rastafa is asking, so you know, will these systems that we put in place for privacy or discrimination, are they going to vary with the political landscape? You know that, that is an important question. It's like also how can these things even roll out, right. Will it be the hospital systems putting these in place regionally? Will it be state laws? Will there be federal mandates? Again, we can't ask you to predict the future, but what do you think of this question from Dr. Rastafa here?

That's a great point because the health system in the US is very fragmented by state, by health systems and so on. The insurance companies, I think are seeing the value in congregating large data sets from different health systems and they're working actively to put all data in one big place. And then different health systems across states can have access to that. So I think having those centralized data centers, either that cross state borders would be key. This will allow, for instance in emergencies or pandemics or other disasters to get access to these data. That could be critical in dispatching the different, not remediations, but plans. Cross borders, cross states. I agree that, you know, there will be because of how the US is set up, that each state will have their own, you know, laws. But again, I think it's a combination of having local autonomy versus having access to larger data sets if needed, especially if it's funded by the federal government.

Yeah, that's going to be an interesting one. To see how it plays out because we hear all of these advancements in technology and what we've talked about like burnout and it seems like a natural fit but like you talked about, it's not that simple to implement these things.

A lot of systems, they know that the value is in the data and they protect, protect their data.

Yeah.

Not willing to share it with other people.

Yeah, absolutely. All right. And I think, I think to wrap up, we have one last question here from, from Harvey Castro saying do you know. So specific question here but asking if you know of any specific, you know, chat GPT or maybe GPT companies in healthcare that you can recommend. Yeah. So are there any, you know, we kind of Talked about the DeepMind and the Palm M, but are there any other, you know, companies or entities that are working on getting this thing that you talked about, this personalized chatbot? Have you seen that yet or is it still a whiles off?

I wouldn't recommend like one specific one because I want to see how they evolve first. But I think between Amazon, between Apple who has like the monitoring even for your brain waves in their AirPods, we will see more like health care related from the big tech giants and we know healthcare is a difficult area to get into. Even when Amazon worked with two other companies and they created Haven within three years they dismantled it because it was so difficult. So that's why I'm hesitant to recommend one particular company because of the fragmentation in the system.

Yeah, yeah, that's a good point. And even Apple. Yeah, I'm excited to see what happens there too. You know, they tease kind of their Apple garbage GPT and like you said, they've been saying that they want to focus their AI on healthcare and wearables. So yeah, so many things going on, so Exactly.

And their Apple watch monitors almost everything when it comes to, to healthcare. Your heart rate, you walk, your patterns and so on. So I think in the future, even if they are not doing it themselves, they will have strategic partnerships with other people that do.

Yeah, absolutely. I think, I think you hit it. Hit it.

Right?

You know, there's so much data out there and I think the future of healthcare is kind of exciting, but so much going on. Thank you Dr. Nadia Butawi for joining us on the Everyday AI Show. We appreciate your time and insights.

Absolutely. Thank you for having me. All right, thanks everybody for stopping by. And if you have questions watching this on the recorded session, you can drop them in the comment and I'll come back and answer them.

Oh, that's true. Nadia is great at going through and making sure and connecting with others. I think that's one thing that I love about Everyday AI is just experts that are going in and they're just helping people learn because we all have to learn together. Speaking of learning, make sure to check out our daily newsletter. So go right now and sign up@youreverydayai.com. so Nadia has actually other resources we didn't even have time to talk about some exciting initiatives that she's working on. We're going to be sharing about those in the newsletter, breaking down today's conversation even more. So thank you everyone for joining us and we hope to see you back tomorrow and every day with Everyday AI. Thanks.

Thank you everyone. Thanks a lot.

And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going for a little more AI magic. Visit youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.