Ep 71: AI in Business – Healthcare Use Cases


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Technology is transforming industries at an unprecedented pace, and the healthcare sector is no exception. In a recent episode of the "Everyday AI" podcast, experts explored the potential of Artificial Intelligence (AI) in healthcare, uncovering various use cases that can revolutionize the way we deliver and receive medical services. As a business owner or decision maker, understanding these advancements presents a remarkable opportunity to enhance healthcare operations, improve patient experiences, and potentially save lives.

Overcoming Resistance:

Implementing new technologies in healthcare has historically faced resistance due to strict regulations and the experiences of burnout among healthcare providers. However, the episode highlights the evolving nature of technology and how humans have adapted to harness its potential. As a business owner, it is crucial to recognize that AI in healthcare is not a mere trend but a transformative force destined to reshape the industry.

Complex Adoption Process:

Integrating AI in healthcare comes with its own set of complexities. Compared to other fields, healthcare requires extensive training, workflow changes, and compliance with regulations such as HIPAA. Consequently, the adoption process may be more time-consuming and costly. However, the benefits of AI in healthcare far outweigh the challenges, as it allows for substantial improvements in patient care, diagnostic accuracy, and operational efficiency.

Enhancing Healthcare Operations:

One of the significant advantages of AI lies in its ability to analyze vast amounts of data and identify patterns. As mentioned in the podcast, AI can analyze electronic health records to pinpoint high-risk patients and shift medical practices from intervention to prevention. Furthermore, AI-powered chatbots can assist with appointment scheduling, enhancing the availability of specialists and boosting patient satisfaction.

Empowering Aging with AI:

The aging population presents unique challenges, and AI can play a pivotal role in addressing them. By leveraging AI monitoring systems, elderly individuals can age comfortably at home while receiving real-time health assessments. For example, AI algorithms can detect conditions such as diabetes or heart disease and ensure prompt medical attention is provided. This enhanced support system not only alleviates the burden on caregivers but also enables seniors to maintain their independence and well-being.

Centralized Data Centers:

In a fragmented US healthcare system, the consolidation of data from different health systems becomes a necessity. Insurance companies are working towards creating centralized data centers to facilitate access to critical data in emergencies and disasters. While challenges exist due to state laws, striking a balance between local autonomy and access to larger datasets holds immense potential, especially with the support of federal funding.


AI is poised to revolutionize the healthcare industry, offering unprecedented opportunities to improve patient outcomes and streamline operations. As a business owner or decision maker, staying informed about the potential of AI in healthcare is vital. Embracing these advancements not only benefits your organization but also contributes to the overall progression of the healthcare sector. By prioritizing user feedback, ensuring human oversight, and addressing ethical concerns, we can unlock the full potential of AI in healthcare and create a better future for all. Let us step forward into this transformative era and embrace the power of AI to revolutionize the world of healthcare.

Topics Covered

- Caring for aging individuals in their homes
    - Growing issue with the aging baby boomer population in the US.
    - Anticipation of integrating AI technologies for remote healthcare support.
- Future of personalized healthcare
    - Data monitoring and chatbots trained on personal data for treatment.
- Concerns about mistrust of AI and hallucinations
    - Inaccurate information provided by language models.
    - Need to address concerns as a society.
- Using chatbots to answer FAQs and provide personalized responses
    - Segmentation of patient population for targeted communication.
- AI to identify bottlenecks and improve staff utilization
    - Burnout as a significant problem in healthcare.
- Supercomputers for personalized treatments in cancer
    - DeepMind and IBM Watson using large data sets.
    - Collaboration between Regeneron Pharmaceuticals and Geisinger Health System for new drug development.
- Human oversight in advanced data analytics and AI
    - Human validation of recommendations.
- Concerns about data safety and third-party access
    - Importance of complying with HIPAA regulations

Podcast Transcript

Daily AI news

Jordan Wilson [00:00:18]:

How is AI going to change the health care industry? Well, there's probably a lot of ways, and that's one of the things that we're gonna be talking about today on everyday AI. This is your daily live stream podcast 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 new 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 gonna 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 it, he is still cautious about investing in the AI industry. 

alright. 2nd, Instagram, kind of a leaked memo just show that they will be warning users of AI content. So, this is, again, a leak documents. a leak document just kinda 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 gonna 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 gonna work, especially for text, but Instagram here, one of the first bigger companies, you know, kind of announcing this.

Alright. Last but not least and kind of relevant to our show today, Google and deepmind. So deep mind is kind of a Google's AI arm, so to speak, but they announced Med-PaLM. 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. Metpalm m is a new, multi model large language model. So that's a mouthful, but think ChatGPT for medical, that's Med-PaLM, and they just announced Med-PaLM, 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 Metpalm, 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 guests today, If you wanna know about AI and business and health care 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 Doctor Nadia Boutawi. she is the founder of Nanonares Inc and entrepreneurs for health care tech. Nadia, thank you for joining us.

Dr. Nadia Boutaoui [00:03:55]:

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

Jordan Wilson [00:04:04]:

It's that's something I I I love about, you know, kind of the everyday AI show is we have people not just, you know, even here as an example, we have, doctor Doctor Harvey Castro jump in the in the comments here saying glad to be here. He was on the show before. So, 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 typically with what's going on in the health care field, and AI because there's there's so much going on. What are your thoughts on some of these recent developments?

Dr. Nadia Boutaoui [00:04:38]:

I think AI is here to stay. It's not gonna replace humans, but a person who knows how to leverage AI. will replace somebody who doesn't. In the health care field, the Accenture, they estimate that AI applications can generate a $150,000,000,000 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 health care systems.

Jordan Wilson [00:05:19]:

Yeah. Abs. And and and that's even that right there. Right? I have I have friends and family who who who work, in health care 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 health care or, you know, large language models even, right, because from the patient side, 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.

How AI improves healthcare

Dr. Nadia Boutaoui [00:05:55]:

I think you you hit the nail on its, on its head here. I think AI can improve operations for, electronic health records with using large data analysis to have 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 So in the coming 6 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 a specialist, even before they get worse. So I think that's one potential application. Another one is for having chat box. is 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's 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.

AI's role in caring for aging people

Jordan Wilson [00:07:30]:

That's so important because, you know, it it is all a timing thing. Right? is. Yeah. And and and just just just real quick because I do wanna follow-up on that, but I do wanna shout out those of us, 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 every, all of them, but, if you do have a question for, Nadia about AI and health care, please drop it now. so so one thing that that you mentioned that I think is is going to be paramount, really, and and how we can actually use AI and all these, you know, advancements with large language models, but is is caring for the elder or not even I'm I'm not even gonna say the elderly. I'm gonna say aging. aging people in their homes, right, because that's that's a reality with the baby, at least here in the US. You know, we have the baby boomer population is aging, and that's gonna 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 2, there's gonna be, you know, options to, you know, you know, somehow integrate or chat with a 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, the very personal level of caring for an aging person versus these new tech technological advancements

Dr. Nadia Boutaoui [00:09:10]:

Yeah. I think I think the ed 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, love 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 2 the key is to keep these technologies accessible so that it will be used by these aging population. these chat boxes, chat box 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 there are 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 the device on your body to new technologies that are within both in smart homes. So they will monitor almost 247. And whenever there is a change in their patterns, it can directly, send the signal to their caregiver care health care provider to contact them. So I think that's the the 2 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.

Mistrust of AI in healthcare and hallucinations

Jordan Wilson [00:11:17]:

Yeah. So so what you talked about there, Nadia, for 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 health care and maybe almost like a a chatbot that's trained on your data to help treat you. Right? Mhmm. One thing that comes in my mind and, you know, Ben, here has a question as well, which I think is great, saying, is there a barrier or or sorry, a higher barrier in health care 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 health care, That's obviously something a lot of people are gonna be worried about. Like, what if my personal, you know, chat bot, 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.

Dr. Nadia Boutaoui [00:12:32]:

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 check by a physician or a trained professional before, given the get go for the treatment. that's one. The second is when it comes to, hallucination and 4th 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 identify the information and to have diversity within the development teams to 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 gonna be amplified. So having that diversity even in the development stage, and having a trained professional to, you know, valid to have the get go no go from that output is key.

Jordan Wilson [00:14:01]:

Yeah. And, you know, I was kind of thinking when you were talking there about just, privacy and data, and kind of kind of related, you know, and I think when people are hesitant, maybe, about AI or large language models in health care, 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 you know, is this, you know, is using large language models in health care 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 I I guess how different is it, or what other implications are there that maybe the 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.

Dr. Nadia Boutaoui [00:14:57]:

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 regulation, especially in in health care. So there's this resistance to, apply 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 health care providers. And if you're if for instance, your tech needs a 10 x to be adopted in a different field, it needs to be 50x in order to be adopted in workforce in health care because those, when you think about adoption, it's not just applying the the 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, health care is a little bit on the back and, they are not the early adopters of new technology because of that.

Jordan Wilson [00:16:13]:

Right. Which I guess, you know, makes sense, you know, because, you know, when you think about your add a in privacy. I think most people go to 2 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, 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 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 or or in the medical field. It's not always early adopters for tech. But what what else do you see happening? you you know, maybe 1st or next in in in your field.

How AI helps with chronic diseases, cancer, and new drugs

Dr. Nadia Boutaoui [00:17:14]:

Yeah. I think you 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 treatments 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 and Geisinger Health System. So a few years back, they sequence up to a quarter million people. They're 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.

Jordan Wilson [00:18:51]:

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 health care 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 practices or, you know, maybe they they work in a smaller healthcare system where maybe they have a little bit flexibility, to to 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 I I guess different aspects of GPT and AI technology that has you excited for growing things on the business side.

AI's role in healthcare customer service and burnout

Dr. Nadia Boutaoui [00:19:41]:

Absolutely. I think, they 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 will 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 by internal processes. find bottlenecks and use AI to relieve those bottlenecks. It will free up your time. It will increase the, utilization of your stuff. 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 a 150 in a different step of the process you can strategically move your staff around. It will help you with the retention. It will increase productivity. and it will reduce burnout for your staff. And we know it's a big problem across.

Jordan Wilson [00:21:08]:

Oh, abs absolutely. I think anyone who who has a a family member or friend in health care. 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. couple couple questions wanted to to get your thoughts on here, Nadia. So, Doctor Rostafa is asking, so, you know, will these systems that we put in place for privacy or discrimination, are they gonna 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, you know, putting these in place regionally? Will it be state laws? Will there be federal mandate you know, again, we can't ask you to to predict the future, but, you know, what do you think of this, this question from Doctor Rustify here?

Fragmented US health system

Dr. Nadia Boutaoui [00:21:58]:

That's a great point, a rough, a rough fight to our staff 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 to that. So I think having those centralized data centers either across that that cross state borders would be key. This will allow, for instance, in emergencies or pandemics or other, you know, disasters to get access to these data that could be critical in dispatching the different not remediation, but plans cross borders cross states. I agree that you know, there will be because of how the US is, so that 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 than datasets if needed, especially if it's funded by the, the, the federal government.

Jordan Wilson [00:23:27]:

Yeah. Yeah. It's that's gonna be an interesting one to see to see how it plays out, right, because we hear all of these advancements in technology and, you know, what we've talked about like burnout and it seems like a natural fit, but, you know, like you talked about, it's not simple to to implement these things. It's not a lot of systems they know that the value is in the data and they protect their data.

Dr. Nadia Boutaoui [00:23:50]:

Yeah. I'm not willing to share it with other people.

Jordan Wilson [00:23:53]:

Yeah. Absolutely. alright. 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, ChatGPT or maybe GPT companies, in health care that you can recommend. Yeah. So are there any, you know, we kinda talked about the deep mind and the poem M, but are there any other, you know, companies or entities that working on getting this thing that you talked about, this personalized chatbot, have you seen that yet, or is it still a while's off? I wouldn't recommend, like, one specific one.

Dr. Nadia Boutaoui [00:24:27]:

because I I wanna see how they evolve first, but I think between Amazon, between apple, who has, like, the monitoring even for your brainwaves and their air airpots, we will see more, like, health care related from the big tech giants. And we know health care is a difficult air area to get into. even when Amazon worked with, with the 2 other companies and they created Haven within 3 years. they dismantle it because it was so difficult. So that's why I'm hesitant to recommend one particular company because of the, the fragmentation in the system.

Jordan Wilson [00:25:10]:

Yeah. Yeah. That's that's a good point. And and even Apple. Yeah. I'm I'm excited to see what happens there too. You know, they've been, they tease kind of their Apple GPT and, like, you said, they've been saying that they wanna focus their AI on health care and wearables. So, yeah, so many things going on. So -- Exactly. And their Apple Watch monitors almost everything when it comes to, to health care, your heart rate, your walk, your patterns, and so on. So I think in the future, even if they are not doing it themselves,

Dr. Nadia Boutaoui [00:25:36]:

will have strategic partnerships

Jordan Wilson [00:25:38]:

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 health care is is exciting, but so much going on. So so thank you, doctor doctor Nadia Boutawi for joining us on the everyday AI show. We appreciate your time and insights.

Dr. Nadia Boutaoui [00:25:57]:

Absolutely. Thank you for having me. Thank you. Yeah. Thanks. Thank you for stopping by. And if you have questions, watching this on the recorded session,

Jordan Wilson [00:26:06]:

you can drop them in the comment, and I'll come back and answer them. Oh, that's true. Nadi is great at going through and and making sure and connecting with others. I think that's one thing that I I love about, everyday AI is just, you know, spurts that are going in and they're just helping people learn because we all have to learn together. So speaking, yeah, speaking of learning, make sure to check out our daily newsletter. So go right now and sign up at your everyday ai.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 gonna 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.

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