A hospital in the cloud bringing health care anywhere in the world | Mohamed Aburawi

0:06You're listening to TED Talks Daily, where we bring you new ideas to spark your curiosity every day. I'm your host, Elise Hu. Today's talk is from our brand new batch of 2024 TED Fellows films, adapted for podcasts just for our TED Talks daily listeners. TED's fellowship supports a network of global innovators, and we're so excited to share their work with you. Today, we'd like you to meet mental health systems entrepreneur Mohamed Abouraoui. So many people living in conflict zones who need healthcare have to cross borders to receive the medical treatments they need. Mohamed shares a solution he has found with AI to bridge this healthcare gap.

0:42and improve the quality of care for so many people around the globe. After you hear from him, stick around for his conversation with TED Fellows Program Director, Lily James Olds.

0:57This is a picture from the Libyan-Tunisian borders. These are patients who couldn't find care within their own country. These ambulance cars carried my father, my grandma, before she passed away. and for me this is emblematic of the challenge we're currently facing. We see a significant number of patients seeking care beyond their borders and they should get care within their community. Currently it's very difficult to do that just by training more doctors and building more medical schools or hospitals because we will never be able to reach everyone everywhere. But if there was an AI doctor that can be with them and have the answers whenever they need them and where they need them, and having those answers being contextualized for that specific patient in that village, we would not see such dire consequences of years of underinvestment in health.

1:59I'm Mohamed Abrawi, a surgeon, and I have the privilege of leading our team at SPITAR, a digital health platform that connects patients in remote communities across the Middle East and Africa to physicians that understand their context, language, and are able to help them best. It's basically a hospital in the cloud.

2:24This folder is how health records are kept in Libya. This file can hold so much in terms of documentation. patient and even then it's very rare that you'll find a patient that will come to you with a file that has everything from their past history that they've kept perfectly neat together for you just to kind of go through as opposed to when I was working for example in one of the leading institutions in the US I can just ask for patient's name, date of birth, log in, get every single procedure that performed in the past 15 years. Because of the lack of digitization in these areas where we have ongoing volatility, a patient may be in one village today, tomorrow you will have conflict and they're in another one.

3:08And people don't really leave or migrate with their files in their packpacks, like, oh, my health records. So you'll lose that. And you'll lose every single allergy, procedure, medical problem, medication that they've had. And you're constantly building that record from scratch. So essentially what we do is help patients capture their medical histories in a digital format. And then we make sure that that record is available at their fingertips, in their phones, but also available for the doctors. And we continue to build on that record to make sure that that patients get the best care possible whenever they need it.

3:49And that's kind of the capturing side of things, the capturing the data. And from there, we start to work on cleaning that data up and making sure it's consistent. And it could be fed into models that could later on start to kind of give these predictive analytics. But what we see with AI or this data economy in general is unfortunately a similar trend we've seen in the past with colonial powers, where now data is the new oil. There is a movement to capture as much data as possible and for this data to be fed into the AI models that are currently being developed. And it's being fed the data that exists in mostly the Western world, where it's readily accessible, where you have electronic medical records.

4:37But when you look at certain villages in Libya or other countries which are suffering now, going through conflict, or have been historically kind of marginalized and underserved. There is not that attention to collecting data. We are not including the full spectrum of humanity. As we continue to build AI, we need to involve other countries in that data collection process and not just assume that we can build a technology in the West and just parachute in. And because it's a medical AI, it will work perfectly there. It will not work. I hope it's a future where patients do not have to leave their countries or wait for months, sometimes even years, to get the proper care that they need.

5:24The writer William Gibson once said, the future is already here, it's just not evenly distributed. AI has the power to really make sure that quality of care is evenly distributed to everyone everywhere.

5:43And now a special conversation between TED Fellow Mohamed Aburrahi and TED Fellows Program Director, Lily James Olds. Mohamed, welcome. So excited to talk to you today. Thank you so much. Excited to be with you. So what you and your team are doing is just one example, obviously, of the exponential transformations that are taking place in healthcare with the technology of AI. Can you tell us more specifically how exactly Spiritar works for patients seeking care? You know, growing up in Libya, I saw what it meant for someone to travel for hours or even days just to get a diagnosis. It sticks with you.

6:26Seeing the frustration of someone holding on to a prescription they can't even fill. That's the human story, I guess, behind the work I do. and our goal is to make sure that care doesn't just exist, it reaches the people who need it, when they need it and in the way they can trust. So for patients, our technology acts as a bridge. So I would say imagine a woman in a rural village in Libya would be experiencing a chest pain. She opens her phone, describes her symptoms and within minutes she's connected to a care pathway. whether that's a virtual consultation, a nearby clinic, or advice tailored to her condition.

7:12No unnecessary delays, no guesswork. It's a system that works in the background, but the results feels like magic. But this goes beyond convenience. It's about justice. I think as we approach the next decade with nearly half of the world's population lacking basic health care, their stakes could not be higher. Absolutely. And I think for so many of us, the place our minds immediately go with AI assisting with anything is obviously safety. How does Spiritar protect its patients and their data? Well, let me, I guess, paint a picture here. Imagine you're in a restaurant and the waiter writes down your order on a napkin.

8:03That's basically how some systems treat your medical data. Unsecured, unregulated, and all too easy to misuse. That's unacceptable. We treat data like it's sacred because it is. On a human level, we ask the question, if this was my mother's medical history, would I feel comfortable with how it's being handled? And if the answer is anything less than a firm yes, we go back and rework the whole system. But data safety isn't just about protection. It's also about inclusion. And that's kind of what we try to keep in mind as we operate and build these solutions. I love that you give the example that others have brought up of data really being the new oil in the data economy.

8:57and you speak about how important it is that we're including the full spectrum of humanity in these data sets that AI models are built on. How do you think we do this? I think the example you just gave with your company is apt, right? How do we also make sure that these AI frameworks models are really built on ethical human frameworks? I think this is where we have to confront some of the uncomfortable truths. historically, a lot of AI models were built on data sets that didn't reflect the world's diversity. It's like trying to write a universal cookbook, but only testing recipes on one kind of cuisine.

9:44You miss the full spectrum of flavors. There's all tools that work well in Boston, but fail spectacularly in Tripoli. AI datasets and language models, they're rapidly developed now and will be the foundation for the tools we produce and use far into the future. And we must ensure these systems are inclusive, ethically sourced, and built on local ownership. Otherwise, we risk codifying inequalities we see today into the tools of tomorrow. In many ways, the global healthcare crisis is fueled by information inaccessibility. And fixing that starts with digitizing the lived experiences of billions of people who have been invisible for current systems and for a long time.

10:48And what does the integration of advanced technologies in healthcare mean for global health, particularly in underserved regions? I think this is where the conversation gets really exciting and urgent. Advanced technologies like AI don't just promise to improve healthcare in well-resourced settings. They have the potential to completely redefine what's possible in places that historically have been left behind. For example, we face a global deficiency of nearly 18 million healthcare workers today. most acutely felt in low and middle income countries. Technology can't replace human expertise, but it can help amplify it.

11:38A single radiologist, for example, can't be in 10 places at once. But an AI-powered diagnostic tool can extend their expertise to clinics in rural Kenya, Bangladesh, or Libya, places where radiologists may not even exist. I think the real power of AI is in the ability to leapfrog. Many underserved regions don't have the legacy healthcare infrastructure we see in wealthier countries, and that can actually be an advantage. They can basically bypass outdated systems and adopt leaner tech-driven models, but the stakes couldn't be higher. I believe if we don't act now, we risk creating tools that serve the privileged few while leaving billions behind.

12:33As one of my mentors once said, the goal isn't just to innovate, it's to include. I love that. Yeah, and there's so much possibility. So I guess it's continuously, as everybody is now, trying to weigh those balances of the possibilities that are about to be unlocked and also being very mindful of the dangers and the challenges. I'm curious, how can providers and patients welcome seamlessly this new technology into their practices? And what are some of the challenges? You've touched on a few of them, but that you see in that process. Well, let me start with a story. A doctor I know, brilliant, old school, you know the type.

13:18He once told me, AI is great, but can it sit next to a patient and hold their hand? And he's right. Technology isn't here to replace the connection that humans have. It's here to enhance it. And for providers, it's about showing them that these tools aren't a competition. They are collaborators, basically. They reduce the administrative burden, speed up diagnosis, and let clinicians focus on what they do best, which is caring for people. On the other hand, for patients, I think they don't need to learn the technology. They just need to trust it. And that's the real hurdle, trust. I think that's so true.

14:12And I think one of the things I'd love to hear you speak a little bit more in depth about as well is, you know, there's many telehealth apps and companies. But I think that your approach with SpearTar is specific because it is so culturally attuned to the different regions, languages, cultures. Can you speak a little bit about that and how you think SpearTar is really welcoming in a kind of new era of this telehealth? I think with many of the solutions out there, it's important to keep in mind that we're not just kind of building new technology, we're making sure that it's inclusive. And what that means is we're really building not just for the communities, but with them and ensuring local ownership, as I mentioned, because many times that gets overlooked.

15:02especially when we talk about medicine, we assume that because we're talking about the human body, because the human physiology and anatomy is the same, we tend to kind of sideline these nuances. And it is very important to take that in consideration from an early stage as we build these solutions to make sure that they are relevant for some of the contexts that they're deployed to. It's really fascinating work. Thank you for this, Mohamed. My last question would just be if someone is interested in diving deeper on some of the things we touched on. I'm curious what resources you'd recommend that have been useful to you in terms of a book, a podcast, or anything else.

15:43I think for a thought-provoking read, Deep Mind by Eric Topol is a great place to start. It's like a level of effort to the future of healthcare. But honestly, I think the best resources curiosity. Ask questions. Challenge assumptions. If you hear about a new breakthrough in AI, don't just say, wow, cool. Think, what's the impact? Who benefits? Who doesn't? And I think that's where the relearning happens. But if I would just kind of add a final thought here. At its core, the story of AI in healthcare is a story of our humanity, our ingenuity, our resilience, and honestly, our shared commitment to a better future.

16:35I love that. Thank you, Mohamed. Thanks.

16:52at theclose.ted.com. And that's it for today. TED Talks Daily is part of the TED Audio Collective. This episode was produced and edited by our team, Martha Estefanos, Oliver Friedman, Brian Green, Autumn Thompson, and Alejandra Salazar. It was mixed by Christopher Faze Bogan. Additional support from Emma Taubner and Daniela Balarezo. I'm Elise Hu. I'll be back tomorrow with a fresh idea for your feet. Thanks for listening.

17:22Thank you.