 Hey, everyone, welcome back to theCUBE's day-long coverage of Women in Data Science 2023. Live from Stanford University, I'm Lisa Martin. We've had some amazing conversations today with my wonderful co-host, as you've seen. Tracy Jung joins me next for a very interesting and inspiring conversation. I know we've been bringing them to you, we're bringing you another one here. Dr. Irene Dankwimolen joins us, the chief medical officer at Marty Health and a speaker at Woods. Welcome, Irene, it's great to have you. Thank you, I'm delighted to be here. Thank you so much for this opportunity. So you have an MD and a master of public health. COVID must have been an interesting time for you with an MPH. Very much so. Yeah, talk a little bit about you, your background and Marty Health, this is interesting, this is a brand new startup. This is a digital health equity startup. Yes, yes. So I'll tell you, I'll start with my story a little bit about myself. So I was actually born in Ghana. I finished high school there and came here for college. What would I say, after I finished my undergraduate, I went to medical school at Dartmouth. And I always knew I wanted to go into public health as well as medicine. So my medical education was actually five years. I did the MPH and my medical degree. At the same time, I got my MPH from Yale, School of Public Health. And after I finished, I trained in internal medicine at Johns Hopkins. And after that, I went into public health. I am currently living in Maryland, so I'm in Bethesda, Maryland, and that's where I've been. And really enjoyed public health, community health, combining that aspect of prevention and wellness and also working in making sure that we have community health clinics and safety net clinics. So great experience there. I also had the privilege of, after eight years in public health, I went to the National Institutes of Health. Oh, wow. Where I basically worked in clinical research, basically on minority health and health disparities. So I was in various leadership roles and helped to advance the science of health equity, working in collaboration with a lot of scientists and researchers at the NIH, really to advance the science. Where did your interest in health equity come from? Was there a defining moment when you were younger and you thought, there's a lot of inequities here. We have to do something about this. Where did that interest start? That's a great question. I think this influence was basically maybe from my upbringing as well as my family and also what I saw around me in Ghana, a lot of preventable diseases. I always say that my grandfather on my father's side was a great influence, inspired me and influenced my career because he was the only sibling, really, that went to school. And as a result, he was able to earn enough money and built a hospital in the hometown. It started as a 20-bed hospital and now it's a 350-bed hospital in our hometown. He knew that education was important and vital as well for well-being. And so he really inspired, you know, his work inspired me. And I remember in residency, I went with a group of residents to this hospital in Ghana just to help over a summer break. So during a summer where we went and helped take care of the sick patients and actually learned what it is like to care for so many patients. And it was really a humbling experience. But that really inspired me. I think also being in this country and when I came to the US and really saw fast-hand how patients are treated differently based on their background or socioeconomic status, I did see firsthand that kind of unconscious bias and drew me to the field of health disparities research and wanted to learn more and do more and contribute. Yeah, so I was curious just when the data science aspect taps in, like, what did you decide that, okay, data science is going to be a problem-solving tool to all the problems you just said? Yeah, that's a good question. So while I was at the NIH, I spent eight years there and precision medicine was launched at that time and there was a lot of heightened interest in big data and how big data could help really revolutionize medicine and health care. And I got the opportunity to go to, there was an opportunity where they were looking for physicians or deputy chief health officer at IBM. And so I went to IBM, Watson Health was being formed as a new business unit and I was one of the first deputy chief health officers really to lead the data and the science evidence. And that's where I realized we could really, the technology and health care has really, there's been a lot of data that I think we're not really using or optimizing to make sure that we're taking care of our patients. And so that's how I got into data science and making sure that we are building technologies, using the right data to advance health equity. Right, so talk a little bit about health equity. We mentioned you're with Marty Health, you've been there for a short time, but Marty Health is also quite new, just a few months old, digital health equity. Talk about what Marty's vision is, what its mission is to really help start dialing down a lot of the disparities that you talked about that you see every day. Yeah, so I've been so privileged. I recently joined Marty Health as their chief medical officer, chief health officer. It's a startup that is actually trying to promote a value-based care, also promote patient-centered care for patients that are experiencing a social disadvantage as a result of their race, ethnicity. And we're starting to look at focused on patients that have sickle cell disease. Okay. Because we realize that that's a population. You know, we know sickle cell disease is a genetic disorder. It impacts a lot of patients that are from, and areas that are endemic malaria. Yeah. And most of our patients here are African-American. And when, you know, they suffer so much stigma and discrimination in the healthcare system and complications from this sickle cell disease. And so what we want to do that we feel like sickle cell is a litmus test for disparities. And we want to make sure that they get in patient-centered care. We want to make sure that we're leveraging data and the research that we've done in sickle cell disease, especially on the continent of Africa, and provide, promote better care, quality care for the patients. That's so inspiring. You know, we've heard so many great stories today. Were you able to watch the keynote this morning? Yes. I loved how it always inspires me. This conference is always, we were talking about this all day, how you walk in the Ariaga Alumni Center here where this event is held every year. And the vibe is powerful, it's positive, it's encouraging, it's a community. It's inspiring for you. It's inspiring. It's a movement, WIDS is a movement. They've created this community where you feel, I don't know, kind of superhuman. Why can't I do this? Why not me? We heard some great stories this morning about data science in terms of applications. You have a great application in terms of health equity. We heard about it in police violence, which is an epidemic in this country for sure, as we know, this happens too often. How can we use data and data science as a facilitator of learning more about that so that that can stop? I think that's so important for more people to understand all of the broad applications of data science, whether it's police violence or climate change or drug discovery or health inequities. And health, yeah. The potential, I think we're scratching the surface, but the potential is massive. It is. This is an event that really helps women and underrepresented minorities think, why not me? Why can't I get involved in that? Yeah, and I always say we use data to make a lot of decisions. And especially in healthcare, we want to be careful about how we are using data because this is impacting the health and outcomes of our patients. And so science evidence is really critical. You know, we want to make sure that data is inclusive and we have quality data. And it's transparent. Our clinical trials, I always say, are not always diverse and inclusive. And if that's going to form the evidence base or data points, then we're doing more harm than good for our patients. And so data science, it's huge. I mean, we need a robust, responsible, trustworthy data science agenda. Trust, you just brought up trust. When we talk about data, we can't not talk about security and privacy and ethics, but trust is table stakes. We have to be able to evaluate the data and trust in it and what it says and the story that can be told from it. So that trust factor is, I think, foundational to data science. We'll see what happened with COVID, right? I mean, when the pandemic came out, everyone, I mean, wanted information. We wanted data. We could trust. There was a lot of hesitancy even with the vaccine, right? And so public health, I mean, like you said, we had to do a lot of work making sure that the right information from the right data was being translated or conveyed to the communities. And so you're totally right. I mean, data is and good information, relevant data is always key. Is there anything else? Oh, sorry. Is there anything Marty House is doing in ensuring that you guys get the right data that you can put trust in it? Yeah, absolutely. And so this is where we are, part of it would be getting data, real world evidence data for patients who are being seen in the healthcare system with sickle cell disease so that we can personalize the data to those patients and provide them with the right treatment, the right intervention that they need. And so part of it would be doing predictive modeling on some of the data, stratifying risk who in the sickle cell patient population is at risk of progressing or getting, they all often get crisis, vasoclusive crisis because there's cells, the blood cell sickles and you want to avoid those chest crisis. And so part of what we'll be doing is doing use and predictive modeling to target those at risk of the disease being progressing so that we can put in preventive measures. It's all about prevention. It's all about making sure that they not be in, going to the hospital or the emergency room where sometimes they end up in pain and one in pain medicine and so. Do you see AI as being a critical piece in the transformation of healthcare, especially where inequities are concerned? Absolutely. And when you say AI, I think it's responsible AI and making sure that it's- That's such a good point, Derey. With the right data, with relevant data is definitely key. I think there is so much data points that healthcare has in the healthcare space. There's physical data, biological data, there's environmental data. And we're not using it to the full capacity or full potential. And I think AI can do that if we do it carefully and like I said, responsibly. That's a key word. You talked about responsibility where data science AI is concerned. It has to be not an afterthought. It has to be intentional. Exactly. And there needs to be a lot of education around it. Most people think AI is just for the technology, right, group. But I think we're all part of, everyone needs to make sure that we're collecting the right amount of data. I think we all play a part in making sure that we have responsible AI. We have good data, quality data and the data science is a multidisciplinary field, I think. Which is one of the things that's exciting about it is it is multidisciplinary. Exactly. And so many of the people that we've talked to in data science have these very nonlinear paths to get there. And so I think they bring such diversity of thought and backgrounds and experiences and thoughts and voices. That helps train the AI models with data that's more inclusive, dropping down the volume on the bias that we know is there. To be successful, it has to. Definitely, it definitely is. What are some of the things as we wrap up here that you're looking forward to accomplishing as part of MARTI Health? Maybe what's on the roadmap that you can share with us for MARTI as it approaches the second half of its first year? Yes, it's all about promoting health equity. It's all about, I mean, there's so much, well, I would start with, you know, part of the healthcare transformation is making sure that we are promoting care that's based on value and not volume. Care that's based on good health outcomes, quality health outcomes, and not just on, you know, the quantity. And so MARTI Health is trying to promote that value-based care. We are envisioning a world in which everyone can live their full life potential, have the best health outcomes, and provide that patient-centered precision care. And we all want that, we all want that. We expect that precision and that personalized experience in our consumer lives. Why not in healthcare? Well, thank you, Irene, for joining us on the program today, talking about what you're doing to really help drive the volume up on health equity and raise awareness for the fact that there's a lot of inequities in there. We have to fix, we have a long way to go. Yes. But people like you are making an impact and we appreciate you joining theCUBE today and sharing what you're doing. Thank you. Thank you so much for sharing. Thank you for having me here. Oh, our pleasure. For our guests and Tracy Zhang, this is Lisa Martin from WIDDS 2023, the eighth annual Women in Data Science Conference brought to you by theCUBE. Stick around, our show wrap will be in just a minute. Thanks for watching.