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Nonprofit Leadership Podcast
How is AI Changing Medical Research?
00:23:50
In this episode, Rob speaks with Dr. Kristen Brown, Senior Research Associate at the Urban Institute, about the transformative impact of artificial intelligence (AI) ...
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- [00:02]
Dr. Rob Harder
This is Dr. Rob Harder with the nonprofit leadership podcast, Making youg World Better. What does it take to be an effective nonprofit leader today? What are the biggest challenges? What are the biggest obstacles? How should nonprofits fundraise in an economy that is constantly changing? All of these reasons combined led me to start this show. And it's my hope that through this series, people can learn not only what it takes to be an effective nonprofit organization, but to hear from effective leaders who are successful successfully making a positive impact in their communities. We hope you enjoy the show as together we hear how they are making their world better. Welcome to the nonprofit leadership podcast Making your World Better. Thanks so much for tuning in. Always good to have you along with us. We've got a very fascinating guest again today, and we're going to talk about a lot of different things and specifically focusing on medical research. But part of the conversation we end up having is the impact of AI. And you know, I've had many guests on the show talking about AI. How can AI be used for good for your nonprofit? How much AI should we use, and what are the dangers of using AI, all those kinds of topics. Well, she's dealing with this as well and a little bit different application when it comes to medical research. And my guest again today is Dr. Kristin Brown, and she's with the Urban Institute. And among many things, we're going to talk about what she's doing. She's doing a lot of research focusing on maternal health here in the United States. But then we end up talking about AI and what is the net gain for using AI? Is it net positive or is it a net negative? And so it's going to be interesting to hear her response to this when I ask that question of her. Well, as always, thanks so much for tuning in. Now on to the show. This podcast is sponsored by Donor Box, helping you help others with the best donation forms in the business. Well, welcome to the Nonprofit Leadership podcast. We have Dr. Kristen Brown. Dr. Thank you so much for taking time to be on the show today.
- [02:04]
Dr. Kristin Brown
Oh, thank you so much for having me. It's just a joy to be here today.
- [02:07]
Dr. Rob Harder
Yeah, well, I always love introducing my listeners to great leaders just like yourself. And so I'm really excited to dive in a bit about what you do at the Urban Institute. So maybe that's always a good way. I feel like, to start out, give a bit of your background, a bit of your journey. Could you tell me about your path to the Urban Institute and maybe what led up to that?
- [02:25]
Dr. Kristin Brown
Sure, sure. So I describe My career as a journey upstream is what I call it. In college, I double majored in biology and psychology. I wanted to understand racial health disparities. And when I came out of college, I was going to grad school. I was like, okay, do I want to be more of a biomedical scientist or more of a social scientist? I thought I had to pick. And I actually first picked being a biomedical scientist. I was like, okay, I'm going to understand the biology, the physiology behind all of these diseases that we know have a lot of racial health disparities. So I was looking at genes and proteins and things like that, and I was like, wait a minute, this feels a little far off from what I intended to do. So how do I think more about, like these social factors? Fortunately, I went to University of Michigan for grad school. And there in the school of Public Health was a center for integrative approaches to health disparities. And there were a social epidemiologist named Ana Diaz Roux, a genetic epidemiologist named Sharon Cardea, who was trying to understand how our social factors actually affect our bodies and therefore our health and health outcomes. So I started working with them, started studying under them, and that's what I did for a lot of my dissertation work and then again in my postdoc. And then after that I went to nih. And the work I was doing at NIH was around risk scores and what goes into these risk scores and what variables are going into these risk scores. And then if we create these risk scores off of mostly white populations, how generalizable are they to other populations? And is the way that we're doing this science actually creating the inequities? So that was a lot of work I was doing at nih. And then, you know, I'm trained as an epidemiologist. My PhD is in epidemiology. And the pandemic happens, right? So I was like, oh, wait, I'm epidemiologist, Pandemic is happening. I think I should probably do something around the racial inequities of the pandemic. And Urban had a big project where they were supporting community organizations who were doing the on the ground work around education, around vaccines, and trying to get these organizations evidence based research that they could use in their work. So I came to Urban at first, really to join on that project, but also let me extend my work into thinking about policy and how policy is affecting all of these downstream factors. Whereas I started all the way down in like jeans, as downstream as you could possibly get to go all the way upstream, career stage by career stage, to get to policy now I can speak to each level and try to think about how each of those levels are affecting health and racial health disparities. So that was my journey to Urban. Enjoyed being here so far.
- [04:56]
Dr. Rob Harder
What a great journey. No, thanks for sharing all of that. Okay, so let's talk about your role specifically now. What is it focused on? How has it grown and how have you developed since you've been there at Urban? Sure.
- [05:06]
Dr. Kristin Brown
So I'm a senior research associate at Urban, which means that I manage different projects mostly around racial health inequities and policy. So I've been able to extend in doing more work in policy now and trying to think about how those factors or those where those leverage points are that we can make in our society to reduce inequities.
- [05:25]
Dr. Rob Harder
Yeah. And I understand the team was recently named as one of the inaugural grantees of the GE Healthcare foundation focusing on maternal health specifically. And so first of all, congratulations. That's a big deal. I know that's a tough vetting process, so well done. Could you give us some context to that? Tell us about the current crisis for moms and babies in the US and what are you trying to do to address that?
- [05:46]
Dr. Kristin Brown
So first of all, it is such an honor to be named as one of the inaugural grantees for the Healthcare Foundation. You know, there's such great synergy we're aligned in trying to make this a more equitable society. So we're just so honored one to even just be supported by the GE Healthcare Foundation. As for maternal health, the US Just fares substantially worse than all of our peer countries. I mean, we are talking about Australia, Canada, France, Germany, United Kingdom, Switzerland, Sweden, Norway, the whole list of our peer high income countries. Our maternal health rates are just way worse. And so it makes you ask the question, well, why is that like, what is it that is going on in how we do healthcare in our healthcare system that we're not getting the outcomes that we should get? Right. And it's not just the money issue because we actually spend a lot of money in healthcare and we're not really getting the outcomes that it seems that we should get for how much money we spend in it. So these rates are particularly egregious for black women. Rates are two to four times higher for black women compared to white, Hispanic or Asian women in terms of maternal mortality in the US which makes us ask the question, like, well, what are these social factors that are causing these racial inequities? But then even if you look specifically at the rates for white women, Hispanic women or Asian women. They are still higher even within those racial ethnic groups. They're even still higher than other, the other peer income countries themselves. So it's not just, it's women overall that are just not having great outcomes Here in getting healthcare in the U.S. we see similar things for infant mortality. We have higher infant mortality rates. So that's when the baby dies before its first birthday, his or her first birthday. And again, we see racial disparities there. And then even if we don't look at mortality and we take a step above and look at morbidity, who's getting sick first before you die? That has an effect on a lot of people in the US as well, where we are getting these unexpected outcomes from labor and delivery that have health impacts over time. What the really egregious and really problematic part about all of this is that most of this is really preventable because if we're not getting the same outcomes as other similar countries, then this is, is something about our healthcare system that is producing these abysmal rates. So what, you know, so what is it? There's a few things, you know, policy things. One is the paid leave. Right. Other countries guarantee paid leave for moms, mothers after they leave, whereas we send our women back to work too soon and then before they have had full time to recover physiologically, psychologically from producing a child. Second, other ones have more obgyns and more midwives. So we don't have enough in our workforce. Other countries do home visits after the child is born to see how the child is doing, the mother is doing. And then we also just have our huge insurance coverage issues here where the other countries have universal health care and we don't. Right. So that means that we have a lot of reproductive age women as part of our American society that are uninsured. So that affects them prenatal care and all of the outcomes that we see.
- [09:21]
Dr. Rob Harder
Interesting. Okay, well this is so interesting to get more of this context on it. And you've got this research project I know that you're putting a lot of time into. Maybe you can give a little bit more specifics on that of what it's focused on and what do you hope to have as the outcomes?
- [09:35]
Dr. Kristin Brown
So the use of artificial intelligence is everywhere these days, right? And it is. Yeah, everywhere in every sector of society, including in the health care of pregnant patients. So for example, AI is being used to categorize patients as high risk to. For example, we can identify risk of preeclampsia of hemorrhaging after childbirth and then mark those patients that are high risk to give them higher level services to help them address or manage that risk. So the project is really centered around understanding how Medicaid agencies are thinking about their policies, about incorporating these AI systems into their health care decision making process. So our project's really important because Medicaid pays for 41% of births nationwide. So getting this right really has very broad implications for maternal health.
- [10:25]
Dr. Rob Harder
Interesting. You know, there's so many areas to focus on and I'm sure when it comes to maternal health for you and your team, you probably had to decide what area you're going to focus specifically within maternal health when it comes to this project then and the way you're going about it and the approach you're taking, how did that process go? Bring us into that.
- [10:43]
Dr. Kristin Brown
Sure. So we have two components. First, we have the first, we are trying to see what documentation is publicly available and then how the Medicaid agencies are incorporating AI into healthcare. So we're first working to build a public knowledge base of Medicaid policies and practices towards using AI in the context of maternal healthcare. So we have our data science team who's working through a process known as web scraping, where they're collecting information from various state Medicaid websites and the team is looking through managed care contracts, through state health equity plans, through quality strategies. And this is a large amount of data, a large amount of unstructured data. So they're able to glean information from all of these websites so that we can then make sense of it for policymakers and other stakeholders, community organizers, et cetera. And then from that, our qualitative research team is going to use the findings from the data science team to interview representatives from Medicaid organizations and really just get a sense of like, what are they thinking around these maternal health factors? So we're going to think about, like, what did they think about when they were trying to develop their equity plans? How well are their equity plans playing out in practice? What are the lessons that they've learned en route to developing their equity plans?
- [12:07]
Dr. Rob Harder
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- [14:51]
Dr. Kristin Brown
So we're hoping that the project gives us a sense of what the conversation even is Right now AI is just unraveling so quickly. Yeah. So we're just trying to keep a sense of like, well, what is the conversation and what are the things we need to be considering where are the trailblazer states in thinking about this? And then what can the other states learn from these trailblazer states? So right now, our data science team is starting to look through all of the data that we've collected and trying to see trends and figure out what we can analyze and what picture we're starting to get. You know, we're so far, we're starting to see that some states have information out there and other states do not. Right. So there's a lot of variation, heterogeneity, and in what's already out there so far. So definitely stay tuned.
- [15:36]
Dr. Rob Harder
Well, it's so fascinating to me, and I would like to see the contrast from your experience now using AI and studying AI and the impact of AI in the medical research sector with your research. But to compare it to how it was different in your days at University of Michigan, where you did research in a much different way. What were some of the big things that really have stood out so far when it comes to using AI and this research project?
- [16:02]
Dr. Kristin Brown
So I would say the technology, right. It's like what you can do is. And you can do it faster and quicker in ways that, you know, 10 years ago, when I was in grad school, it would have taken you your whole career to do something that, you know, can now be done in a few weeks. And, you know, how do we use that to our advantage is the question. And then how do we also not cause harm in the process? Like, how do we not be too fast, but faster? Right. So that's. That's the big difference is it just makes everything just faster.
- [16:37]
Dr. Rob Harder
Well, you know, there's a lot of nonprofits dedicated to research, of course. So from your experience, why is this research so important? Important? And what have you learned so far from this collaboration with the GE Healthcare foundation, and how have they really facilitated or maybe been a catalyst for you being able to do that, this research project? Perhaps quicker and with more funding.
- [16:56]
Dr. Kristin Brown
Yeah. Well, we're so glad again for the support of GE Healthcare foundation as we tackle this important and timely issue. And I specifically say important because we know the impact that this has on maternal health and how many women are affected in the US that really shouldn't be right because it's preventable, but also timely because AI, this is AI. This is a new AI era that's being ushered in, and we want to make sure that we do that right. And research itself is just so important because it equips policymakers and stakeholders and decision makers and physicians with evidence of what decisions to make, right? And so this project is just so critical at this moment, when AI is just being developed so rapidly, and on top of that being layered on some of the cracks that already exist within American society, including our terrible rates of maternal morbidity mortality and infant mortality. So in public health, we have what we call the theory of fundamental causes. And one of the tenets of that theory is that every time whenever there's new technology, that that always increases disparities because the haves get it, the haves don't. And what we're trying to do is we're trying to stay ahead of that curve this time. Like, okay, we know all of these new technologies come out, but if we can center equity at the foundation at the beginning, then can we prevent that exacerbation that typically happens when new technologies are brought about? And, you know, AI just has so much potential, but it has so much potential in both directions, right? It has potential to go really, really well. It can help with implicit biases of, you know, physicians that currently cause racial health inequities and go the other way and, you know, be really, really harmful. Because the data that is being used to develop these AI models, if. But if that data itself is flawed, if that data itself is inequitable, then it's only going to be magnified when you put it into AI methods. So what we're trying to do is to take this moment, because this moment is so important, and make sure that we're baking equity into it at the ground level or as soon as we can, and sound that trumpet now so that we don't have to try to fix it, fix it later.
- [19:16]
Dr. Rob Harder
I'm really glad you're bringing this up. I've had many people talk about nonprofits and AI, specifically utilizing AI, say with fundraising, for example, or special events. And here's a really interesting application when it comes to medical research. I mean, you've already spoken to some of the exact concerns that I've talked to others about. The concern about privacy, the concern about bias built into AI itself, and as you say, the risk of exasperating the issue. So I know it's early, and you're still in the process of doing this research project, but so far, what would your verdict be? Is having AI an asset, or are there more liabilities right now utilizing AI, or is it too early to say? What would you say to that?
- [19:55]
Dr. Kristin Brown
I think it's too early to say, but history tells us that new technologies exacerbate. History tells us that it exacerbates. But I think it can go both ways. It's just which one is going to. I think one of my concerns is that people say, oh, well, this is what the model showed me and it's not my fault. The model did it. Right? So then it becomes who's responsible for what went in the model in the first place. And if the model is already being trained on inequitable data or data that's been incomplete, that gives us the results that we have now, then who do we even point to to say this is where we went wrong? Right. Because now it's just the computer, you know, the computer told me. So it's just so critical. It's so critical for so many lives, really literally lives at stake that we get this right in this moment.
- [20:56]
Dr. Rob Harder
Okay, for my listeners, then, what would you like them to take away from this work? Like, if they really get interested in what you're having to say and want to do their own research and learn more about the Urban Institute, what would you like them to take away from this work?
- [21:09]
Dr. Kristin Brown
I think just to keep being vigilant, to make sure that equity is bathed in at the ground level. You know, some states have developed plans, many have not. Right. So some states are going to catch up and try to do it. This is just a foundational moment and this is an opportunity to build equity into the fabric and policies that are being developed right now. And we have to realize the moment that we're in and make sure that, you know, the burden is on us, of the America that we give to our kids in the next generation to make sure that we do this right. And secondly, I would say that this isn't a one and done project. I think that obviously AI is here to stay. Obviously the maternal health crisis has existed for a very long time. It's been pervasive. So to really do this and to really intervene and really get the outcomes that we really not only want, but really should have that we've got to make sure that we're on top of this and that we're, we're really paying attention and, and not even just. Not just paying attention, but actually intervening when needed. So we need that the morale and the will to actually in. To intervene on these, these issues.
- [22:24]
Dr. Rob Harder
Well, related to that, how can people connect with you? If they want to connect with you or find out again more about the Urban Institute as a whole, where would you send them?
- [22:31]
Dr. Kristin Brown
Sure. So I'm on LinkedIn and X as Kristin Brown, Ph.D. urban is on all social media platforms, X, Facebook, LinkedIn, YouTube, as Urban Institute, so we're not too hard to find.
- [22:43]
Dr. Rob Harder
Well, Dr. Brown, it's fascinating to hear what you're doing. And thanks for answering those questions about how you're utilizing AI in this case, for medical research. And thanks again just for sharing your insights and for taking time to be on the show.
- [22:55]
Dr. Kristin Brown
Oh, thank you so much for having me. This was fun.
- [22:58]
Dr. Rob Harder
Hey, friends. Well, I wanted you to know that this podcast can be found on I iTunes, Spotify, Amazon, Google podcasts, and wherever you listen to other podcasts. I also want to encourage you to like subscribe and share this podcast with others. This will actually help us get this great content out to more nonprofit leaders just like you. You can also join the Nonprofit Leadership Podcast community, find other resources and interviews of past guests, all on my website. Nonprofit Leadership Podcast. Well, thanks again for listening. And until next time, keep making your world better. And don't forget to subscribe to my YouTube channel, the Nonprofit Leadership Podcast. Go to YouTube and look up Nonprofit Leadership Podcast. We'll see you there. This podcast is sponsored by DonorBox Donor Box, helping you help others with the best donation forms in the business.