(audience applauds) - Wow, what a kickoff to the MeTRIC Symposium, right. So I'm just gonna pause for a moment. We went from Ravi, to Srijan, to Sachin.
So I think this is Kathy and Victoria's way of saying Happy Diwali to everybody. (laughs) (audience laughs) So I have the pleasure of talking about WIRED-L. It's interesting, there's so much overlap between the talks that just went earlier, lots of great friends, colleagues. And one of the themes that I think you're gonna hear today, and I think it's gonna totally echo what Srijan and Sachin had said earlier, is this is really a team-based sport. And it's certainly true at my center as well.
So what is WIRED-L? Well, I think the basics for it start with this fundamental understanding that literally everyone in this room owns a smartphone. And probably if statistics are right, about half of you will have a wearable watch on at this time. And this is a fact that's, this is clearly known, right? And if you look at these statistics, these are a little bit outdated at this point, but there's millions of these devices that are out there. There is increasingly the way in which many of us connect to ourselves and our world. And this is true, Sachin had mentioned this earlier, that even populations that historically have been thought to be less engaged with these devices, that's just not true, right? For many Black Americans, older Americans, these devices have become a daily part of their lives, and many of 'em start to use them to engage with health and health related conditions.
But the reality is, is that last corner box, which is that we really don't know what these devices are doing in terms of health. We're starting to make some inroads, but in reality, this continues to be a big problem. So when we were starting to think about this about three or four years ago, we became interested as a group, there are many researchers. I come into this not from a technology angle, but from kind of a health services and outcomes research angle, where I was interested in how we use newer technologies in general, not just mobile health technologies.
And one of the things that when you look at the literature, for a large part, there are these four things that I think have been hindrances to how we start to use these devices. One is that they tend to be exclusive, right? We have oftentimes done many of these studies in populations of convenience rather than many times the populations that really need these devices. They're often done in a very cursory manner. Srijan had mentioned you can get these things to work for about two weeks and then they end up by your bathroom sink. And that's a big, big problem, and something that we've started to learn and understand in our own work. A lot of these studies are done kind of in a one and done manner.
You do it. You bring up this group, and then suddenly everybody disappears and they go on to other work. And then finally, one of the things that's very important is the siloed nature of this work, right? This takes really multiple disciplines that go across, not just clinical specialties, but research specialties.
A real understanding of how to do this, it requires that kind of multidisciplinary approach. So we proposed and pitched to the American Heart Association. We became part of a strategically funded research network. And it's been really a joy to get this up and running. Largely not just working internally within our own group, but across different centers.
And our vision, what we really wanted at the end of the day was to kind of leverage some of this novel technology and innovation, and we wanted to start to work on things that were effective, but then also sustained. Again, this idea of improvement in health. And it was a very naive idea, but part of the naive nature of it was this probable belief that it really is an app that's gonna change health. And an app can be a part of that, but it takes a lot more obviously that many of us kind of understand in this room.
But we wanted to create this translation accelerator, this idea that if you had a great idea for doing a mobile health technology study, how do you translate that really quickly towards some type of technology that you could test in a rigorous manner? And there are four pillars, and these are what I'm gonna talk about here over the next few minutes that have become a part of our group. One pillar is around community engagement, I'll speak more on that. Digital clinical trials.
We've heard a little bit about observational studies, I'm gonna tell you a little bit about our experience with some clinical trials in this space. Platform scalability, something that's been mentioned, I'll tell you our approach. And then obviously the final thing is collaboration and dissemination. So I'm gonna start with community engagement, and I'm gonna point to this map. One thing that's been really critical for us, this was actually pushed by the sponsor, but it's probably been one of the most transformational things in my own career, has been really trying to actively move beyond the walls of the University of Michigan. Now, Flint and Ann Arbor, about an hour apart, about a hundred thousand people.
Although in the last census, Flint has continued to decline to about 85,000, and Ann Arbor's up to about 120,000. But these cities could be a world apart, right? We kind of know the demographics, both kind of socially and economically of Ann Arbor. But Flint, if you just pause and think about it for a moment, is a city that at one point in time was one of the richest cities in the United States.
Had the highest median income of a city in the United States. And now, right, 40% of its population lives below the poverty line, over 50% of its children live below the poverty line. And it's a city that's really had some devastating outcomes. Now, the University of Michigan-Flint is up there, and one of the biggest goals that we had in doing this center was trying to move some of this technology, mobile health technologies, to these other types of environments, and trying to experiment with how we could do that well. And I'll tell you, in this type of work and stuff, when we talk about community engagement, I've learned a lot. One of our kind of center faculty is Lesli Skolarus.
She's moved on to Northwestern. But her engagement with this community was, really a decade in the making. And over the years and stuff, she has taught me so much about how to really work with these communities.
And I'll tell you one thing that's always been kind of in the front of my mind is a quote that she said to our group early on. Is, if we're gonna do this, we wanna do this with the community, not for the community. And that's been a big framework for it. So I'm gonna tell you a little bit about a couple of these studies. These are two studies that we publish some of the data on it.
When we decided to do a digital health intervention, we basically said, well, we're gonna build this type of mobile health app, but we're gonna do it with the citizens that are gonna be in part of this trial, right? These are participants from both these communities. Both of these studies that we ended up publishing kind of talk about that experience. The one that I wanna just focus on, 'cause it's just so telling, is the one to the left. Where, again, these are gonna be digital health interventions.
They're nudges that we give to participants. And prior to this work, the way we would develop nudges would be, maybe go out for a beer, write down some motivational messages and then stick 'em into some type of health app. And so what we decided instead was, let's have the participants who we're gonna recruit from, those communities, let's have them design these. And what's fascinating is, and this is just a table from that, and I wish I had time to go through some of these, 'cause they're just startling, right? If you look at this column, the first column is the research generated notifications, right? What we thought would be a motivational message.
The middle ones are community generated notifications from Flint, from the federally qualified health center that we recruited from. And then finally the university clinic here at Michigan Medicine. An the summary in this article is really, when you look at the community notifications, they are so different. If I gave a list to you, you would be able to easily point out, I think where these different kinds of messages come from. But they tended to be very direct in their language.
They tended to use colloquial language, right, simple language. And then finally, I thought what was really fascinating to me was they had these themes of grace, right? Like, "Forgive yourself if you didn't do a hundred steps today. Don't worry about it, there's always tomorrow." And one of the things, and it's just a little quick story, was many of the ones, especially the ones from the FQHC, had a lot of religious undertone, right? And it's a classic kind of academic exercise that we have, right? We're like, "Gosh, could we put a notification that says Jesus in it? Is that something we're able to do?" But I will tell you, if you do not engage with these communities, if you do not engage with the things that are important to them, then you're gonna be really missing an opportunity.
And that's something I think we all have to kind of think more about as we move forward. All right, so digital clinical trials. As I mentioned, much of the work in wearables has been really on observation, right? We slap on these devices, and we get all this streams of data.
So one of the things that is a potential here, especially when you're thinking about behavior change, is our ability to nudge people towards behaviors that perhaps might be more advantageous from a health perspective. And so we thought a lot about this. We're very interested in this space, and I think Srijan and Sachin had mentioned, we have literally world leaders here in the space of just in time adaptive interventions.
Many people, some of whom you'll hear from in this afternoon, have been at the forefront of designing these interventions. So just to simplify this, they're basically nudges, but they're more than just a nudge at 9:00 a.m every day to tell you to go walk, right? They take into account the fact that these devices oftentimes know a lot about you, right? They know what day of the week it is, they know if it's sunny outside, they know how much you've moved around for the last couple of days, right? And if you could tailor those to actually give a very personalized nudge that's given at the right moment in time, the idea is that this might be able to improve behavior to a greater extent.
And the cool thing about these also, is the way in which you deliver them can be literally multiple times throughout a day, and you can randomize whether or not that nudge is given. And that has a direct impact on the causal inferences you can draw from these types of interventions. And these are called micro randomized trials, right? And we've done a few of these, where literally there's thousands of interventions that are happening on an individual over a six month period of time to understand, hey, if I gave that on a Saturday, it's a different response than if I gave it on a Wednesday. All right, so we've been able to do this in four trials. These have been all learning experiences for us.
But I'm gonna focus right now on this last trial, this is an ongoing trial we have right now, it's called the myBPmyLife trial. And just as an overview, this is a trial where we are trying to improve blood pressure control through these nudges. And we're giving these nudges focused in two areas, right? Physical activity, can you increase your physical activity? And then the second area is in improving your dietary intake of salt. And so far what we've done is, we've been able to successfully recruit. And again, this is built on the platforms that, to be honest, that Sachin and Srijan, these remote recruitment platforms that others have kind of led the way at at Michigan, where we can do this entire enrollment.
And we've enrolled from two sites, both in Ann Arbor and in Flint. And so far we've enrolled over 600 participants, about 601, 602. And we're tracking them now. And at this point, we're just in the phase.
Just last week and stuff, we're down to 87 participants that are left and remaining in the study. Hopefully they will exit sometime in around mid-January and we'll have results. And our primary outcome is blood pressure that we collect at the time of enrollment, and then looking at their blood pressure six months down the line. All right, so just to give you a sense of this, right, these are the intervention group and the control group, and about 300 in both of these. But I think what's fascinating about this is, they're kind of a typical type of population for these types of interventions, is if you actually stratify them by Ann Arbor and Flint. And that's a theme that I think we were talking about earlier.
Sachin had mentioned about diversity and being more inclusive. I think these numbers are kind of striking when you do kind of separate these groups out. So we tried really hard to recruit from Flint.
And in fact, our goal in the beginning was to do about half in Flint and half in Ann Arbor. And we didn't come close. We were able to get about a hundred from the Flint, the federally qualified health center there called Hamilton Healthcare Network.
And then about 500 ended up coming from Ann Arbor. But you can see how strikingly different they are, right, just from an age perspective, 62 years old versus 47 years old. The breakdown by gender also is remarkable. And then obviously by race, right? And I just wanna pause for this because it's just such a critical piece of how we've thought about this, and I'll come back to this theme a couple of times.
But in this work, which was led by Jessie Golbus, who's here, and you'll hear from her this afternoon, as well as Lesli Skolarus, it's just a little breakdown of these are 400 participants who were recruited from this little block period of time. And we thought, okay, let's just try to look and see how hard was it to recruit from Ann Arbor versus Flint, right? We always talk about this, let's try to quantify this. And I just think this is one of our most important early insights from this study, right? At the end of the day, right, that bottom box, we enrolled 10 from each. But the path to get to 10 recruited participants from Ann Arbor versus 10 recruited from Flint is entirely different. And I'll just summarize this by this last bullet point there, where the FQHC participants required more phone calls to enroll. Almost an order of magnitude is twice as hard, right? And so if we want to talk about these values of inclusiveness and diversity, I think we have to just make that commitment.
We went back to, actually our funders, and we shared this. Because we said, "Look, you guys all say this is what we need to do. We need to set up systems to pay for it, and to actually have the resources to accomplish it." All right, so platform scalability. I think others have talked a little bit about this.
I'm just gonna tell you a little bit about our approach to this as well. So one of the key things is this idea, and others have spoken about this, eliminate redundancy, really enhance reusability. We need to start to come together as an organization to do this. We've all been talking about it, we all have the same vision.
We're all really good friends, right? And yet it just seems like there's a hump that we need to get over, and I hope MeTRIC is gonna be one of these. This is a brilliant slide, Sachin actually was the creator of it, right? It's idea of we have these apps, right? And then we gotta go through all these steps to create something that's an actual software device, and then that is something that we can eventually test. And we all know that these are steps that are along the way, right? And what we thought of when we were developing this center, WIRED-L, is just like, "Man, all these things in the middle that we don't really care about or we're not even very good at.
And in fact, sometimes when we do it, we do it dangerously. If we could just create something, right?" And in this, we put WIRED-L, but maybe MeTRIC, maybe some other type of organization around this is what we need to do to start kind of moving this field forward. And I think there's two advantages of it. There's the efficiency advantage that I think we've all spoken about, but the other real advantages is we need to start doing this from a scientific standpoint. Because right now we all do things in our own way, and it's hard to build on a knowledge base with that kind of scattered approach.
And I think that understanding kind of common data models, common processes around this is gonna be critical if we're gonna start moving the entire field forward. All right, I'm shocked that I only have one slide that overlaps with Sachin. All right, so I consider that a win.
But I'm gonna just quickly say yes. In my vision, when you think about a reusable modular platform, imagine, right, you're interested in doing a study on weight loss, right, obesity, right? There are gonna be things that happen from the participant perspective that are just common, have to happen in every study, certainly from the researcher's perspective, and we just need to figure out ways of just getting this done so that we can share these ideas. All right, the final part of this is the idea of collaboration and dissemination.
And these are lessons that I've kind of learned over the years. And I'm gonna share a couple things with you. When we put this together, we really imagine like we're sitting here, but there's this entire ecosystem around, right? At the top you see our partners within the university, all sorts of groups, right? Research groups, there are technology and infrastructure groups, right? And then there's even commercial and innovation groups, FFMI. Mike Ranella is sitting here as well.
And then in the bottom part are these outside partners, right? It's the rest of the world that exists out there. And we've had a lot of luck and fortune to work with many of the other SFORN centers. There's four hospitals within that, that includes Johns Hopkins, Stanford, Boston University, and the University of Cincinnati. And that's been a wonderful partnership because, Sachin's alluded to this, other institutions think about this completely differently, right? And sometimes you're intimidated, you're like, "Oh my gosh, Stanford, they must be doing everything." Stanford doesn't have Monica Stidham, right? That's a huge competitive advantage for us at the University of Michigan.
And if we don't take advantage of that, then I think that we are doing ourselves a disservice. Commercial partners are huge, right? There are things that we do well, there are things we don't do well. We have worked very closely with Care Evolution, we've worked with other partners.
Working with Care Evolution is an advantage because every time daylight savings happens, right? Last week, I don't have to worry about my app breaking, right? Someone else has to worry about my app breaking, and they usually do a much better job at solving that issue. And then finally, these types of outside partnership institutions, it has been like a real privilege to work with the Flint based community healthcare organizations. And I don't think we take advantage enough of the University of Michigan-Flint in our work. And I'd love to see more of this work in mobile health technologies incorporate some of those communities too. When you think about these different research opportunities, we in just three years have been able to put together collaborative grants. We have two grants now with Johns Hopkins.
We have a grant, a good friend of mine, Mike Ho is here. We have a grant we're putting in together with the University of Colorado. We have a grant with UCSF, a PCORI funded grant. And then we also have a collaborative projects we've been doing with Stanford. And then I think the most interesting novel ones, just in the last few months that we've thought a lot about, are actually commercial organizations. 'Cause I think at the end of the day, if you really wanna think about dissemination, it's not just going from University of X to University of Y, I think we have to really think about who are the people who are gonna be using this technology? And we've started to have some inroads with Instacart Health, which is very interested in how we think about technologies, especially mobile health technologies in the light of food security.
And then finally Delta. And I think this has been a really interesting partnership for us because payers, insurers are really interested in healthcare and health technologies, and how that can really reach their insured populations. And so that's some of the things that we're trying to think about as we move forward. All right, so this was our vision for the future, and I'm gonna end by coming back on one theme, which is we need to do this together, right? So we just recently worked with MICHR and Julie Lumeng to put together kind of a platform grant through NCATS, through our CTSA program here at MICHR. And what we wanna do is take all these groups and build together both a technology piece, but then also a piece about best practices, right? I mean, Sachin had mentioned things like, we learn things, right? We learn how to enroll participants.
We learn how to bring people into a process of collecting data in a safe and responsible manner. And we shouldn't have those learnings just disappear every time a different investigator comes to the table. And one of the reasons why this is so important is, as we start to move outside of the University of Michigan, I think it becomes very critical. There's this word here that as a lover of the English language, it pains me to see this. It's probably one of the most quirky buzzwords that's now coming out of the tech world, right? Techquity. But it has a really critical idea in here, right? This idea that as we design and deploy technologies, we have to think about them through this lens of equity.
And I'm gonna end with something, I think throughout all this and stuff, I came across this paper, this paper is in the journal that I edit, so I did come across it. But it was a Photo-voices study, which I don't know if you guys know this, this is a new qualitative method where they just give cameras to people, and they just take pictures, right? And then they just make comments about them. And this was a really amazing, this was done in West Baltimore, which very similar kind of in terms of demographics and characteristics to the city of Flint. And this is a set of photos that was called "Closed Market," right? And the quote that was associated with it was, "Most of them places," meaning grocery markets, "Don't wanna come into the black community. I guess because they gotta put up with too many problems in there."
And so I'm just gonna end with, it is very easy to not go into these communities because there are a lot of problems and challenges. And a lot of studies you're gonna do that are just not gonna work. But at the same time, I think we, at least at WIRED-L, have thought about how do we do these studies in a way that we force ourselves to go into these communities, 'cause it is gonna be better in the long run. And I think it's a place where, at least at the University of Michigan, we can make a real impact. So thank you for your attention.
(audience applauds)
2023-12-09