Interactive Maps of Aging: Judy Salerno and Lindsay Goldman

Eric 00:12

Welcome to the GeriPal Podcast. This is Eric Widera.

Alex 00:18

This is Alex Smith.

Eric 00:19

And Alex, today we’re going to be talking about interactive maps of aging. Who do we have to talk about this with us?

Alex 00:25

We are honored to welcome Judy Salerno, who’s a physician leader in healthcare for older adults. She’s the president emeritus of the New York Academy of Medicine and was previously the leader at Susan G. Komen Foundation and was executive director at the Institute of Medicine and was deputy director of the NIA, among many other amazing titles. Thank you for all the work you’ve done, Judy, and welcome to the GeriPal Podcast.

Judy 00:50

Thanks. Glad to be here.

Alex 00:52

And we’re delighted to welcome Lindsay Goldman, who is CEO of Grantmakers in Aging, which is a network of funders advancing the policies, programs, and investments that support the wellbeing in late life of older adults, and was previously at the Center for Healthy Aging in the New York Academy of Medicine, where she worked with Judy on the Interactive Maps of Aging. Lindsay, welcome to the GeriPal Podcast.

Lindsay 01:17

Thanks so much. Happy to be here.

Eric 01:19

So this is actually a brand new term for me, Interactive Maps of Aging. So I got a lot to learn, but before we do, we always go to a song request. Who has a song request for Alex?

Judy 01:28

Uh, I do.

Eric 01:30

What’s the song, Judy?

Judy 01:32

Well, I love Carole King, and I think her, uh, album Tapestry is, is probably in, in the annals of, um, the most wonderful rock… well, she’s not a rock star, but a wonderful, wonderful album with beautiful music. And when I think of Tapestry, I think of the words, the rich and royal hue. And that brought to mind this month the loss of 2 of our feminist royalties – Dolly Parton and of course Gloria Steinem, who I had the honor of meeting at New York Academy of Medicine and having a long chat with. So this is in honor of them. If you could play that, I’d love it.

Alex 02:21

Thank you. That’s a terrific request. And, if you’re listening live, you get me on guitar. And if you’re listening to the audio only, you get my wife Cindy playing the piano for this.

Lindsay 02:31

Thanks.

Alex 02:34

(singing)

Lindsay 03:38

Thank you.

Alex 03:40

Thank you, Judy. Beautiful. And thank you for honoring Dolly and Gloria. Thank you.

Eric 03:46

Judy, did I hear you also sing Jolene?

Lindsay 03:49

She does.

Judy 03:51

Yes, but I don’t want to scare people today.

Speaker 5 03:56

Next time. Next time.

Judy 03:57

Next time I’ll practice a little.

Eric 04:02

All right. So we’re going to be talking about interactive maps of aging. Um, and I was wondering if I could turn maybe to you, Lindsay, first. How did you get interested in the idea of using interactive maps to help think about aging populations in particular cities?

Lindsay 04:20

So it’s sort of strange, but all of my major career milestones coincide with major disasters. I, I don’t know that I bring the disaster, but I usually arrive like pretty soon after. And so during Superstorm Sandy, I was working at UJA Federation and we were making grants to organizations that served older New Yorkers and had been significantly affected by the storm.

And so I was very involved in the hurricane response and in matching organizations and older people who had been affected by the storm with organizations and older people who had not and could benefit from, you know, mutual aid. And so I, I had that experience and actually think, Judy, you also were involved in disaster response in Katrina.

Eric 05:20

I was.

Lindsay 05:20

Which we learned a lot about. So I then had the opportunity to go to the New York Academy of Medicine where 2 actually GIA members, the Altman Foundation and the New York Community Trust, had given a grant to study the impact of, of Hurricane Sandy on older New Yorkers. And like every other disaster, Older people were disproportionately injured or killed during that storm. But one of the most important things that we learned was that age itself wasn’t what made someone vulnerable.

What made them vulnerable was when all of the various systems and structures and infrastructure and communications that they relied on failed. And so when, you know, the power went out and elevators stopped working and In some cases, like this went on for several weeks. In some building it was like more than a month. Transportation and communication disrupted and people couldn’t access, you know, everything that they needed.

That’s when they turned to local organizations and they were the most critical responders. And it’s like that in most emergencies that most people aren’t, you know, rescued by the handsome firefighter. But in fact, they’re helped by their friends and neighbors and local community-based organizations that have the trust of communities. They know the languages spoken, they know the particular needs, except that those organizations weren’t always connected to each other and they weren’t connected to the formal emergency response system.

And so as a result, we saw that there were gaps and redundancies because there were there just wasn’t enough coordination across organizations and sectors in the response, right? So it wasn’t just about who needed help, it was like, who’s already there and what are they doing?

Eric 07:17

But what does that have to do with geography? So when I think about a map, I think about, I’m looking at an overlay of something on top of a map, right?

Lindsay 07:26

Exactly. Well, so there was no such map. Um, and so one of the recommendations that came out of the Sandy research was That we should use GIS technology and—

Eric 07:38

GIS is?

Lindsay 07:40

It’s geographic information systems. So mapping software and publicly available data, which New York City had a lot of at the time, to better understand the environments that people are aging in and experiencing disasters in. And So that is what ultimately led us to create Image NYC, the interactive map of aging.

Judy 08:07

I would just add that while it sounds like it’s a relatively straightforward thing to do, to take these datasets and just throw them into a map, it’s actually quite sophisticated in terms of data fusion techniques that you need because Everything from how they measure neighborhoods or by zip code or by neighborhood tabulation areas or boroughs. It’s all very variable and it’s hard to do.

Eric 08:40

And, you know, I had a chance to… so we were in Sao Paulo together last April and we had a chance to look at Judy’s talk and see it. You actually gave an example in your talk that, you know, looking at maps, maybe not interactive maps, it’s not a new phenomenon. Do you remember your example that you gave?

Judy 09:02

Yes. John Snow, the father, or parent, I should say, of epidemiology. In, in the 1850s, there was a terrible cholera outbreak in the Soho neighborhood of London, and they had about 500 cases over a 2-week period. And John Snow, by then they were talking about miasma, like the germs were in the air. So people were covering their faces and that wasn’t really helping. People were still dying. But John Snow was the germ of the germ theory.

Lindsay 09:39

Mm-hmm.

Judy 09:40

So to speak. Um, that was that, that there were actual germs that were living on things or in things. And he thought maybe the water was involved. So what he did, he and some, what was essentially primary care doctors did, was they mapped in the SoHo district where all the cases were. And you could see that they were clustered around the central water pump.

So they did something a little bit revolutionary. They took the handle off the pump so people couldn’t have water. And guess what? The number of cases went down and le voilà, you have the first evidence of the germ theory of disease. And it was radical at the time, but, but certainly revolutionary in what it laid the foundation for and how we think about the spread of disease.

Eric 10:37

Yeah. And I think we’re probably all used to that with COVID I think probably a lot of us looked every, every day, multiple times a day, maybe a little longer than that, at all of the interactive maps of COVID Where is it spreading throughout the world? Where is it spreading in your city? So I feel like that’s, that’s something that probably most of us have used this for. How does this work for geriatrics and aging? I guess infectious disease now.

Lindsay 11:04

Yeah.

Judy 11:04

Okay. So we Geriatricians are not specialists, but super specialists. We kind of step back and look at the whole landscape. And what we’re doing and what we can do with this map is look not only at the health indicators, maybe family circumstances, but we can look at in the environment, the neighborhood, the surrounding green space in the neighborhood. We can look at, you know, where there are accessible subway stops and in, well, in this case in New York City, and now we’re going to do in Sao Paulo.

And then try to, the interactive part is trying to associate them with health outcomes and what people think contributes to aging well in a particular neighborhood. And, you know, in New York City, as well as the city of Sao Paulo, which is larger than New York City, it’s a matter of the, you know, neighborhoods. We’re talking about 12 million people in Sao Paulo, but the neighborhoods are communities, small communities, and there’s variability in terms of resources, in terms of what’s available to people, where the drugstores are, where transportation is.

All of these things contribute to how well people can age in a particular community. So we want to look at that at a very refined level.

Eric 12:38

And Lindsay, just so early, so we’ll have a link to the interactive map for New York on our show notes, and we’ll talk about Sao Paulo in a little bit, but can you just provide kind of a picture of what this interactive map looks like? What are the different overlays that they can currently use and What’s your favorite?

Lindsay 12:58

So the map, I should say, was developed, uh, in partnership with the Center for Urban Development at the Graduate Center. And it was created with some seed funding from the Fanfox and Leslie R. Samuels Foundation. And that seed funding enabled us to create a map that allows us to look at age alongside about 150 different sociodemographic characteristics. Including things like poverty and race and ethnicity, disability, language, household configuration, people living alone, people accessing certain benefits, housing, and health.

And over time, we’ve added additional characteristics. We’ve removed some characteristics where, you know, data needed to be updated, and a lot of the data was from publicly available datasets, census data, um, and New York City-specific data, but some of the data needed to be crunched by some city agencies. So it was truly a multi-sectoral effort.

But what’s unique about the map and what makes it actionable is that we overlaid all different kinds of community assets, including health and social services, Affordable housing, public housing, transportation, public safety information, hurricane evacuation zones, pedestrian safety areas that were priorities for the Department of Transportation, parks, libraries, cultural institutions, all of the assets and amenities that make up a neighborhood. And I think, you know, that’s what’s different about our map, or at least what, what was at the time was that, you know, you could map by census tract, but you could map by borough, right?

And so one is too granular and nobody identifies themselves as living, you know, in a certain census tract. Now you say like, I’m from the Upper East Side, or yeah, I’m from, you know, SoHo. And then, you know, boroughs are just too large. And so you miss the nuances and some of the inequities that exist. you know, within larger sort of areas of the city if you don’t look more narrowly at the neighborhood experience.

Eric 15:24

Do you have a favorite overlay?

Lindsay 15:27

So I really love benches. I like to talk a lot about the connection between public benches and public health. And we can look at, for example, the concentration of older people with ambulatory difficulty alongside every city bench that has been cited by the Department of Transportation. And one of the things we wanted to achieve with the ImageNYC map is that New York City was one of the first age-friendly cities, and that started under Mayor Bloomberg and it continued.

And we really wanted to know where had we been successful in making improvements, who was benefiting from those improvements. For example, all of the new benches that we installed, and where was there still significant need and people were not feeling like New York City was one of the age-friendliest places to be.

Eric 16:27

I love that.

Judy 16:28

I would just add that Lindsay has a personal experience too. When we did focus groups and we asked people what they would need to improve How well they aged in their neighborhoods, aging in place. And one of the things they said was, well, when I go to the local store and buy my groceries, I can’t carry them all the way 6 blocks. I need another bench 3 blocks in, 3 blocks in. And Lindsay’s father-in-law was able to continue because he had a bench. He was able to continue working because He could walk to the subway stop and stop on the bench.

Eric 17:10

And he could—

Judy 17:10

I love this.

Eric 17:11

‘Cause there’s so much architecture right now. It’s just hostile architecture. Like you develop it so people can’t sit on it. Um, so you make it hostile to that. And there’s a growing movement of like a guerrilla bench movement where like in San Francisco, we have people actually installing benches in San Francisco. I’m not sure if that’s happening in New York outside of the city.

Lindsay 17:30

I love this. I, I’m gonna start the—

Eric 17:32

oh my God.

Alex 17:33

Yeah.

Lindsay 17:33

Guerrilla bench movement.

Eric 17:34

San Francisco Bay Area Bench Collective is our guerrilla That’s amazing.

Lindsay 17:39

I guess you can’t openly acknowledge that and be, still have it be guerrilla.

Judy 17:44

You know, there was, um, we, we learned crazy things that we would never think about when we talked to older people about, um, their neighborhoods.

Alex 17:53

Yeah.

Judy 17:54

For example, that older people didn’t wanna take buses because the bus shelters had ads on the sides of them and they felt unsafe because no one could see them. So if you go to New York now, the sides of the bus shelters don’t have, by and large, don’t have ads on them so people can be seen. So they can’t sit down and be mugged, you know?

Eric 18:17

That’s fab. All our ads in San Francisco are, uh, AI ads in every bus stop. So I don’t think they’re going away here in San Francisco. I also love the tree canopy one.

Alex 18:26

Can I give my favorite?

Eric 18:27

Oh yeah.

Lindsay 18:28

Yeah.

Alex 18:28

Oh wait, you, you go, you give yours, the tree canopy.

Eric 18:30

Tree canopy, because just talking about bus stops is. Like if you have a bus stop where there’s some shade and tree canopy on a hot day, that’s so much different if it’s just unshaded bus stop, it’s hot. And you can actually see, or like the heat is coming from the city and, you know, higher SES areas, socioeconomic areas tend to have much better tree canopy.

Judy 18:55

Yep.

Alex 18:56

Yeah. And my, mine is similarly the heat vulnerability score. You know, you can, you can drill down to neighborhood, you know, so like within Manhattan, you go up north and it’s like East Harlem and in Brooklyn, East Flatbush, and then South Jamaica, Jamaica in Queens. And we have colleagues and collaborators in New York City. And we talked with them there in the midst of some extreme heat wave and the patient, the older adults they’re caring for are really suffering. And similarly, there are now extremes at the other end with this past winter, you know, massive snowstorm and people being stuck at home for longer periods of time.

So I think the climate tab is going to become all the more important and pressing in order to identify. And I think we’re going to get to how do you use this action in a moment. Can I just say the one I found most strange? Because all of these, so many of these are like, you know, characteristics associated with health, and then on the far right, there’s voters. How did you get to the voters? What, what, what was the idea behind adding the voters?

Lindsay 20:06

Oh, well, that’s actually one of the most important ones there. And that speaks to one of the use cases, which is that not only can we pinpoint exactly, you know, who is in a given community and what resources and amenities are available, where those gaps are. But sometimes we need to make the case to the only people who have the power to make the changes in order to address those gaps and meet those needs. And those people are policymakers.

And so it helps to remind them that older people not only contribute a great deal to their communities in the form of financial and social capital, But also they vote and they vote most often. And so it is helpful to remind policymakers when you are making the case for, let’s say, discretionary dollars, or if you’re advocating for a piece of legislation, that this is a political bloc that needs to be taken into consideration.

Judy 21:17

We, we did show and tells with city council members frequently. with the map, and they were fascinated by it. They wanted to see their district and they wanted to know everything about their little area that, and what was going on there and how many people lived in walk-ups and all kinds of interesting information.

Lindsay 21:39

And we actually started with PDFs. And so this was the sort of higher-tech version of those static PDFs that we had to print out before a visit.

Eric 21:51

Was there anyone that really surprised either one of you? Like something that was hidden in plain sight when you either saw it or you layered different things together that you’re all, huh, would’ve never guessed that.

Judy 22:06

Well, let me just say that we developed it as a tool for multiple different types of people, from policymakers to researchers to the public to use. We didn’t have a specific purpose. We saw an infinite number of, of different kinds of combinations of variables that you could look at. But again, you know, I, I, as I come back always to pedestrian safety, that we were able to use data on crosswalks that were dangerous for older people, where there were more fatalities with older people.

And we, it was very simple that the countdown clocks on those corners weren’t long enough for older people with walkers or, you know, or even not only older people, but parents pushing strollers with babies couldn’t get across the street. So we had a multiple and we were able in a short period of time to reduce pedestrian fatalities in the key intersections by 16%.

Lindsay 23:16

Wow.

Judy 23:18

That was, that’s amazing. That’s, those are lives saved by just looking. And when I say hiding in plain sight, I mean that we collect tons of data, but when we start to visualize it, when we start to utilize it, when we start to connect it, then we get information that’s useful. And that’s what the whole purpose is, to get all the data that’s out there and make it accessible and useful and visual.

Lindsay 23:49

Okay.

Eric 23:50

I got another question. It sounds like you made this work for New York City, but I’m not in New York City. Can you do this elsewhere?

Judy 24:01

Yes. We had somebody come and visit us from Cape Town, South Africa, who wants to do it. Several counties in New Jersey have done it.

Speaker 5 24:11

And—

Eric 24:12

And you mentioned you’re doing it in Sao Paulo?

Judy 24:14

And I’m doing it in Sao Paulo, Brazil.

Eric 24:17

Tell us about that.

Judy 24:18

Yeah. Um, I went down there on a, what I call my geriatric Fulbright. After I quasi-retired, I decided that I needed to do something. So I went down to University of Sao Paulo. And got the Fulbright program to pay for a year. Amazing, amazing experience. And I proposed, look at this map. Why don’t we do this in the city of Sao Paulo? Because Brazil, we always think of Brazil as a young country. Um, you know, we think of the women on Copacabana in the, the bikinis and yeah, it’s there.

Lindsay 24:54

That was you, right?

Judy 24:55

That was.

Judy 25:03

Yes. Well, come down and see me and we’ll go to the beach together. But it’s the rapidity of the aging of the population in Brazil that is scary because they’re not prepared for it. They always think of themselves as a young country.

Alex 25:20

Yeah.

Judy 25:20

But, you know, as a matter of fact, that we’re, you know, we’re looking at A huge, huge number, probably 2.5 million people just in the city, within the city limits of Sao Paulo who are aging. And there’s very, very poorly distributed aging resources, senior centers, clinics, pharmacies, accessible subway stops and bus stops, all these kinds of things. And I said, hey, let’s do this.

And we had the ability to get information because of the the state, the national health system, and everybody’s enrolled. So we have data there just begging for somebody to put it together so it could be used. And the city, the state of Sao Paulo, the medical school people, the social work schools all across the university, everybody loves this idea. They’re so incredibly enthusiastic.

Eric 26:20

How?

Judy 26:20

And we got, uh, just one other interesting fact. We, um, we have some people working on mapping. The people who have mapped the Amazon, now that’s kind of a tough thing to do.

Alex 26:33

Yep.

Judy 26:34

They’re the team that’s mapping Sao Paulo and all the variables for us. So they’re doing all the technical work. And these guys are, and they are all guys, they are amazing. They’re so talented and this is like, um, you know, something and we’re creating this and their data are updated regularly by the government. So we’re going to have a dynamic tool that’s going to live into the future.

Alex 27:02

Yeah. We’ve already mentioned AI and I think, Eric, is it fair to say that pretty much every podcast we record these days, we mention AI at least once? Is there a role for AI in simplifying the work of creating these maps and analyzing them as this technology just keeps improving?

Judy 27:21

Well, we have a, a sub-project that will use AI not to create the map per se, but to explore, to dig down into what variables are related to creating healthy neighborhoods for older people. So there’s a whole big study and it’s a, it’s a pretty, again, I’m not technically sophisticated, but the people who are doing it are. So there’s a, the MAP guys are doing this and they’re very excited about it. They think we’re going to discover things that can contribute to healthy aging that we don’t know about yet.

Lindsay 28:02

Yeah.

Eric 28:03

Is there any thought on how to make the underlying technology transferable? Like if you don’t have people already mapping the Amazon, or I’m guessing you had a, you know, a working relationship with somebody with deep technology experience in creating these maps, like how does, like, you know, a county that doesn’t have that, is there ways that they could use this technology or is it just too sophisticated?

Judy 28:31

It’s open source. You want to talk about that?

Lindsay 28:33

Well, I was just going to say it’s actually not all that sophisticated. Um, well, I don’t know about that.

Judy 28:40

This came into my book.

Lindsay 28:42

But, but, you know, it was created with a very limited budget. It, it is open source. It can be adapted by other localities. But I do think that the technology remains a barrier. Um, and, and the, just the labor required to maintain it, like anytime you create something, you know, within A few months, it’s outdated.

Alex 29:07

Yeah.

Lindsay 29:08

And so that’s where I feel like AI has a major role to play here in sort of minimizing the, the human need for constant updating. And I mean, in some cases, like we were using Excel spreadsheets, and so all of that, I think AI will help to minimize and in some cases, you know, eliminate the need for, for human intellect, but also like democratize access to the data, which is really essential in helping to make the case for increased investment in aging. It’s the, a picture speaks a thousand words.

Judy 29:50

Mm-hmm.

Lindsay 29:51

And, and that is really true, particularly when it comes to aging, which people have really detrimental misconceptions about. So I think, you know, you can’t argue with what’s on a map. So you can’t tell me that age isn’t an equity issue if you’re looking at a neighborhood and seeing the under-investment as compared to some other neighborhood.

Eric 30:19

Can I ask, how do you also think about privacy in the age of flock cameras, tracking our movements wherever we go? Like, are there layers that, that you don’t think should be part of these maps or a level of drill-down that is unacceptable?

Lindsay 30:37

Well, so it’s interesting that you asked that because one of the, there were 2 choices after Sandy, right? To figure out like who needed help and who was there to help them and where did we need to bring in additional capacity. And so, There was, we should create a map, and there was, we should create a registry of all the potentially vulnerable people under all of the different circumstances that could make them vulnerable. And privacy was one of the main arguments, as well as maintenance, against a registry. And also like, how do you decide who goes on it?

Alex 31:16

And—

Lindsay 31:17

Yeah. When do I come off of it? And what happens when I die? Does anybody say that I’m not there so the firefighter doesn’t show up?

Alex 31:23

Mm-hmm.

Lindsay 31:23

In the emergency. Um, so I feel like the map, because the data is in aggregate, um, helps to allay some of those privacy concerns. But now, you know, we’re in a different time. So that’s certainly something to consider.

Alex 31:42

Mm-hmm. And sticking with Lindsay for a second, did you wanna, was there another example that you wanted to give around philanthropy and use of these?

Lindsay 31:51

Well, I think that, you know, in philanthropy, our goal is always to make aging more audible, more visible, more fundable. And, you know, one of the reasons why aging is such an underfunded priority, besides the fact that people tend to not want to talk about it too much and deny that it’s even happening, is because there is this misconception, what I call the myth of the Medicare fairy. That government has it all covered.

And so if we’re not talking about it and we think that somebody else has taken care of it, and in this case, it’s, it’s this assumption that Medicare will cover long-term care when in fact it does not, right? So there’s this, you know, overestimation of Medicare and underestimation of the role of Medicaid and all of this. you know, comes together to make people less likely to direct philanthropic resources to aging because we feel like government has it covered and all of the old people are fine. They have Medicare, they have Social Security, they’re doing well.

And it’s only with data and with maps that we can say, well, you know, if your investment priority is gender or racial justice, Right? Then if it’s health equity, then you have to consider aging because otherwise you’re not doing your work very well because here are the disparities that you can’t argue with because they’re in this map here.

Eric 33:33

Judy, I’m going to ask you, if imagine I am a foundation, I have unlimited funds and I say you can add any dataset to this interactive map, what layer would you add?

Judy 33:49

Oh my goodness. We are going through in Brazil right now with trying to narrow down the set of variables. We have 250. And I think that the ones that we don’t have really good data on are related to families and whether people live alone, whether they live with caregivers, where they live in a multi-generational household.

And I think that’s really important as part of, you know, particularly as you have a society like Brazil that’s moving from multi-generational households to, you know, people being more mobile and the families, the kids moving away, the adult kids and the parents being there alone and what, you know, what’s in the community. So. So I think information on families and that it’s there, but we have to tease it out a little more. I think it’s so important.

Eric 34:50

And you have some of that in New York, right? I saw older adults living alone and I was surprised at the high percentages and the variability in that.

Judy 34:59

Yes.

Lindsay 35:00

Very high and actually higher than in other parts of the country.

Judy 35:04

Yeah. Yeah. Well, New York City is a good place to age in place. You know, it’s really, there’s a lot there.

Lindsay 35:14

It’s a nice place to live alone too.

Alex 35:16

Yeah.

Eric 35:18

Lindsay, what would you choose? Any dataset?

Lindsay 35:21

Oh, wow.

Eric 35:22

Unlimited funds.

Lindsay 35:24

Unlimited funds.

Judy 35:26

That makes her eyes light up.

Lindsay 35:28

Yeah. I think it’s less about one dataset and more about The ability to extend the map to other populations and to see the intersections between, you know, the shifting demographics in later life as well as in earlier life. And so I’d love to have a better sense of where there are inter-generational touch-points.

Eric 35:58

Yeah.

Lindsay 35:59

That I don’t think we can see Right now.

Alex 36:03

My last question is, well, we did a podcast with Amy Kind. You’re probably familiar with her work and she did the Neighborhood Atlas. She’s at Wisconsin. And interested in your thoughts about that. It’s, you know, it’s a similar, motivated by a similar idea. In her case, it’s, you know, the whole country, most of the country, I think, or if not the whole country, though the detail.

It’s not as deep of drilled down in specific areas. You know, I think you get some ranking, like a state-level ranking and a national-level ranking. Any thoughts about either her work or other people who are doing this work that you want to give a shout out to that are sort of kindred spirits in this endeavor?

Judy 36:46

Well, and that’s a hard question, but I would like to just follow up on Lindsay’s point that The beauty of these maps and the technology that we’re using is that they can be applied to other populations. This could be a map where we look at maternal mortality or, you know, child health, or it can be used for so many different purposes other than aging or coordinated with aging.

And I think that if we can show how useful this is and how it can continue to be updated and more sophisticated, and we, we really get information that’s useful and data that’s accessible in a way that we, we can’t when we’re looking at, you know, giant datasets, that we can, we can do anything with this. We can change Healthcare.

Eric 37:48

Well, uh, Judy, Lindsay, I want to thank you for being on this podcast. Really interesting stuff. If there was like one takeaway for clinicians, social workers are listening to this who are meaning boots on the ground, what are you hoping they would take away from these interactive maps or use these interactive maps?

Speaker 5 38:08

Judy?

Judy 38:09

Issues around health and equity. happen at a neighborhood level. And we have to be aware of that. We can’t look at cities or states. We have to really, you know, as people in Wisconsin have done, we have to look at a much more refined level of information to really understand what our patients need, what they want, and what matters to them.

Alex 38:35

Great.

Eric 38:36

Thank you. Lindsay?

Lindsay 38:37

So, you know, as a funder, I don’t just want to see what the need is. I wanna see the needs and the assets together to see where the gaps are, particularly like when there’s limited resources, we can’t be inefficient. And sometimes the best investment isn’t creating another program, another organization. It’s investing in what’s already there. And that’s why maps are so important because the map can show you. where there is a community that maybe has significant need, but there’s also a rich network of existing assets that philanthropy can strengthen and help to connect rather than duplicate.

Eric 39:19

I love that. Well, Alex, you wanna take us home with, what was the song titled again?

Alex 39:24

Tapestry. These are beautiful lyrics, by the way. I was not that familiar with this song, but I’ve really enjoyed getting to know this song. So thank you, Judy, for this request. Here’s a little bit more.

Alex 39:38

(singing) “My life has been a tapestry of rich and royal hue, an everlasting vision of the ever-changing view, a wondrous woven magic in bits of blue and yellow. A tapestry to feel and see, impossible to hold. Once amid the soft silver sadness in the sky, there came a man of fortune, a drifter passing by. He wore a torn and tattered cloth around his leather hide and a coat of many colors, yellow-green on either side.”

Eric 40:42

Lindsay, Judy, thanks for joining us on this podcast. Wonderful work that you’re doing.

Judy 40:47

Thank you.

Lindsay 40:47

Thanks so much.

Judy 40:48

Thanks for having us.

Eric 40:49

And thank you to all of our listeners for your continued support.

This episode is not CME eligible.

For more info on the CME credit, go to https://geripal.org/cme/