When it comes to learning about and treating the communities we serve, data is the key. But with so much data out there, how do Catholic health providers begin to sort through it all and make sense of what they find? Jaime Dircksen, Vice President of Community Health and Well-Being at Trinity Health, joins the show to discuss how she and her team utilize data to best serve Trinity Health’s patient populations.
When it comes to learning about and treating the communities we serve, data is the key. But with so much data out there, how do Catholic health providers begin to sort through it all and make sense of what they find?
Jaime Dircksen, Vice President of Community Health and Well-Being at Trinity Health, joins the show to discuss how she and her team utilize data to best serve Trinity Health’s patient populations. She discusses key indicators they look for, how different customizable tools can help or harm the process and how generative AI and emerging technologies offer hope and caution to caregivers looking to better connect with their patients.
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Brian Reardon (00:07):
Welcome to Health Calls, the podcast of the Catholic Health Association of the United States. I'm your host, Brian Reardon, and with me is Josh Matejka. Hey Josh.
Josh Matejka (00:16):
Hey Brian.
Brian Reardon (00:17):
And this episode in the new year as we kick off 2025 is Data 101 for community benefit. In just a moment, we're going to bring in as our guest, Jaime Dircksen, she serves as Vice President of Community Health and Wellbeing for Trinity Health. So Josh, as we're kicking off the new year and the second half of season five of Health Calls, let's start by really talking a little bit on explaining to our listeners why we're starting off the new year with a conversation about the use of technology and the work that we do in Catholic healthcare around improving community health.
Josh Matejka (00:51):
Yeah, that's a great question, Brian. One thing that I think is probably on a lot of people's minds as we head into the new year, it's very imminent that here in the United States we're going to be entering a new presidential administration and a new Congress. And with that comes a lot of questions about what does the future of healthcare look like under this administration. I know it's a conversation we've been having a lot at CHA and I'm sure in a lot of industries it affects everything that we do. And so one of the things that we want to make sure that we are doing at CHA and throughout Catholic Health is we're staying true to our mission, specifically as it relates to taking care of our communities. And when we look at that, we need the best data that speaks to what issues are plaguing our communities, what sicknesses are treating different members of our communities. And as we look at all that, we've seen some of the work that our members, specifically Trinity Health have done in gathering that data and sharing that data using technology. And I'll be honest, this is a topic of conversation that I'm still learning about and I think a lot of people feel that way. So I think starting the year off with this as both a deep dive and kind of a general introduction to community health and data and the use of technology is going to be really useful for our listeners.
Brian Reardon (02:06):
And we've got a really good guest to walk us through this topic. And that would again be Jaime Dircksen, she's Vice President of Community Health and Wellbeing for Trinity Health. Jaime, great to have you on the show.
Jaime Dircksen (02:16):
Thanks for having me. Great to be here.
Brian Reardon (02:18):
Yeah. And you've been a big supporter of CHA over the years and participating in our community benefit 101 program. Now we're talking data 101 for community benefit, and I think I want to start with some words of wisdom, if you will, that Julie Troche, a lot of people who've been in Catholic healthcare know that name Julie, retired about a year ago from CHA, was a well-known and respected leader in the community benefit space. She used to say that random acts of kindness just don't cut it. When you're looking to do community benefit work, how have you taken that advice as you work with your colleagues at Trinity and across Catholic Healthcare to ensure that our community benefit efforts are more intentional and deliberate?
Jaime Dircksen (02:58):
So I met right after I started, it's the first thing she said to me, and I take it very seriously. I would say that first step is that we at Trinity Health at least really believe in evidence-based interventions that impact large sizes of the population. So when we think about how we work to improve community health, particularly through addressing the needs in our implementation strategies, really how do we think about policy systems and environmental change is honestly how we approach moving away from random acts of kindness, which are things like turkeys on Thanksgiving and random food drives, which are very wonderful and supportive of individuals, but we will never see the impact at a community level. And so really focusing on large scale interventions and policies and environmental change that we know will make a difference in the long run.
Brian Reardon (03:58):
And I think those random acts of kindness, a lot of times when I was in the community benefit space prior to serving at CHA, you get invited to do health fairs, but a lot of times those would be in more affluent areas. And so I think when we talk about data, really understanding where there is need in the community, and maybe that's a good place to start as we discuss, how do you leverage data? So what would be, I guess a basic area to start? I'm guessing demographic information is really important. There's so much robust data out there about what our communities look like. Is that a good place to start?
Jaime Dircksen (04:33):
It's the best place to start is what I would say. I mean, first and foremost, we all have to define our service areas for our community. Health needs assessments, which are required for nonprofit healthcare. And in doing so, it helps you put boundaries around where you look for data. And it also allows you to ensure or at least to focus where you're providing services. So in your reference to health fairs, which are only effective if they are purposely designed to screen and connect people to healthcare. And if you can't do that, then that's a challenge. It is great for marketing, don't get me wrong, but marketing is not community benefit and doesn't improve the health of the communities. And so I think we have to use demographic data, like particularly income and what community assets exist. So I think one thing that we often miss is what are all the assets, parks, green space, social services, churches, other areas that community members gather to really recognize either the strengths or the opportunities that exist in a community to build more thriving places that support the individuals who live in those communities, whether they be young people or older people, but the services, the community assets like the physical buildings need to be supportive of those populations.
(06:01):
So absolutely start with demographics, think about income, think about race, think about ethnicity, because cultural awareness is really important in how we design interventions, how we create space for individuals to gather if it's safe, if it's respectful, culturally appropriate, the food is what that population desires to eat. All of those things need to be considered and data really helps inform that.
Brian Reardon (06:29):
And I think this is an understatement when I say there's just an overwhelming amount of healthcare data in particular that you could get access to. What advice would you give colleagues who are working on community benefit, community impact on, again, how to start, I mean census bureau IGOs would be maybe a place, but how do you really determine, particularly when it comes to government data, what is the sort of low hanging fruit and the best place to start? And then maybe where are some other areas that wouldn't be obvious to look at?
Jaime Dircksen (07:00):
Yeah, I think that, I mean, almost every community in the United States does a survey called Fuss, which measures health perceptions of health across the United States. And those are available on state public health websites. They're available on the CDC website Centers for Disease Control and Prevention. So those are easy places. I will say that you have to be a little bit savvy because you'll get these big tables and if you don't know how to use big tables of data, it just looks like a whole bunch of numbers that you don't know what to do with. So I would say first and foremost, you need to partner with a data savvy person, a data analytics data partner, and really assess what it is that you're looking for. So I always say start on the inside. Healthcare has a ton of information inside its own walls. Our electronic health records is real-time information about the health of the population that we see every day, whereas the publicly available data is usually two or three years behind.
(08:01):
At Trinity Health, we look at vital signs. So really we focus on some key indicators, housing insecurity, food insecurity, poverty, early childhood access, graduation rates, employment, some big ticket population indicators. And then if we see disparities, if we see differences from national to state or state to county, county to local, then that's how you start to focus your energy around where you want to design interventions and partner with others. But I would say most importantly, you can't do this without others and really start with what's available. You could spend time looking at data for the rest of your life, and we just have to decide on a place and start focusing on a few data indicators that you really want to see make a difference. And I would just say the last thing is you have give it time. Changing community health indicators does not take months or years. It takes many, many years. And so you have to stick with it once you make a decision around where you want to focus.
Brian Reardon (09:09):
And when is too much data a bad thing?
Jaime Dircksen (09:11):
Well, as I said, if you are a data person and you love data, you will always find differences. You will always find places where you can dig deeper and it can be a time suck so that you have this balance of millions and millions and millions of rows of data and information to the amount of time you have to act on it. And I think that the last three to four cycles of community health needs assessments that have been in play have not changed in terms of what the community identifies as need and what the community identifies as validated by data, which data can be tricky. You can use it in positive, in manipulative ways. So I think that we have to be careful. And what I would also say is data is only as good as how you one understand it, and two, validate it with the people who you're trying to intervene with. And so we can't just use data and machine learning to make our decisions. We have to talk to people to understand if the interventions and our policies or whatever the solution is that is out to improve the data actually is working because the people are engaged with it and are seeing improvements. So too much data can be overwhelming and it can waste a lot of time. If you really try to get to where is the one place to focus, you could focus in many, many places. Just have to start somewhere.
Brian Reardon (10:48):
Yep. I want to go back to an article you wrote for Health Progress earlier this year. It was entitled New Ways to Measure Impact in Communities. And while much of the article spoke to the importance of effectively capturing and accounting for the investments that not-for-profit hospitals make in our communities, what I liked about your article is you conclude by stating that until community members have access to high quality education, affordable food and housing, achieving improvements in health outcomes is not possible. So continuing this conversation around big data machine learning, how can all this data help hospitals and health systems address these and other social determinants of health that you mentioned in your article?
Jaime Dircksen (11:30):
I think in two ways, as I think most people listening know, healthcare cares deeply about patient outcomes, and that means you need data and patient outcomes are health outcomes, less hospitalizations, improved, diabetes, et cetera. And so the things that contribute to emergency department visits and diabetes are environmental conditions, things that are outside of the control of the healthcare that is being delivered. So you can have the best healthcare in the world, but the environment in which you live is not healthy and therefore you will not achieve health. And so using what I'm most excited about in healthcare is the collection of patient social needs data, which has been really eyeopening to clinicians to be able to see the correlation between the individuals that we serve who have multiple identified social needs such as food needs, financial needs, transportation need, et cetera, and also have multiple comorbidities and how you marry interventions with that population to improve the outcomes of that population.
(12:39):
I think that healthcare more and more realizes the opportunity to impact the people they serve every day and also recognize that that alone will not stop the folks from coming to the door because the environment is not healthy. And so there somehow needs to be a coupling of direct interventions with the people we serve and the community in which they live, creating access to more healthy food, for instance, doing community-based interventions coupled with individual interventions with the patients that we serve. So I think the social needs data has been tremendous and the amount of research that's been done lately, around 20% of healthcare, 20% of the care that you receive accounts for the health that you have. And so I think we have great opportunity to address the other areas, again in partnership with many other sectors to be able to address the conditions in community while healthcare is recognizing their role in addressing the whole person beyond the physical condition of the person, but also the social needs of that person. That's where I think there is the greatest opportunity. Marrying data.
Brian Reardon (13:54):
Yeah, we're learning more about patient social needs because of the screening tools that I know Trinity and other systems are using. And that's come up in conversations about what to actually do with the data or the results that we find. I think it's what, five or six? It's not a real long survey that we use, for example, patient presenting in an er that's a data source, I guess, and an opportunity to really learn more about what their needs are and maybe come up with new strategies to address 'em.
Jaime Dircksen (14:21):
Definitely. And because CMS required in calendar year 24 actually that hospitals are required to screen patients who are hospitalized, it's going to generate even more data. And I would say there's an industry of corporations who have formed to work to use technology to address social needs, which are essentially a range of community resource directories to community resource directories with community health workers. So the robustness varies based on the product that you purchase, but it's an opportunity for a single national product to aggregate all of the social service assets across the United States, embed those into an electronic health record so that it makes it easy for the healthcare provider when a person is like, I actually don't know where I'm going to get food for the rest of the month because I've run out of money. And the provider could in 30 seconds give this person a resource. Whereas before, without this directory embedded into an electronic health record, you would have to rely on either your own knowledge or referring to someone else who may or may not exist in your health system. So I think that technology advantage is tremendous, so long as all of the clinicians and people serving patients are aware that it exists and know how to use it.
Brian Reardon (15:44):
And that's an example of maybe using machine learning or AI to make a difference and actually address some of these social determinants.
Jaime Dircksen (15:52):
Absolutely. And even the opportunity for healthcare and the social service sector to be better connected. I mean, we can't just without having a conversation, send referrals to a nonprofit, but have a conversation, understand the nonprofit's capacity, understand our needs, and then their seamless communication through technology to be able to get people what they need in the places where they live, which most times patients aren't even aware that these resources exist in their community is really this awesome opportunity to just connect the assets that already exist.
Brian Reardon (16:32):
And from a practical standpoint, like a case worker in a hospital looking at a patient that's being discharged, that type of tool could give them much more readily available access to understanding what's the capacity to food bank housing opportunities. So really, it sounds like there's the opportunity to arm or provide particular caseworkers who are working with patients, the ability in real time to understand what resources are available.
Jaime Dircksen (17:00):
Absolutely. And it saves a ton of time for both the patient and the clinician because there's sort of this instant communication and then connection that is reliable for the patient to be able to be connected to this organization. Whereas before you might have to call, leave a voice message, someone's going to call you back. I mean, it's just the opportunity to use the technology in this way provides significant time savings and potentially could really save families who are suffering in a much more expedited way.
Brian Reardon (17:32):
And you talked earlier about the need to make sure there's that personal connection. I would imagine a pitfall of AI is sort of over-reliance and taking out that personal aspect of understanding the needs of an individual.
Jaime Dircksen (17:46):
It is a huge risk is what I would say. There are a lot of operators who might think we have ai, so we can just use that for instance, for communication. Why do we need to have people who think about facilitating language services for our populations who don't speak English or who are deaf or hard of hearing? Well, if people don't know the tool exists, they don't know how to use the tool and the tool isn't working, then it's sort of useless. The AI and the technology is useless. But if we have just like anything, we still need relationships with humans to facilitate the partnership. But once the partnership is strong and maintained, the technology really accelerates all of the goodwill that clinicians and service providers ancillary staff are trying to do for the patients that we're serving in community at large. But without, if there isn't shared agreement around how referrals are made, for instance, using these community resource directories, then you have a bunch of referrals going to a black hole and no one knows about it, and then the patient isn't served and then the agency has a bad rep because they don't even know that they're getting these referrals because there was no relationship, a human relationship. So the human interaction is essential. The AI or machine learning is a facilitator and accelerator.
Brian Reardon (19:12):
Josh, you've been listening to the conversation, want to bring you in to kind of as we wrap things up here to give your thoughts or any questions you may have for Jaime?
Josh Matejka (19:20):
Yeah, Jaime, I really appreciate your perspective on the usefulness of machine learning and generative AI in terms of how it can assist and accelerate. But I also think that you have a, maybe healthy skepticism is too strong, but you have an appropriate perspective on how it can be used. Well, I would say that one of the things that we're constantly confronting when we do research for this season is that everybody's got their eye on the next thing or what's the next technology, what's the next step for anybody in your space, community health and community benefit and all that data sifting, what would you say is a guiding principle that you carry and that Trinity Health carries in terms of evaluating what are the next steps that we take into this kind of technological era?
Jaime Dircksen (20:08):
So I would say a couple things. The two examples I would use are they're great data aggregator tools and mapping tools around population, data, demographics, those vital signs that I spoke of, food, housing, insecurity, poverty, education, et cetera. And if you, as the person using the data are unfamiliar with the place that's aggregating the data, you may receive skewed results. Because when you're not looking at using the data, using an equity lens or using a lived experience lens, there are gaps in reality. And so somebody has to be that reality check, which ideally is a person who knows the community that is being assessed. Similarly with the community resource directory opportunities that exist, there are, I can't tell you how many resources there are across the country, but I'm not understanding capacity can create tension and strife between healthcare and social service sector. And so we do need to balance the use and the selection of the technology with the process of how we engage with the people on both sides of the technology, if that makes sense.
Brian Reardon (21:25):
Makes perfect sense. No really good insights and guidance. Jaime, again, we appreciate you taking time out to share your experience and wisdom on this topic. As always, really just a source of just great information on all things community benefits. So thanks again for taking time to be with us.
Jaime Dircksen (21:42):
Well, thanks for having me.
Brian Reardon (21:44):
And again, that was Jaime Dircksen. She serves as the Vice President for Community Health and Wellbeing with Trinity Health. My name is Brian Reardon, I'm the host of Health Calls, and our executive producer, as you heard, is Josh Matejka. We have additional production support for Health Calls from Yvonne Stroder. This episode was engineered by Brian Hartmann at Clayton Studios in St. Louis, Missouri. And you can find Health Calls on all of your favorite podcast apps and services, as well as on our website, which is chausa.org/podcast. If you enjoyed the show, please give us a five star rating and share your feedback. We'd love to hear from you. And as always, thanks for listening.