Challenges in areas ranging from education to the environment, gender to governance, health to housing don’t exist in a vacuum. Each month, Abt experts from two disciplines explore ideas for tackling these challenges in our monthly podcast, The Intersect. Sign up for monthly e-mail notifications here. Catch up with previous episodes here.
The social determinants of health are interactive and multi-faceted, but often the experts who address them are siloed—as are their data. How do we share the data that can tell us the full story about the people who rely on—and receive—support? Chris Tappan and Lori Hunter discuss data systems, collaboration between agencies, and the vital importance of equitable services in this latest episode of The Intersect.
For more on this topic, listen to:
- Episode 22: Breathing Easer: Emission Data, Environmental Justice and Child Health
- Episode 20: Data and Racial Equity: How Do We Eliminate Bias from AI, Machine Learning, and More?
Read the Transcript
Eric Tischler: Hi and welcome to The Intersect. I'm Eric Tischler. Abt Associates tackles complex challenges around the world, ranging from improving health and education to assessing the impact of environmental changes. For any given problem, we bring multiple perspectives to the table. We thought it would be enlightening and maybe even fun to pair up colleagues from different disciplines so they can share their ideas and perhaps spark new thinking about how we solve these challenges. Today, I'm joined by two of those colleagues, Chris Tappan, and Lori Hunter.
As New Hampshire's former associate commissioner of health and human services, Chris specialized in applying progressive practice, program, policy, strategy, and financial expertise across the health and human services spectrum. She's brought that expertise to Abt as the co-lead of our global center on technical assistance and implementation.
Lori is a principal associate in our digital services and enabling technology division. She's a certified scrum master with 20 years of experience working in systems analysis, functional requirements analysis, user centered design, and user experience, database administration and design, and web design and development. Currently she's directing the design development operations and maintenance of the new runaway and homeless youth Homeless Management Information System for the Family and Youth Services Bureau.
Lori Hunter: Great to be here.
Chris Tappan: Wonderful to be here.
Eric: Social determinants of health cross areas of expertise, but those experts and the data they need are often siloed. How can we break down those silos so stakeholders can have a holistic view of the data they need? Chris, can you talk about your experience in New Hampshire?
Chris: Sure. So when COVID hit, I was in the role of associate commissioner at New Hampshire's Department of Health and Human Services. I was overseeing a pretty broad array of services like TANIF and SNAP, housing, employment programs, childcare, in-home and community-based services for elders and adults with disabilities, behavioral health, and child welfare. Really quickly when COVID hit, we realized that our typical data sources on service utilization wouldn't be good enough to help us figure out quick solutions. We needed to know what was happening in real time, day by day, then eventually week by week. So we leveraged partnerships we had been working for a couple of years to create to help us get closer to the ground and to look across the determinants of health to understand more deeply what was happening and to develop a real time solutions.
Prior to COVID, I'd been part of this learning community in New England with the other New England state government health and human service agencies. The initiative was called the Whole Family Approach to Jobs. As part of that, it brought together government agencies and a wide array of cross-sector partners, including philanthropy, business, and nonprofit organizations. And most importantly, it brought parents and individuals with lived experience into the conversation. And we really worked for a couple of years on leveraging and bringing them to the front of the conversation to drive our work and our learning together.
So part of what we did during COVID is we leveraged these partnerships that we had been creating during the Whole Family Approach to Jobs. And we were immediately able to pull together voices at all levels across our system, at the state level, at the higher-level community level, like at the city level and county level. But deep into neighborhoods and with partners to really understand what was happening for parents and families.
Eric: So you're building this coalition of all these different stakeholders. How are you bringing data together? And that's what I want to pivot to, Lori. Because, Lori, you’re sort of working on this … I'm going to say microcosm, relative microcosm because you're working on different aspects of housing, and housing challenges, and housing data. How are you sort of facilitating that crosstalk between those different areas within that sector?
Lori: Well, I think that's the difficult part about this whole thing is that, while we are collecting that data in multiple different siloed data systems, I don't think that there's enough of a conversation around how we can share that data across those systems, across those programs to get a better view of the people who are being affected by say COVID, or homelessness, or the opioid crisis. And I feel like this is an opportunity for us to open those lines of communication, share that data across all of the different silos, and really get to the meat of who we're trying to help. Are we helping them? If we're not helping them, how do we pivot to make sure that we do start helping them and get them to where they need to be?
Eric: What's your vision of sort of how we can bring those people together to do that?
Lori: Well, I think it starts with an open conversation around the people who collect the data and have them understand that sharing their data can only continue to grow their programs and make them better. I think that there is a hesitancy to share data because they're afraid that their data aren't good enough. But this is an opportunity to really see that your data are good enough. And then pairing it with more data makes that story that much stronger and that much more compelling to help the people who are really needing the assistance.
Eric: Great. And Chris, I see you nodding and I know you had to sort of bridge these gaps in the preschool development grant. You want to talk about that?
Chris: Sure. Well, I will just say real quick that, as Lori just mentioned, having people being willing to look at data without it being perfect. In COVID, we didn't have time to get it perfect and to get it all clean. And what it did is it accelerated what we had been working for years to build more interoperable conversations about data and data elements and how to use data together. The preschool development grants are funding that came out from the Department of Health and Human Services and the Department of Education federally a few years ago. And one of the things that it did was really to push locals, states, and communities to actually bring different partnerships together that all touch the lives of young children and families.
And to begin to share their data to better coordinate services across the community to make it easier for families to navigate. And to not have to go door to door to door and they tell their stories over and over again and have their data collected at multiple points. But instead for the systems that were behind the programs and services to be doing that work. The idea really being that the experience of children and families should be held at the center. And that experience should be smooth and it should be easy. It should be easy to navigate and get your kids or get your family what you need.
Eric: Let's say, you're a state government, or you're a federal government and you want your agencies to be talking to each other and sharing information. What are some of the challenges the two of you have seen that you need to identify and lay out?
Chris: So just, I think continuing to think about how do you bring people from across sectors? It can be challenging enough from within a single organization to bring together different departments or parts of that organization to share data. But when you talk about reaching across the types of organizations or agencies that might be serving and trying to support children and families, that becomes increasingly complex. In New Hampshire, through funding for the community collaborations to strengthen and preserve families grant, which came before for the preschool development grants. They actually, for the first time, this came out from the administration, from children and families from the Children's Bureau. The hope was actually to create deeper coordination and cohesiveness across systems that support families and strengthen families prior to a crisis that might bring them to the front door of child welfare. So it was actually to reduce the chance of trauma happening in a child's life. What that did is it actually, for the first time for us in New Hampshire and I know for other places across the country, it really pushed government agencies and their partners to talk about how to span boundaries and work together in ways that really creates clear direction, alignment, and commitment. And a big part of that commitment is about sharing data that makes a difference for families. So the challenge becomes, how do you talk about the risks, the barriers to operationalizing and attention around data sharing. So things like data sharing agreements become very hard in a complicated regulatory space, but it's doable. And there's many jurisdictions across the country that are actively doing this and it is making a change and it's improving outcomes for kids and families. And that's the ultimate goal.
Eric: Yeah. I was going to ask you about outcomes. And with the COVID work, I don't know if you saw similar outcomes. But I think pointing to the data, if you can, Chris, do you want to speak to how the data itself was actually helping to sort of reach these goals?
Chris: So one of the things that was elevated really quickly in COVID was inequity, and disparities, and service utilization, and access. So we had known in New Hampshire and again, I was working very closely with my New England partners. We actually, our federal government, our region one of ACF actually coordinated weekly calls for us to be able to be sharing what we were learning and what was happening. So I was hearing very similar things from across all of the New England States. And part of what quickly happened is that we realized that we were seeing families who were living in underserved communities have even more extreme and urgent needs that were not getting met.
So for example, when funding came out from the initial funding package under COVID last year and in particular targeted at housing, when the monies for those housing vouchers and housing supports rolled out, we actually saw that those vouchers actually most often went to white families. Who was left in our homeless shelters was actually individuals of color and families of color. So black and brown families were left in the homeless shelters. And we had to ask ourselves, what was happening between landlords accessing those funding for housing? And what was happening with why who was remaining in the homeless shelters were black and brown individuals and families. And really what we came to understand is we had some biases in the system that we had to address and we had to remediate quickly. And we did. We leaned in, we opened up the dialogue, and we pushed that effort forward.
Eric: Chris, we’ve got to have you come back and talk about that a bit more just in and of itself. But so that's great. That's how reporting out is helping to sort of identify problems and then lead you to find resolution to those problems. Lori, what are you seeing in terms of systems? What about collecting that data that people are using to share and how do we share that data beyond just an oral report? How can we make that data available to more people who can use it?
Lori: Well, I think, as Chris said, I think that the data use agreements are, while they're hard, that they are something that can be done and ways to share that data can be written into those data use agreements. And understand for the most part that I think people want to use the data for good. They're not out to try and use the data against the people who are being reported on. And this also gives you an opportunity to really think about the granularity of data and how that varies across different programs, how it's hard to integrate two datasets because you don't have a key that links them together. So thinking about a better way to collect data so that you can start to link these data a little bit better. Make the data more readily useful to the staff who need to use that data.
I often come into conflict with trying to be able to pull data out of systems because while, it's a great way to ingest data and validate that the data are there, getting it back out into a useful format seems to be something that is missing from several of the, maybe the administrative data collection systems that are already out there that are helping to support programs. And so trying to find a way to either modernize those systems or modernize the approach to visualizing that data or using that data is the next step. And how they can use that data to tell the story of how their programs are collectively impacting the health and wellbeing of the people being served.
Eric: Right. And now's maybe a good time for me as the marketing guy to say that I know we do a lot of data visualization for housing, but then also New York Times and Washington Post just did a piece on the data visualization we did for EPA. So that's something that we're pretty good at. And I hear you say that something that can help people make better use of data once they can get past those concerns that they have and get those agreements in place. So moving forward, what should we be looking for? As we just mentioned, data visualization. Can you be more specific or can we be more tactical on how we might recommend that agencies think about sort of pulling those resources, sharing those resources, how they could work together more collaboratively around data?
Chris: So I would offer a significant lesson learned. As I mentioned, the Whole Family Approach to Jobs that we have been working on across New England had actually been progressively, we've been elevating the voice of parents and individuals with lived experience at the forefront. During COVID in particular, as I mentioned, we noted the shift in our housing data. We had been gathering on a weekly basis at our department. I led these conversations that we touched across all the determinants of health. So each week we asked about food access, transportation, housing, childcare, employment, healthcare, what was access looking like across all of those dynamics. And then we looked at them at different levels. So as Lori mentioned, we looked at the state level program or administrative data. We then actually also brought in community level data. So we invited in community partners that ran nonprofit organizations that often eventually reported up to us.
But in that moment, it wasn't fast enough. And I think that's a lesson learned, is that we have to increase the timeliness of our mechanisms to see and understand data. We actually created a network that connected to our parent and individuals with lived experience voices. So we connected with family resource and support centers, with our New Hampshire chapter of the national alliance for the mentally ill, with different kinds of providers and organizations that had a quick connection and could ask people, what is it feeling like today in this experience? And what do we need to know about that from a data perspective? And I think elevating and recognizing the importance of those voices as a primary source, not a secondary or later validation source, but a primary source about how to create solutions and to make change, and then track your changes is really where we are now with understanding and advancing equity.
Lori: And I would agree with that. And to piggyback on that Chris, I think that collecting those voices in whatever way you collect them, whether it's through a qualitative survey or whether it's recording them, taking the time to apply some level of natural language processing to it to fully pull out the themes that are happening across what those voices are saying. And then combining that with the data that are being collected, I think you just get that much better of a picture of what's really happening.
Eric: Lori, is there anything else you would suggest sort of from a technical perspective of how to implement this sort of collaborative approach?
Lori: Just be open to having those data use agreements out there, being open to having a conversation about your data might not be the cleanest, it might not be the best, but it's still important data. You're still spending the money to collect that data. So let's find a way to use it in maybe more ways than you probably thought of before. And just sort of step outside of what your research questions are right now. And think about how your data can maybe use to answer other research questions that maybe you haven't thought of in the past.
Chris: So with Abt, we're really pushing towards a data-driven solutions oriented technical assistance approach. We want to be with people, with their data, co-creating their solutions. And then knowing whether those solutions are actually working. And so part of what we're trying to build in across all of the work that we're doing is this multi-level approach to data collection.
It's really important right now that as we try to advance equity and do that quite, I think with a lot of urgency, more urgency than we had a year ago. And today is the one-year anniversary of George Floyd's murder. And so to really recognize the importance of advancing equity. If we're not doing that with a deep questioning of, is this telling us the true story for those individuals who live in underserved communities, then we're not really taking on what the greatest challenge is right now.
And again, I would say, I think one of the things that had often in the past, in my career gotten in the way of being able to share data and then do this co-creation of solutions, was that certain people at the table often feel the need to raise the barriers or the risks. And that is important. But one of the things I tried to do as a leader, and I always appreciated my partners who came to the table with an attitude of opening the no, how do we create the yes together? How do we create the, we can do this together? Because if we don't do that, we're never going to really get to the kinds of outcomes that people deserve. People deserve better services. And one of the best ways we can do that is to create data systems that actually tell us the true story.
Eric: Well, that's the pull quote.
Eric: So that's a great place, I think, to end. Thank you both for joining me!
Lori: Absolutely. Thanks for having me.
Chris: Great. Nice to be here, Eric. Thanks.
Eric: And thank you for joining us at the Interest.