Claudia D. Solari is a senior research associate in the Metropolitan Housing and Communities Policy Center at the Urban Institute, where she studies housing instability. Solari specializes in social inequality and demography, with a focus on homelessness, low-income housing, mixed-income housing, neighborhood inequality and segregation, and housing crowding. Recently, Dr. Solari and her colleagues have published two reports related to veteran homelessness: The Value of Ending Veteran and Chronic Homelessness in Four Communities (August 2021) and Community Strategies to Understand and Reduce Veteran Inflow into Homelessness (November 2020). OSAH sat down with Dr. Solari to learn about her research on Veteran Homelessness, the importance of quality data, and much more.
Dr. Solari’s views are her own and do not represent the views of the Urban Institute, its trustees, or its funders.
OSAH: What does quality data on homelessness—particularly veteran homelessness—look like?
CS: Before we can go to notions of quality data, we should talk about the broader landscape of data a little bit. At first, most people didn’t even think you would be able to get data on such a mobile and diverse group of people who have various reasons that they may not want to be found or identified. The Homeless Management Information Systems (HMIS) proved them wrong. Prior to the introduction of HMISs, estimates spanned a wide range. The HMISs, which include demographic information —including veteran status— of each person and their every touch through the homelessness response system that allows you to understand the extent of homelessness within various demographic groups, and can help inform policy and programmatic decisions. So, the critical role that data has played in shaping our homelessness response system and shaping policy cannot be understated.
When it comes to data quality, however, many communities’ Homeless Management Information Systems still have work to do. Not every program serving people experiencing homelessness are contributing data to HMIS in a community, so there is still a lot of estimation happening in the system. Basically, the more programs that participate, the better your entire data management system is. But there are other limitations on quality. Even if you have a nice HMIS system in your CoC, you are still blind to other systems’ data of another CoC. In addition, the VA has their HOMES data, which is separate, so you have two large systems – The VA and the mainstream homelessness response system – that are trying to serve the same population in a given community with jurisdictions that don’t quite overlap; they are siloed enough that you don’t quite know what the left and the right hand are doing; there is a lack of coordination there. I know that there are efforts to break these siloes down; people have realized it is not helpful to have such a narrow view of how veterans are being served in a community.
That’s part of ‘quality’ and it feeds into what your system perspective is. The homelessness response system was originally designed as a program-level approach to service people experiencing homelessness, but programmatic silos had made people blind to underlying causes of homelessness and what potential solutions might be. Enhancing the wealth of programs participating in HMIS, as well as breaking down siloes between HMIS and HOMES systems is really where quality lies as it relates to understanding veterans experiencing homelessness. There are already steps where the VA is trying to share HOMES data on the HUD-VASH program with HMIS systems. It needs to be more than the HUD-VASH data, though; To fully represent veteran homelessness, data sharing needs to include all of the VA programs and all of the mainstream homelessness programs.
OSAH: What is the value of having access to quality, non-siloed data?
CS: I think the value of administrative data can really help not just track program-level outcomes—It can also inform a broader analysis: let’s look at how we’re doing for everybody and where can we do better? Without quality data, you wouldn’t know where you can do better; it helps motivate and target where your attention and resources can go. For example, you might find an increase in veterans experiencing homelessness for the first time in your community, and that might involve a different action to address that than if you had an increase in veterans who had exited homelessness in the past but are returning to homelessness from permanent housing situations.
I also want to emphasize the importance of qualitative data. We learned a lot from just hearing the voices of veterans who were experiencing homelessness in these communities. What brought them there? Where was the breakdown in the services they were receiving? For example, there were some communities that—through interviews with homeless veterans—found that a lot of the veterans were experiencing homelessness just after they had left a VA-funded substance use disorder treatment program.
If we want to stop inflow, stop the pipeline into homelessness, identifying clear areas where people are funneling from another system into homelessness is critical. Without asking veterans themselves, the community wouldn’t have thought to look at the people who are getting served within the VA-funded substance use disorder treatment programs and to start asking the participants there, do you have a place to live after you leave this treatment facility? The same goes for VA medical centers. When they are serving veterans, they can ask about the stability of their housing situations. These are ways to catch housing instability further upstream. I know HUD talks about making homelessness “rare, brief, and non-recurring.” That requires a systems-level approach and it inevitably has to include inflow and homelessness prevention. That involves multiple community systems coordinating together.
OSAH: Where is the highest quality data right now, and what data needs to be improved?
CS: There is higher quality data within contained programs, but there is room for improvement at both points of entry and exit. There is a lot of missing information when someone leaves an emergency shelter, for example. It’s easier to get intake information, but sometimes people just take off and now you don’t know where they went. When you transition someone from an emergency shelter in your system to a permanent supportive housing program in your system, those data are better quality because it’s all within your system. But when people leave, you may not know where they are going until they come back. I think there is probably room for improvement on the returns to homelessness information, too, and street outreach isn’t systematically being included in HMIS. But the longitudinal systems analysis data, which is considered the ‘next generation’ data collection effort for the Annual Homeless Assessment Report (AHAR) to Congress, those data are now getting more focused on returns—where are they coming from, how long were they out for, and what brought them back in. I think there is a lot of room for better understanding the permanency of exits out of homelessness.
OSAH: What are the main issues right now in terms of improving data collection at the local level?
CS: It’s a complicated array, but at the local level providers need to understand how the data benefit them. If you haven’t conveyed the value of their own data collection, and how those data can inform their activities, then it becomes less valuable for them. There was an understanding of that in the beginning—because HMISs aren’t housed directly at HUD, the data are instead coming through these privatized HMIS systems and aren’t just there for reporting to the federal government; that data are also useful to help the community answer questions that are locally important for them to answer. Setting the system up this way was smart, but it made for a lot of complication. Every community has a separate system, but they aren’t always talking to each other. I don’t think local communities always know how to capitalize on the data they are collecting. There is so much information out there that isn’t being taken advantage of because it’s complex, but the quantitative data are only going to tell you so much. It is important to hear directly from people who are experiencing homelessness themselves. They know what is interfering with their ability to get out of homelessness and where they came from before that first night they found themselves without a space of their own; if you ask enough people, you will begin to see patterns emerge and be able to break down structural barriers.
OSAH: In your view, what has been driving recent efforts to reduce and eliminate homelessness for specific populations?
CS: Dennis Culhane and his colleagues have a lot of papers studying high utilizers, people experiencing chronic homelessness, who are using the system more than the average person experiencing homelessness—It can become expensive quickly. Costs such as ambulance rides, emergency room visits, police interactions, and shelter occupancy add up. This is why chronic homelessness is a population of interest for programmatic interventions. I don’t think it’s a coincidence that chronic homelessness and veterans are the two populations with the most initial focus for policymakers and in initiatives like the 100,000 Homes Campaign and Built for Zero led by Community Solutions. It’s easier to get buy-in across the aisle. Chronic homelessness for the cost factors and veterans because they served their country and people broadly agree they should benefit from additional support. Youth and families with children have been other populations people can get behind. But, people experiencing homelessness as individuals are the largest group experiencing homelessness in the U.S.
OSAH: Your research documented many positive, community-wide outcomes following reductions in veteran and chronic homelessness. How did local stakeholders respond to these types of benefits?
The interesting part about that—during the interviews with local stakeholders, some of them were more aware of the reduction than others. Part of that is because they didn’t end homelessness entirely; they still have people who need an ambulance ride, for example. But here is where the data really becomes valuable. You can see the results when there is a concentrated effort to end homelessness for a specific population; you can see the impact through the numbers. Contacts with other social services are diminishing, for example, which reinforces that the progress is real. I think the place that is most salient is the health system with the number of E.R. overnight stays and the number of ambulance rides—It’s very tangible and concrete. Improvements also seem more salient when the reduction is tied to a specific area. It’s also important to note that a community will experience both short term benefits and longer-term benefits. In the longer term, for example, tourism may grow with a reduction of homelessness, as can public transportation ridership. These may be harder to attribute directly to reductions in homelessness, than the number of E.R. overnight stays in the past six months.
OSAH: What can we extrapolate in terms of benefits from the dramatic reduction in Veteran homelessness over the last decade?
CS: Let’s back up. When it comes to the value of ending homelessness for any population, I think the first value is that it shows its possible. I think that lesson itself can be extended to other populations, and we can extrapolate that, for sure. I think that is the largest value-add—people thinking it’s possible. The other thing is that by focusing on one group that everyone can agree on—such as veterans—you start to form alliances and partnerships that didn’t exist before, making connections that weren’t there. I really feel like it’s the siloes, siloes create gaps, and these partnerships close the gaps. That can help with other populations as well and even in prevention.. For our Veteran inflow project, some providers hadn’t ever reached out to partners previously or even thought to before their pilot program.
OSAH: What should be emphasized to make future improvements related to Veteran Homelessness?
CS: First, the importance of opening lines of communication between agencies, so they are not just diving into action before they know if the solution is going to work. Second, the importance of affordable housing. When we reviewed interviews with veterans experiencing homelessness, it was interesting to hear their stories on what started this cycle to begin with. Things like the loss of a loved one, loss of family who had owned the house they lived in; there was a breakdown and not enough support to stabilize them, and the cycle started. If you are just one family member’s situation away from homelessness, that says a lot. There is a recent push to expand the HCV program which is long needed, but we can’t ignore the shortage of affordable housing, the eviction crisis, the missed opportunities engaging in prevention at other institutions that are upstream. There is a lot of room for improvement in prevention.
We know it’s possible to end homelessness for a group. The question becomes: is it important enough to make that choice, to invest resources in reducing and ending homelessness? Ultimately, it’s a resource issue. There are a lot of services out there, and people don’t always know how to access them, so making sure that the people you are trying to serve know what is available to them is important, but also funding those services is important so there aren’t any gaps.