Using HUD and Other Data Resources to Help End Homelessness

The U.S. Department of Housing and Urban Development (HUD) has been stressing the importance of using data to inform local decision making and to make changes to local systems of care. However, to understand the full scope of what is going on in each community we need to use traditional Continuum of Care (CoC) data in concert with other homeless data sources.
People experiencing homelessness often touch several public systems and a subset continuously cycle through a variety of costly emergency interventions (i.e. shelters, emergency room visits, hospitalizations, arrests, etc.). These different systems often lack effective methods for identifying persons who are homeless and connecting them to the most appropriate services and housing. Integrating data across these sectors helps target and coordinate care for vulnerable populations and allows communities to better track outcomes to answer key policy questions and inform practice.
As you look at these broader data sources, you should be aware of a few that may help your CoC better understand your local story. In this announcement, you will find HUD data resources and homeless data resources from national and federal stakeholders.
HUD Data Resources:
    The most obvious data that should be at the fingertips of each community is your own Homeless Management Information Systems (HMIS) data, especially the system performance measures. CoCs also have their Point-in-Time (PIT) count and Housing Inventory Count (HIC) data to help them understand who is homeless on a given night and the resources available to serve them.
    If CoCs want to compare their local data to other CoCs, HUD publishes CoC-level HIC and PIT count data back to 2007. HUD recently updated the system performance measures data to include FY 2017 system performance measures data by CoC.
    New Starting in October, CoCs will be able to run Longitudinal System Analysis (LSA) reports from their HMIS. The LSA reports were designed to reduce the data submission burden for CoCs for the Annual Homeless Assessment Report (AHAR) and to provide much greater access to granular data for local data analysis. HUD is confident that LSA reports will be a necessary and effective tool to drive the kind of system change needed for each community to end homelessness. In the future, HUD will provide tools that will help communities use their LSA data for system performance analysis and modeling.
Broad Homeless Data Resources:
    Many communities are using their local school data which broadens the population to include children in school who are doubled up (“Doubling up” can mean many things and sometimes refers to multigenerational households or to people who share housing on a long-term basis in order to save on housing costs). More partnerships are forming to show the intersection of health care and homelessness. Communities across the country continue to see that permanent supportive housing more effectively meets the needs of persons living on the street – especially those who are chronically homeless – and costs less. Similarly, communities are sharing homelessness and criminal justice data to better target people exiting the corrections system before they become homeless.
    On the USAspending website, you can view all federal funding dedicated to homelessness coming into your communities. This website breaks down funding in your CoC by federal agency and the dollar amount provided. It also allows you to look at communities similar to your own for comparison purposes. Another great resource is the Understanding Homelessness website, which allows you to contextualize homelessness data against other community attributes like average bedroom rent, welfare spending, and population density. Adding new layers and facets to your local data helps to understand factors that are impacting homelessness in your communities.
    Geographic or location-based analysis tools are helpful in the effort to end homelessness. ArcGIS tools provided by ESRI, for example, offer an untapped resource for communities. Nearly every county in the country subscribes to this suite of tools that contains map-based tools as well as a webpage platform and a variety of mobile applications that could help with the PIT count, street outreach, and other methods of identifying people who are sleeping outside. A recent article highlighted how the County of Los Angeles is using this tool to inform their efforts to end homelessness.
To help communities better understand what ESRI resources are available and how to identify who in your community already has access, HUD is conducting a webinar on October 22, 2018 from 2:00pm to 3:00pm. Please register for the webinar to attend.
         
Visit the HUD Exchange at https://www.hudexchange.info

How many people are homeless in your community?


On any given night, more than 550,000 Americans are without a home. The Alliance's State of Homelessness in America report sheds light on the population experiencing homelessness, the homeless system's response, and how both are changing over time.

What the interactive report finds: While the vast majority of people experiencing homelessness live in some form of shelter or transitional housing, 34 percent live "unsheltered" in a place not meant for human habitation. Individuals comprise 67 percent of the homeless population and people in families make up the remaining 33 percent.
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Since 2007, homelessness has decreased for most groups across the country, declining overall by 14 percent. The most dramatic decreases have been for veterans, individuals experiencing chronic homelessness, and people living in unsheltered locations.

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Communities across the country respond to homelessness with a variety of housing and services. Over the last decade, they have placed a greater emphasis on permanent housing solutions, which now account for about half of the homeless assistance beds in the U.S.

The State of Homelessness in America report presents data on homelessness down to the state and local level, with detailed information on the change in regional homeless populations over time.

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