PIT Count Planning and Analysis Aided by Open Data and Open Source Tools
Presented at: NHSDC, Nashville, TN
Presented on: 04/17/2019
The planning process for conducting an accurate point in time homeless count in larger regions such as Texas Balance of State, King County, and Dallas can be a daunting undertaking. Like any large project, it is often best to break this work down into manageable tasks and to use lessons learned by others to help inform the process. In this presentation, we will provide an overview of how open source and free tools can be utilized alongside both open and private data sets to inform the entire count process. Topics covered include recruiting volunteers, using historical data to establish count routes, creating balanced count teams, monitoring the count, establishing a sampling and enumeration methodology (if needed), and using open source tools such as QGIS and Tableau, and using open data sets such as US Census and the HUD GIS Tools to analyze the data for racial disparities.
Racial Disparities Analysis Using Data from Homeless Response Systems
Presented at: NHSDC, Nashville, TN
Presented on: 04/16/2019
In response to one of HUD’s questions from the 2019 CoC funding application, our team analyzed how equitably our CoC is serving different racial/ethnic groups in terms of receiving homelessness services, prioritizing those services, and housing success rate. We determined that an unbiased homeless system would serve each racial/ethnic group at the same rate that each group experiences homelessness. Using data from the United States Census Bureau and our HMIS, we compared these rates from before and after the implementation of a coordinated entry system to determine if program entry requirements would result in a less biased system. We gathered information on how local systemic discrimination has led to disproportionate numbers of people of color living in poverty and homelessness, compared levels of vulnerability (disability status, VI-SPDAT scores) between the different groups, and studied how the rates at which each race/ethnicity is served differs by housing provider types. Ultimately, we found that we serve all individuals more equally now, but people of color can still greatly benefit from restructuring the social systems that put them more at risk of homelessness. We believe that our method could be of use to other communities looking for a way to ensure equity among the groups they serve.
Rethinking the Homelessness Response Framework
Presented at: NHSDC,, Nashville, TN
Presented on: 04/15/2019
Communities face many common challenges when attempting to effectively respond to the range of housing needs of individuals and families. To overcome these challenges, multiple technical objects, or services, can be integrated into a singular framework. Each service within the framework fulfills a specific functional requirement and works seamlessly with the other services through the adoption of established APIs and data exchange protocols. In this presentation, we share this development practice, known as “Service-Oriented Architecture” (SOA), and have an informed discussion on how this practice might revolutionize our collective approach for responding to homelessness. We highlight how the SOA approach has supported work to measure the impact of natural disasters, identify racial disparities, inform prioritization for coordinated entry, and measure system and project performance.
Refining Coordinated Entry to Better Connect with People Living on the Streets
Presented at: San Antonio Mayor’s Housing Summit
Presented on: 09/18/2018
A key tenet of the Federal Strategic Plan to Prevent and End Homelessness is to create a “No Wrong Door” coordinated entry system. While HMIS is an entry point for the majority of Federally funded projects, there are still several other entry and exit points within a community that HMIS does not cover. Charlotte, San Antonio, and Houston shared a common goal of reducing the number of closed doors and decided to participate in a pilot project aimed at addressing this issue. During this session, we share details on the obstacles that need to be overcome to extend coordinated entry to include street outreach, first responders, and providers that aren’t funded by HUD. This will be followed by an overview of the design, development, and implementation phases that ensued as well as a status update of where each community is within the process of broadening their homelessness response frameworks to be more inclusive.
When CE Best Practices Don’t Work: Setting up CE in Regions with Closed and Fragmented Data Systems
Presented at: NHSDC Conference, Pittsburgh PA
Presented on: 04/18/2018
HUD has required that regions have a Coordinated Entry System in place by January 23, 2018. We’ve seen best practices from many regions who have a single, open, HMIS system and have strong participation rates. What about regions who do not? Some regions have providers that use different HMIS software or don’t use HMIS at all. Others have a compelling need to include first responders and street outreach workers into the CE framework. And then there are the regions with a closed-HMIS that have difficulty when it comes to putting the “coordinated” into “coordinated entry”. Even with all of these components figured out, then there is the need to come to a common agreement on how to prioritize people for housing opportunities that might arise, and what additional assessments should be conducted (if any). During this session we will share the experiences in working with regions for whom the commonly used best practices don’t seem to cut it.
Measuring the Impact of Natural Disasters on the Homeless System
Presented at: NHSDC Conference, Pittsburgh PA
Presented on: 04/17/2018
Collecting PIT data in communities impacted by natural disasters is essential to assure regions are not penalized. Data also helps to further inform recommendations on long-term disaster recovery to the State Agencies so they may better know how to utilize Community Development Block Grant Disaster Recovery funds. By measuring this impact, the disaster results are normalized so that these regions are treated fairly when compared to areas that were not directly impacted. The work is made possible through the adoption of GPS-enabled mobile technologies that enable impacted communities to gather and report geo-spatial information in ways that traditional HMIS or paper-based count methodologies.
