This post is the final in a series about the elements of a coordinated assessment and housing placement system (CAHP). This post offers an overview of data collection and communication, which plays a vital role in the housing referral process. We’ll also take another look at Take Down Targets, which are helping to drive results as we push on toward an end to veteran and chronic homelessness
This series has explored the key elements of a well functioning coordinated assessment and housing placement system for ending homelessness in a community. We’ve talked about the overall value of a coordinated system, the importance of assessment (a common way of understanding who is experiencing homelessness and what they need), and the role of navigation and case conferencing to help people get through the housing process as quickly as possible. Today, we turn to the most important quality of a CAHP system–– it is built for learning.
Imagine a community that assesses everyone on its streets by name, works with each person hand in hand to complete each step of the housing placement process, and quickly matches people to the best housing options to fit their needs. We would all agree that a strong CAHP system is designed to do these things. But now imagine that this community has no mechanism in place for evaluating the system it has built -- no way of using all the by-name data it collects, or analyzing and measuring outcomes in line with that data. Despite having a strong system in place, this community would have no meaningful way of improving, or even of identifying potential areas of improvement.
In short, this community would be frozen. It could never perform any better or worse than it performed the day it built its system.
Zero: 2016 communities from Los Angeles to Rhode Island are taking the critical steps necessary to develop a system that will help them achieve and maintain an end to veteran and chronic homelessness by collecting by-name information on their homeless neighbors, streamlining the housing placement process, and removing barriers to entry to get people off the streets and into housing as quickly as possible. But these communities are also designing systems built for learning so that they can change and improve as they go.
By aggregating by-name information gathered during assessments in an actionable, centrally accessible databases, communities can ensure that all local case workers, housing navigators and service providers have access to up-to-date information for every person experiencing homelessness, regardless of when or by whom they were assessed. This database can allow communities to track the progress of individual people toward housing, including the process of obtaining needed documents during case conferencing. Done well, it can also enable tracking of housing vacancies and available resources.
An actionable database can also provide an important benefit to the CAHP system itself: by tracking people through the housing process and aggregating those results, it can provide performance data and identify red flags, whether in the form of populations that are falling through the cracks or specific logjams in the housing process. These flags can help a community know where to focus its improvement efforts.
This is the difference between data for judgment and data for improvement. Data for judgment is data that a community collects and reports but never utilizes. It leads only to a number-- a big picture snapshot, perhaps once or twice a year-- that does little to help a community move specific people through the housing process or fix solvable problems in real time. Data for improvement, on the other hand, allows communities to track their performance and make meaningful, data-informed adjustments. This second type of data enables evaluation, troubleshooting and process improvement across a community’s entire housing placement system, helping communities prioritize resources, identify gaps and ensure that individuals or families experiencing homelessness are referred to housing opportunities that best fits their needs.
Given that preferences, needs and protocols vary by community, the most actionable database should be easy to customize at the local level. The system should be automated and web-based, HIPAA-compliant and ensure that the personal information of each person experiencing homelessness is carefully protected while still accessible to all local agencies involved in the housing process. Some communities have built such a database into their existing HMIS systems. Others have created new, centralized databases designed specifically to facilitate the housing process. Within both approaches, communities have achieved central access across agencies through a shared release of information that all people experiencing homelessness sign at the time of their assessment.
Last month, Zero: 2016 communities confirmed and committed to their Take Down Targets, establishing one of the most integral pieces of data in their efforts to end homelessness. These targets represent the total number of veterans experiencing homelessness who will need to be connected to permanent housing in order to end veteran homelessness by the end of this year, and the total number of individuals experiencing chronic homelessness who need to be connected to permanent housing in order to end chronic homelessness in these communities by the end of 2016.
Once these Targets are established, communities can set monthly housing placement goals by determining how many veterans or people experiencing chronic homelessness need to be placed in permanent housing each month in order to in order to stay on track toward their goals of ending veteran and chronic homelessness within the Zero: 2016 timeframe. Actionable databases, optimized for system-wide learning, are among the most powerful tools for tracking progress toward a community’s Take Down Target and making course corrections.
A Housing System Built for Zero Series: