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What is the Quality Data Foundations Toolkit?
- Overview
- Resources
- Data Quality
- Deduplication
- Inactivity
- Outreach Coverage
- Provider Participation
- Tracking List Statuses
- Tracking Population Statuses
- Unassessed
Unassessed
Tracking those who have declined services
Question 5
Is my by-name dataset able to track single adults who have not consented to services or have not been assessed, but are actively experiencing homelessness?
The resources on this page will dig deeper into how a community can effectively count and track single adults who are actively experiencing homelessness, but who have not yet been assessed, consented to services, or signed a release of information (ROI) to be included in the by-name dataset (BND). Question 5 of the scorecard asks how communities can most effectively ensure that all single adults who are actively experiencing homelessness be accounted for, regardless of their assessment and ROI status.
It is important to note that the purpose of the All-Singles Scorecard is to zoom in on single adult individuals and adult households experiencing literal homelessness. This does not mean you should not consider how families and youth experiencing homelessness are tracked and identified in your system. However, when you evaluate the scorecard question on tracking folks who have not consented to services or have not been assessed, you will want to answer those questions specifically for the single adult population.
What is Built for Zero’s approach to individuals who have declined services or have not yet been assessed?
For the purpose of this standard, BFZ is using “Unassessed” as an umbrella term for understanding how to include individuals identified as experiencing literal homelessness in your by-name dataset when they have chosen to not engage in services or not yet engaged with services, including assessment and information sharing.
Why does tracking people who have not been assessed or declined services matter?
Quantifying homelessness inclusively
To reduce and solve homelessness, and truly understand the extent and dimensions of homelessness, a community must account for everyone that they can identify. Tracking and counting only those people who are currently engaged in services leaves people behind. Regardless of their level of engagement, all people experiencing literal homelessness need to be included in the community’s by-name dataset, just as they would be counted in the annual Point-in-Time count.
To accurately understand homelessness in a community, it’s essential to track everyone, not just those who have engaged in housing services. This comprehensive approach allows for a more effective tailoring of services. For instance, if a significant number of single adults have not been assessed, it may indicate that emergency shelters and street outreach teams lack the necessary resources and capacity to conduct these assessments. On the other hand, if a substantial number of single adults decline services, it could highlight a need for enhanced training in trauma-informed care, person-centered approaches, or rapport-building strategies. Recognizing these patterns is crucial for developing a more inclusive and effective homeless response system and acknowledges that addressing homelessness often requires more than just providing housing.
As your community develops plans for achieving the goal of functional zero, you want to be confident that you have an accurate count of all people experiencing homelessness. When considering how your community will work toward functional zero, considerations around working with folks who are not able to or ready to engage in services are critical, and knowing who those individuals are is the first step.
How can my community account for people who have not been assessed or consented to services?
A community’s specific approach to tracking individuals who have not consented to services or been assessed should be thoroughly documented to ensure a shared understanding across community providers. Practices should include the opportunity for progressive engagement so that any person for whom the necessary information to determine population or sub-population status has not been collected is still included in the community’s actively homeless numbers (likely as part of the All Singles or system-wide data), and can be engaged accordingly over time.
Tracking individuals who have not consented to services
When a service provider encounters someone who is literally homeless, but has not consented to services, there are a variety of ways that person can be included in the by-name dataset. One approach is to use a “non-consent form” — an internal document that collects minimal information — that can be used by providers to track folks who have not consented to services but are known to be experiencing literal homelessness. Another approach is to use anonymous information to identify the individual, either outside of HMIS or in an anonymous HMIS entry. Whichever method a community chooses to collect information on individuals experiencing literal homelessness who have not consented to services, the naming convention and data-entry practices should be consistent.
Tracking individuals who have not been assessed
Sometimes, even given the best efforts of providers, staff, and the system as a whole, you may encounter and work with individuals who do not consent to the community’s common assessment or simply have not yet, for any reason, completed a full assessment.
For many communities, this may rely on looking at who is enrolled in a project versus who has completed an assessment. Since assessments are often a critical part of building a prioritization list, this can help to highlight how the by-name dataset is different from a prioritization list.
Tracking individuals who have not signed an ROI
If a person is identified as literally homeless but has not signed an ROI to be included in the the by-name dataset, the community should identify a method to account for this person, deduplicating the list to the best of their ability. Basic information about a person can be noted by an outreach worker and not shared with others for the purpose of case management. These individuals can be added anonymously to the the by-name dataset through case conferencing. These processes can look similar to accounting for those who have not consented to services.
What does this look like in HMIS?
According to HUD’s HMIS guidance: “Street Outreach and Coordinated Entry projects may record a project entry with limited information about the client and improve on the accuracy and completeness of client data over time by editing data in an HMIS as they engage the client. The initial entry may be as basic as the ‘Project Start Date’ and a ‘code name; (e.g., ‘Redhat Tenthstreetbridge’) response in the name field that would be identifiable for retrieval by the worker in the system. Over time, the data must be edited for accuracy (e.g., replacing ‘Redhat’ with ‘Robert’) as the worker learns more details, more information about the client is obtained.”
Scorecard Assessment
5: Tracking those who have not consented to services or been assessed
This scorecard question ensures that the community is able to account for all individuals experiencing literal homelessness in their system, even if they have not consented to services, completed an assessment, or signed an ROI. Documenting these practices helps to create a shared understanding of how the community includes everyone who is literally homeless in their by-name dataset.
Scorecard Question
Does your community have a way to track actively homeless individuals who have not consented to services and/or assessment at this time?
Initial Quality Data Threshold
The community has an established method to include individuals in the by-name dataset if they have not consented to services or an assessment that adheres to the data sharing and confidentiality requirements of any applicable community policies.
Sustaining Quality Data Threshold
There are community-wide documented policies and procedures in place that describe the process of how the system is tracking and minimizing duplication of those who are literally homeless but do not consent to services or an assessment in the by-name dataset.
Things to think about:
- If a street outreach organization identifies a person experiencing homelessness, they should document the interaction, ideally by creating a program entry in HMIS, and add information as they gather it over time through progressive engagement — even if this person has not yet been assessed or has declined assessment.
- If a person does not sign a release of information for their information to be shared, an anonymous record can be created in HMIS.
- Consider where else your community might not otherwise be tracking people in your by-name dataset — who’s not making it into your dataset?
Click here for a sample spreadsheet template that can be used to start collecting minimal information about the people who fall into this category. Please make a copy and feel free to use and modify in a way that best fits your community’s needs.
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