Rubric

The Scorecard Rubric

The Quality Data Scorecards are more than just a checklist. They are diagnostic tools to guide system improvement. In practice, each scorecard is a measurement framework that gives communities a structured way to interrogate their system and build confidence that the inflow, active, and outflow metrics they’re producing accurately reflect how people move through the homeless response system.

Quality Data is the milestone communities reach when that confidence is clearly established. It means a community can say, with evidence, that their data reflects the realities of people navigating the system, that everyone experiencing homelessness is included in the by-name dataset, that data is collected and managed consistently across the system, and that the data infrastructure has the logic needed to analyze that movement accurately and reliably.

The scorecard’s three components map directly onto these conditions:

  • Data Contribution confirms completeness: everyone experiencing homelessness in the population of interest is included in the by-name dataset, giving the community a complete unit of analysis.
  • Policies and Procedures confirms consistency: data is collected and managed the same way across the entire system.
  • Data Infrastructure confirms analytical soundness: the community has established shared definitions and the data mechanics needed to track current and historic inflow, outflow, and active statuses, and to disaggregate data for system improvement.

Used this way, each scorecard is the mechanism communities use to build toward Quality Data, giving confidence that their data is telling them accurate information about how people move through the system. Without this level of confidence, it’s difficult to make inferences about the metrics produced. Going through the Quality Data process turns data into a powerful tool for change and system planning. It shows where there are gaps in the system, where people are getting stuck, and helps inform the processes and programs that support the work of measurably reducing homelessness and improving outcomes for people navigating the system.

How to use the rubrics

Each of the scorecard’s three components, data contribution, policies and procedures, and data infrastructure, are broken down further into rubrics that define what it takes to answer “yes” to every scorecard question for a given population. These rubrics were designed to provide the clarity and direction communities need to reach Quality Data for the specific populations they’re focusing on. 

For each scorecard question, the rubric lays out three thresholds: not at threshold, initial threshold, and advanced threshold. More information about each threshold can be found on the Quality Data Standards page. 

The population scorecard rubric can be reviewed alongside the corresponding toolkit sections to help communities determine where they are on their Quality Data journey. This rubric and all guidance in this toolkit will be updated periodically as we continue to refine our understanding of by-name data systems. 

Single Adults Rubric

1A – Data Contribution: Outreach Coverage

Is the geographic coverage of your outreach clearly mapped out, informed by your data, and regularly assessed to ensure you are able to reach all unsheltered individuals within your community?

1B – Data Contribution: Outreach Coverage

Have you coordinated your outreach, ensuring that your outreach teams are deployed at the locations and the times that they are most likely to effectively engage with unsheltered homeless individuals, while minimizing duplication between providers?

1C – Data Contribution: Outreach Coverage

Do you have a documented outreach policy that clearly states how your outreach teams will be deployed and how they work with each other to swiftly connect individuals to their self-determined needs?

1D – Data Contribution: Outreach Coverage

 Do you have consistent, coordinated and reliable outreach and in-reach efforts across your geographic coverage area that gives you confidence that at least 90% of the unsheltered population is captured in your by-name dataset?

2A – Data Contribution: Provider Participation

Are 90% of CoC-funded and non-CoC-funded providers reporting data into your by-name dataset?

2B – Data Contribution: Provider Participation

Are approximately 90-100% of single adults experiencing homelessness served by the providers reporting into your by-name dataset? 

3A – Data Contribution: Provider Participation

Is your by-name dataset able to collect data on all single adults experiencing homelessness in your community, including unsheltered individuals living in a place not meant for human habitation (e.g., street, cars, campsites, beaches, deserts, or riverbeds)?

3B – Data Contribution: Provider Participation

Is your by-name dataset able to collect data on all single adults experiencing homelessness in your community, including individuals in shelters, safe havens, seasonal overflow beds, hotels paid for by homeless providers, or Health Care for Homeless Veterans (HCHV) beds?

3C – Data Contribution: Provider Participation

Is your by-name dataset able to collect data on all single adults experiencing homelessness in your community, including individuals in transitional housing, including VA-funded Transitional Housing?

3D – Data Contribution: Adjacent Systems

Is your by-name dataset able to collect data on all single adults experiencing homelessness in your community, including individuals fleeing domestic violence?

4A – Policies & Procedures: Inactivity

Has your community established a written policy that specifies the number of days of inactivity (i.e., the person cannot be located) after which a person’s status will be changed to “inactive,” and which includes protocols to attempt to locate an individual before they are moved to inactive status?

4B – Policies & Procedures: Inactivity

Does that written policy account for changing an individual’s status to “‘inactive’” based on a client’s verified absence from the community before the specified number of days has elapsed? (e.g., reunited with family in a different community, death, etc.)

4C – Policies & Procedures: Inactivity

Does that written policy account for individuals in your by-name dataset who are entering an institution (e.g. jail or hospital) where they are expected to remain for 90 days or fewer?

5 – Policies & Procedures: Tracking Unassessed

Does your community have a way to track actively homeless individuals (i.e., single adults experiencing homelessness) who have not consented to services and/or assessment at this time?

6 – Policies & Procedures: By-Name Data Management

Does your community have policies and protocols in place for keeping your by-name dataset up to date and accurate, including timelines for provider data submission and ongoing quality assurance protocol?

7 – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track the “homeless/housed status” of all individuals, including the date each status was last changed and the previous status? Homeless status fields should include at minimum: homeless, inactive, and permanently housed.

8 – Data Infrastructure: By-Name Data Management

Does your community’s by-name dataset include a unique identifier (e.g., an HMIS ID) for each individual to prevent duplication of client records and facilitate coordination between providers?

9 – Data Infrastructure: Tracking List Statuses

Does your by-name dataset track the total number of newly identified (not necessarily assessed) individuals experiencing homelessness every month? This figure represents a portion of your monthly inflow.

10 – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track individuals returning to active homeless status within the past month?

11A – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track individuals as they move out of active homeless status, including those who move into permanent housing?

11B – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track individuals as they move out of active homeless status, including those who become inactive, per your inactive policy?

11C – Data Infrastructure: Tracking Population-Based Statuses

Does your community’s by-name dataset track individuals as they move out of active homeless status, including those who no longer meet the population criteria of single adult?

12A – Data Infrastructure: Tracking Population-Based Statuses

Does your community’s by-name dataset track population-based statuses, including: veteran, chronic, youth, and family with minor children?

12B – Data Infrastructure: Tracking Population-Based Statuses

Can your by-name dataset track people with multiple population-based statuses (e.g., chronic homeless status AND veteran status)?

12C – Data Infrastructure: Tracking List Statuses

Can your by-name dataset track historical changes in activity status (e.g., active to inactive, active to housed, etc.)?

12D – Data Infrastructure: Tracking Population-Based Statuses

Can your by-name dataset track individuals who become chronically homeless after they are added to your single adults list?

12E – Data Infrastructure: Tracking Population-Based Statuses

Can your by-name dataset track individuals who are initially assigned chronic or veteran status when they enter your system but later do not meet the criteria for these population statuses?

13A – Data Infrastructure: Equity

Does your community have a way to report data on key demographic characteristics in the by-name dataset for the purpose of understanding and analyzing disproportionality in system outcomes?

13B – Data Infrastructure: Equity

Does your data collection policy and process ensure the accuracy and self-identification of clients’ demographic data?

Youth Rubric

1A – Data Contribution: Outreach Coverage

Is the geographic coverage of your outreach clearly mapped out, informed by your data and regularly assessed, to ensure you are able to reach all unsheltered unaccompanied young people  experiencing literal homelessness within your community?

1B – Data Contribution: Outreach Coverage

Have you coordinated your outreach, ensuring that your outreach teams are deployed at the locations and the times that they are most likely to effectively engage with unsheltered unaccompanied young people, while minimizing duplication between providers?

1C – Data Contribution: Outreach Coverage

Do you have a documented outreach policy that clearly states how your outreach teams will be deployed and how they work with each other to swiftly connect unsheltered unaccompanied young people to their self-determined needs?

1D – Data Contribution: Outreach Coverage

Do you have consistent, coordinated and reliable outreach and in-reach efforts across your geographic coverage area that gives you confidence that at least 90% of unsheltered unaccompanied young people are captured on your by-name dataset?

1E – Data Contribution: Meaningfully Engaging PLEE

Are youth and/or young adults with lived expertise of homelessness involved in conducting your outreach and/or informing your outreach strategies and locations?

2A – Data Contribution: Adjacent Systems

Does your homelessness system have formal or informal agreements and processes in place for coordinating with other key systems to quickly and accurately identify unaccompanied young people within those systems who are experiencing literal homelessness (as defined by HUD categories: 1-Literally Homeless and 4- Flee/Attempting to Flee Domestic Violence), including: Your child welfare system?

2B -Data Contribution: Adjacent Systems

Does your homelessness system have formal or informal agreements and processes in place for coordinating with other key systems to quickly and accurately identify unaccompanied young people within those systems who are experiencing literal homelessness (as defined by HUD categories: 1-Literally Homeless and 4- Flee/Attempting to Flee Domestic Violence), including: Local school districts?

2C – Data Contribution: Adjacent Systems

Does your homelessness system have formal or informal agreements and processes in place for coordinating with other key systems to quickly and accurately identify unaccompanied young people within those systems who are experiencing literal homelessness (as defined by HUD categories: 1-Literally Homeless and 4- Flee/Attempting to Flee Domestic Violence), including: Your juvenile justice system?

3A – Data Contribution: Provider Participation

Are 90% of federally or publicly funded providers (including CoC Program funded providers and RHY providers) serving unaccompanied young people reporting data into your by-name dataset?

3B – Data Contribution: Provider Participation

Are 90% of non-federally or publicly funded providers serving unaccompanied young people reporting data into your by-name dataset?

3C – Data Contribution: Provider Participation

Are approximately 90-100% of unaccompanied young people experiencing homelessness served by the providers reporting into your by-name dataset? 

4A – Data Contribution: Provider Participation

Does the youth section of your by-name dataset include all young people currently experiencing homelessness including: Young people living on the streets or other places not meant for human habitation (e.g. street, cars, campsites, beaches, deserts, or riverbeds)?

4B – Data Contribution: Provider Participation

Does the youth section of your by-name dataset include all young people currently experiencing homelessness including: Young people living in shelter, transitional housing or other time-limited settings?

4C – Data Contribution: Adjacent Systems

Does the youth section of your by-name dataset include all young people currently experiencing homelessness including: Young people fleeing domestic violence?

5 – Data Contribution: Adjacent Systems

Is your community able to track young people exiting the foster care system without stable housing and to ensure that those individuals are added to your by-name dataset if they are experiencing homelessness (as defined by HUD categories: 1-Literally Homeless and 4- Flee/Attempting to Flee Domestic Violence)?

6A – Policies & Procedures: Inactivity

Has your community established a written policy that specifies the number of days of inactivity (i.e. the person cannot be located) after which an unaccompanied young person’s status will be changed to “inactive,” and which includes protocols to attempt to locate the unaccompanied young person before they are moved to inactive status?

6B – Policies & Procedures: Inactivity

 Does that written policy account for changing an unaccompanied young person’s status to ‘inactive’ based on a client’s verified absence from the community before the specified number of days has elapsed? (e.g. reunited with family in a different community, death, etc.)?

6C – Policies & Procedures: Inactivity

Does that written policy account for unaccompanied young people on your by-name dataset who are entering an institution (e.g. jail or hospital) where they are expected to remain for 90 days or fewer?

7 – Policies & Procedures: Unassessed

Does your community have a way to track actively homeless unaccompanied young people who have not consented to services and/or assessment at this time?

8 – Policies & Procedures: By-Name Data Management

Does your community have policies and protocols in place for keeping your by-name dataset up to date and accurate, including timeliness for provider data submission and ongoing quality assurance protocol?

9 – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track the ‘homeless / housed status’ of all unaccompanied young people experiencing homelessness, including the date each status was last changed and the previous status? Homeless status fields should include at minimum: homeless, inactive and permanently housed.

10 – Data Infrastructure: By-Name Data Management

Does your community’s by-name dataset include a unique identifier (e.g. an HMIS ID) for each unaccompanied young person to prevent duplication of client records and facilitate coordination between providers?

11 – Data Infrastructure: Tracking List Statuses

Does your by-name dataset track the total number of newly identified (not necessarily assessed) unaccompanied young people experiencing homelessness every month? This figure represents a portion of your monthly inflow.

12 – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track unaccompanied young people returning to active homelessness within the past month?

13A – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track unaccompanied young people as they move out of active homeless status, including those who move into permanent housing?

13B – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track unaccompanied young people as they move out of active homeless status, including those who become inactive, per your inactive policy?

13C – Data Infrastructure: Tracking Population-Based Statuses

Does your community’s by-name dataset track unaccompanied young people as they move out of active homeless status, including those who no longer meet the population criteria of unaccompanied youth and young adults?

14A – Data Infrastructure: Tracking Population-Based Statuses

Can your by-name dataset track unaccompanied young people with multiple population-based statuses (e.g. chronic homeless status AND veteran status)?

14B – Data Infrastructure: Tracking List Statuses

Can your by-name dataset track historical changes in activity status (e.g. active to inactive, active to housed, etc.)?

14C – Data Infrastructure: Tracking Population-Based Statuses

Can your by-name dataset track unaccompanied young people who become chronically homeless after they are added to your youth and young adult list?

14D – Data Infrastructure: Tracking Population-Based Statuses

Can your by-name dataset track unaccompanied young people experiencing homelessness who are initially assigned chronic or veteran status when they enter your system but later do not meet the criteria for these population statuses?

15A – Data Infrastructure: Equity

Does your community have a way to report data on key demographic characteristics of young people in the by-name dataset for the purpose of understanding and analyzing disproportionality in system outcomes?

15B – Data Infrastructure: Equity

Does your data collection policy and process ensure the accuracy and self-identification of clients’ demographic data?

Family Rubric

1A – Data Contribution: Outreach Coverage

Is the geographic coverage of your outreach clearly mapped out, informed by your data and regularly assessed, to ensure you are able to reach all unsheltered families within your community?

1B – Data Contribution: Outreach Coverage

Have you coordinated your outreach, ensuring that your outreach teams are deployed at the locations and the times that they are mostly likely to effectively engage with unsheltered families, while minimizing duplication between providers?

1C – Data Contribution: Outreach Coverage

Do you have a documented outreach policy that clearly states how your outreach teams will be deployed and how they work with each other to swiftly connect unsheltered families to their self-determined needs?

1D – Data Contribution: Outreach Coverage

Do you have consistent, coordinated and reliable outreach and in-reach efforts across your geographic coverage area that gives you confidence that at least 90% of the unsheltered families are  captured on your by-name dataset?

1E – Data Contribution: Meaningfully Engaging PLEE

Are families with lived experience of homelessness involved in conducting your outreach and/or informing your outreach strategies and locations?

2A – Data Contribution: Adjacent Systems

Does your homelessness system have formal or informal agreements and processes in place for coordinating with other key systems to quickly and accurately identify  family households within the following systems who are experiencing homelessness are accounted for on your  by-name dataset, including: Your victim services provider system (i.e. Domestic Violence system)?

2B – Data Contribution: Adjacent Systems

Does your homelessness system have formal or informal agreements and processes in place for coordinating with other key systems to quickly and accurately identify  family households within the following systems who are experiencing homelessness are accounted for on your  by-name dataset, including: Your local child welfare system?

2C – Data Contribution: Adjacent Systems

Does your homelessness system have formal or informal agreements and processes in place for coordinating with other key systems to quickly and accurately identify  family households within the following systems who are experiencing homelessness are accounted for on your  by-name dataset, including: Your local school districts?

2D – Data Contribution: Adjacent Systems

Does your homelessness system have formal or informal agreements and processes in place for coordinating with other key systems to quickly and accurately identify  family households within the following systems who are experiencing homelessness are accounted for on your  by-name dataset, including: Your local Veterans Administration Medical Center?

3A – Data Contribution: Provider Participation

Are 90% of federally or publicly funded providers serving homeless family households reporting data into your by-name dataset?

3B – Data Contribution: Provider Participation

Are 90% of non-federally or publicly funded providers serving family households experiencing homelessness reporting data into your by-name dataset?

3C – Data Contribution: Provider Participation

Are approximately 90-100% of homeless family households served by the providers reporting into your by-name dataset? 

4A -Data Contribution: Provider Participation

Does your community’s by-name dataset include all family households currently experiencing literal homelessness including: Families living on the streets or other places not meant for human habitation (e.g. street, cars, campsites, beaches, deserts, or riverbeds)?

4B – Data Contribution: Provider Participation

Does your community’s by-name dataset include all family households currently experiencing literal homelessness including: Families living in shelter, transitional housing or other time-limited settings?

4C – Data Contribution: Adjacent Systems

Does your community’s by-name dataset include all family households currently experiencing literal homelessness including: Families fleeing domestic violence?

5A – Policies & Procedures: Inactivity

Has your community established a written policy that specifies the number of days of inactivity (i.e. the family cannot be located) after which a homeless family’s status will be changed to “inactive,” which includes protocols to attempt to locate the homeless family before they are moved to inactive status?

5B – Policies & Procedures: Inactivity

Does that written policy account for changing a homeless family’s status to ‘inactive’ based on a client’s verified absence from the community before the specified number of days has elapsed? (e.g. separated from family, death etc.)?

5C – Policies & Procedures: Inactivity

Does that written policy account for a homeless family on your list who are entering an institution (e.g. jail or hospital) where they are expected to remain for 90 days or fewer?

6 – Policies & Procedures: Unassessed

 Does your community have a way to track actively families experiencing homelessness who have not consented to services and/or assessment at this time?

7 – Policies & Procedures: By-Name Data Management

Does your community have policies and protocols in place for keeping your by-name dataset up to date and accurate, including timelines for provider data submission and ongoing quality assurance protocol?

8 – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track the ‘homeless / housed status’ of all families experiencing homelessness, including the date each status was last changed and the previous status? Homeless status fields should include at minimum: homeless, inactive and permanently housed.

9 – Data Infrastructure: By-Name Data Management

 Does your community’s by-name dataset include a unique identifier (e.g. an HMIS ID) for each homeless family household and each person in each household to prevent duplication of client records and facilitate coordination between providers?

10 – Data Infrastructure: Tracking List Statuses

Does your by-name dataset track the total number of newly identified (not necessarily assessed) families experiencing homelessness experiencing homelessness every month? This figure represents a portion of your monthly inflow.

11 – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track families experiencing homelessness returning to active homelessness within the past month?

12A – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track families experiencing homelessness as they move out of active homeless status, including those who move into permanent housing?

12B – Data Infrastructure: Tracking List Statuses

Does your community’s by-name dataset track families experiencing homelessness as they move out of active homeless status, including those who become inactive, per your inactive policy?

12C – Data Infrastructure: Tracking Population-Based Statuses

Does your community’s by-name dataset track families experiencing homelessness as they move out of active homeless status, including those who no longer meet the population criteria of families experiencing homelessness?

13A – Data Infrastructure: Tracking Population-Based Statuses

Can your by-name dataset track families experiencing homelessness with multiple population-based statuses (e.g. chronic homeless status AND veteran status)?

13B -Data Infrastructure: Tracking List Statuses

Can your by-name dataset track historical changes in activity status (e.g. active to inactive, active to housed, etc.)?

13C – Data Infrastructure: Tracking Population-Based Statuses

Can your by-name dataset track families experiencing homelessness who become chronically homeless after they are added to your families list?

13D – Data Infrastructure: Tracking Population-Based Statuses

Can your by-name dataset track families experiencing homelessness who are initially assigned chronic or veteran status when they enter your system but later do not meet the criteria for these population statuses?

14A – Data Infrastructure: Equity

Does your community have a way to report data on key demographic characteristics in the by-name dataset for the purpose of understanding and analyzing disproportionality in system outcomes?

14B – Data Infrastructure: Equity

Does your data collection policy and process ensure the accuracy and self-identification of clients’ demographic data?