DATA-DRIVEN PARTNERSHIPS: Collaborating Across Sectors and Systems to Improve Housing Stability for Families.
Children with stable housing are more likely to flourish in their development and be healthy later in life. Stable housing also provides a necessary platform for families to realize socioeconomic mobility and to thrive in their communities.
Several types of housing interventions have been developed to meet needs, and many are now being brought to scale through vibrant cross-sector partnerships.
Particularly for families experiencing a range of risk factors, including substance use, mental health disorders, justice system involvement, and intergenerational involvement with the child welfare system, the supportive housing model of deeply subsidized housing combined with wraparound support services is achieving success. In recent years, research has demonstrated that this combination can both prevent and end families' involvement with child welfare systems.
Supportive housing uses a Housing First approach, which prioritizes the rapid provision of permanent housing to households experiencing homelessness or housing instability with minimal pre-conditions or barriers, thus serving as a platform from which families can effectively address the issues that initially brought them to the attention of child welfare in the first place.
The supportive services aim to protect the safety of children while promoting both prevention and sustained recovery from trauma, addiction, mental illness, and housing instability for parents, and the positive growth, development, and socioeconomic mobility of the entire family.
Solutions such as supportive housing that integrate housing and services for families can serve as a platform for delivery of preventive services and other evidence-based practices and interventions included in state Family First Prevention Services Act (FFPSA) prevention plans. FFPSA has provided a way for states to increase focus on prevention and planning, which can include helping to address housing instability in families through partnerships that rely on data sharing.
Data-Driven Partnerships Across the Child Welfare and Homeless/Housing Systems
Sharing data across child welfare, housing, and homelessness sectors as well as other cross-sector partners can range from an initial one-time match to fully integrating data at the city, county, or state levels. To start, it is important to invest in the initial planning. This requires convening and engaging essential partners to develop shared values, vision, goals, mutual trust, and a formal commitment from all parties to address barriers posed by systemic structures, policies, and resource limitations.
Examples of potential partners to engage include child welfare, housing authorities, homelessness continuum of care (CoC) leads, and other public and private health and human services agencies that provide linkages to physical and behavioral health care, education, economic assistance, early childhood, justice, court programs, legal services, and domestic violence, among others.
It is important to formalize partnership agreements (e.g., through a memorandum of understanding [MOU]) and agree upon a core team that meets regularly. Consider structures that allow leadership participation and decision-making, while also engaging the expertise and skills of others.
A critical first step is to conduct a data-sharing landscape assessment that looks for existing or planned data-sharing agreements, data warehouses, or other sharing structure. Agencies should also identify data that need to be shared, for what purpose, and where they are currently collected and in what context.
Building from a shared vision, goals, and an understanding of the current efforts, partners should then draft their data-sharing plan and outline scope for how data will be used. The plan should account for drafting or revising an approval process associated with data-sharing agreements and consent documents.
While a gap may exist between the current state and the vision and goals developed by the partnership, there are some critical first steps that can be taken. For example, matching data from the homelessness response system to child welfare system data allows identification and engagement of families who are unstably housed with myriad risk factors.
If data matching is not possible, the MOU between agencies around a specific housing initiative can help coordinate care for families; a further step is to implement a corresponding agreement at the client level. Taken further, child welfare agencies could partner with housing and homelessness response agencies, including potential use of their information systems to facilitate assessment and coordination with a community's housing resources.
Strategies for Overcoming Data-Sharing Road Blocks
Myths and challenges to sharing data and information are plentiful. Often agencies will default to a stance of not being able to share any data or information due to privacy/confidentiality laws. In many cases, creating a data-sharing agreement between partners can help to set up parameters and protocols that protect participant privacy under applicable laws.
Partners will need to identify what information is able to be shared, and for what purpose, early in their processes, and get clear leadership buy-in to support getting a data-sharing agreement across the finish line. Ensure a review of release of information, informed consent and/or privacy notices to determine what is allowed to be shared with partners and for which purposes. It may be useful to engage in an exercise that clarifies values toward data stewardship and collaboration during vision and goal-setting processes with your partners. For ongoing data integration, this may be a chance to reduce redundancies in data collection if certain elements can be cross populated, and offers opportunities for future cross-system coordination as use cases are developed.
While a great initial step, matching child welfare and homelessness response system data may not identify all families experiencing housing instability or homelessness. For example, a recent match in Los Angeles between the child welfare and homeless systems found that two-thirds of homeless families had involvement on the child welfare side; however, the match only included those people identifying as families, thus did not pick up single adults in shelter that may have already had children removed.
Furthermore, some families do not access formal homelessness response system resources, or may be turned away due to a lack of shelter availability or not meeting a specified definition of homelessness. Child welfare may find data-quality issues such as an under-report of inadequate housing status due to common challenges such as data-system limitations, agency policy or practice, caseworker training, or caseworker input. To overcome this, we recommend a few practices to improve information on families' housing challenges throughout the child welfare case management process:
1. Embed housing screening questions within child welfare intake or assessment tools
2. Use common housing screening questions across partner agencies/public systems
3. Screen for housing instability at key points throughout the process, not just at initial intake as family circumstances may change.
Understanding and definitions of "housing instability or homeless" are often different depending on the system, and perspectives on risks and needs may also vary by sector. For instance, the education system uses a different federal definition of homelessness than the one used by the homelessness response system through the U.S. Department of Housing and Urban Development (HUD); the biggest difference is that families who are doubled up are not homeless under the HUD definition.
The homelessness response system prioritizes many resources based on factors, such as chronicity of homelessness and health needs. From a child welfare lens, factors such as a lack of stable housing and being at high risk for negative child welfare outcomes may drive decisions about prioritization of limited resources matched to needs. Work together to ensure that even when definitions do not align, enough information about housing instability status is collected to allow cross-sector partners to identify those with significant risks/vulnerabilities that could be mitigated through ready access to integrated housing and services solutions.
Finally, the reality is that data systems may be ancient, not interoperable, and/or agencies may not have the capacity to engage in data matching. Further, geographic coverage differs--a state child welfare agency will find that homeless data will be kept in different databases using different software over several regions across the state. To solve technical capacity issues, a university partner may prove valuable in helping to match data and provide meaningful information.
While the vision and goals of the plan may take time to be fully realized, getting started with a one-time initial match can frame discussions by providing useful information about cross-system overlap, providing a baseline that informs discussions about target population needs and gaps.
In order to improve the housing status of families, child welfare agencies are beginning to coordinate and cross-partner with the homelessness and housing systems. Key to the success of these partnerships is the ability to share data and family information across the various systems. Such sharing is becoming a part of a larger set of actions that form a roadmap to implement and scale integrated housing and services solutions for families we can keep together safely, and away from child welfare involvement.
For more information on supportive housing and how we can help child welfare-involved families find stability and thrive, visit csh.org and lRoofFamilies.org.
(1.) Swann-Jackson, R., Tapper, D., & Fields, A. (2010). Keeping Families Together: An evaluation of the implementation and outcomes of a pilot supportive housing model for families involved in the child welfare system. Retrieved from https://www.csh.org/wp-content/uploads/20U/12/Report_KFTFindingsreport.pdf
(2.) Farrell, A.F., Britner, P.A., Guzzardo, M., & Goodrich, S. (2010). Supportive housing for families in child welfare: Client characteristics and their outcomes at discharge. Children and Youth Services Review, 32(2). 145-154. https://doi.org/10.1016/j.childyouth.2009.06.012
(3.) Pergamit, M., Cunningham, M., Hanson, D., & Stanczyk, A. (2019). Does Supportive Housing Keep Families Together? Supportive Housing for Child Welfare Families Research Partnership. Retrieved from https://www.urban.org/sites/default/files/publication/100289/does_supportive_housing_keep_families_together.pdf
(4.) Foust, R., Nghiem, H.T., Prindle, J., Hoonhout, J., McCroskey, J., & Putnam-Hornstein, E. (2019): Child protection involvement among homeless families, Journal of Public Child Welfare, https://doi.org/10.W80/15548732.2019.1651437
By Kim Keaton and Andrew Johnson
Kim Keaton is the Director of Data and Analytics at CSH (Corporation for Supportive Housing).
Andrew Johnson is a Senior Program Manager and strategic priority lead for children and families at CSH (Corporation for Supportive Housing).
Recent research and innovations in the housing field
* A program created by CSH (Corporation for Supportive Housing) in New York City for families experiencing homelessness and involved with the child welfare system found that supportive housing helps to improve housing stability, promotes recovery from behavioral health conditions and decreases their risk of subsequent involvement with child welfare.
* In Connecticut, a study looking at outcomes for 1,720 families involved with the child welfare system and referred to their Supportive Housing for Families program showed that supportive housing leads to improved housing stability and environment of care for families, and better employment outcomes for parents.
* A multi-site study of a $25-million-dollar federal demonstration of supportive housing for child welfare-involved families looked at models in Connecticut; Broward County, FL; Memphis, TN; Cedar Rapids, IA; and San Francisco, and concluded firmly that supportive housing had ended homelessness for these families and is keeping them housed in a stable environment.
* AECF (Annie E. Casey Foundation)--KidsCount Data Center: https://datacenter.kidscount.org
* CSH Data: www.csh.org/data
* EvictionLab: https://evictionlab.org
* Administration for Children and Families (ACF) memo Child Welfare, CoC, Public Housing Authority (PHA) collaboration and linking admin data
* ACF Comprehensive Child Welfare Information System (CCWIS) guidance related to data sharing
* Child Welfare Information Gateway bulletin
* One Roof
* United States Interagency Council on Homelessness (USICH) Data-Driven Strategies; USICH Family Homeless benchmarks
--https://www.usich.gov/tools-for-action/homelessness-in-america-focus-on-famil i es-wit h-ch ildren/
* Enhancing Coordinated Entry through partnerships with Mainstream Resources--USICH
* HUD notice--January 2017 matched administrative data as option for CoCs to use in the prioritization process for housing.
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|Author:||Keaton, Kim; Johnson, Andrew|
|Publication:||Policy & Practice|
|Date:||Dec 1, 2019|
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