How Data Can Prevent Homelessness

When it comes to making the shift from managing homelessness to preventing it, data has an important role to play. High-quality data arms professionals working in the sector with the information they need to identify young people at risk of homelessness and support those exiting homelessness from never returning. This quick response could relieve many public systems currently impacted by homelessness, including healthcare, justice, child protection, and housing and homelessness.

Yet the use of data to predict and prevent homelessness is not yet the norm.

On February 19, 2021, Making the Shift hosted the third In Conversation webinar with Michael Lenczner, Founding Director of Powered by Data, Matt Parker, VP of Innovation at HelpSeeker, and Robyn Blackadar, President & CEO of PolicyWise, to discuss the use of data and technology to prevent homelessness. The webinar complements the recent call for proposals for research projects on this theme, which is an integral part of the MtS Research Agenda. The key takeaway: the sector is missing out on an important opportunity to reuse data to support prevention activities.

Below are highlights from the discussion to learn more about the role of data in homelessness prevention.

Administrative data: moving from managing homelessness to preventing it

In the context of homeless services, “data” usually refers to information about people experiencing homelessness that is collected by the shelter system and other related agencies. This case management data provides insights into the current state of shelter use, such as the number of days a person has been homeless and general shelter capacity. However, this data does not necessarily provide insight into the predictive factors that contribute to homelessness, such as hospital stays, interactions with the justice system, or familial breakdown.

In contrast, administrative data is collected by the government and other public bodies (e.g., Canadian Institute for Health information) in the course of administering programs and delivering services. Simply put, administrative data is information that is already being collected. For example, when someone goes to the emergency room, a variety of data will be collected about their health history, including blood pressure, if they have access to a primary care physician, etc. All of this information is stored in their electronic health record.

The real value of administrative data comes from matching datasets. Using the example above, imagine linking anonymous health data collected in emergency rooms from young people 13–24 with records of school absences. Combined, these two datasets may provide valuable insight into the number of young people who are not attending school and accessing emergency medical services. Data scientists and researchers can then use this combined data to identify people who may be at risk of homelessness and make recommendations on what services will prevent it from happening. This policy brief from Powered By Data provides case studies on how sharing and linking data is contributing to evidence-based services and policies.

Using data in homelessness requires an appreciation of ethics and inherent bias

While there are many potential benefits to using data to predict, prevent, and end housing instability and loss, there are also risks. Data sharing increases the risk of exposure, as well as the potential for bias.

That is why it is important for legislators and organizations interested in setting up data sharing agreements to consider the risks of exposure and to use frameworks that reduce bias. Principles like OCAP (Ownership Control Access and Possession) are an important framework for respecting Indigenous sovereignty as well as people at risk of or experiencing homelessness.

Expanding information on vulnerable populations also raises ethical questions. Becoming homeless is a traumatic experience that violates a person’s right to housing and privacy. Staff at shelters and drop-in centres are understandably concerned about asking people to reveal more about themselves after undergoing such injustices.

But in most cases, the homeless serving system does not need to expand data collection. Rather, it needs access to data that is already collected, and to use that data to prevent crises. Using existing information to prevent homelessness is arguably more ethical than waiting for a person to access a shelter. There is significant interest and focus on data linkage in healthcare, but these same practices are not being applied to other sectors.

To ensure data sharing agreements honour a person’s right to privacy, design it in partnership with people who have lived experience of homelessness and other important stakeholders, particularly Indigenous partners. For example, PolicyWise collaborated with Home and Health in Calgary to create an ethical information sharing tool that incorporates the Seven Grandfather Teachings.

Take advantage of existing resources in data and technology to prevent homelessness

Many community and front-line organizations do not have the resources and staff required to analyze data and provide recommendations that will inform decisions. To address this barrier, organizations can take a collective approach and leverage existing data infrastructure, organizations, and technology.

Intermediary organizations like PolicyWise and Powered By Data play an important role in connecting organizations with researchers, private sector, and other partners to make sense of information and draw conclusions from it. For example, Robyn and Michael worked with Carleton University on a common approach to create the Build Better Data project. In this project, they are developing standards for data collection with nonprofit organizations so that they will be able to share their data.

Technology can also support different levels of anonymization and analysis so that decision-makers and constituents can be well informed about the risks. HelpSeeker is working on a decision support system that will help community organizations prioritize and interpret data and make better decisions based on best practices.

What’s next

Look out for upcoming research projects supported by Making the Shift that develop a data infrastructure roadmap or that support the use of data to prevent homelessness.