Homeless Management Information System

A Homeless Management Information System (HMIS) is a local information technology system used to collect client-level data and data on the provision of housing and services to homeless individuals and families and persons at risk of homelessness. Each Continuum of Care (CoC) is responsible for selecting an HMIS software solution that complies with HUD's data collection, management, and reporting standards.

SNAPS Data Strategy & Usability

HUD and our Federal partners are committed to assisting communities to end homelessness for individuals and families. Collecting complete and accurate data about homelessness in your communities is a core element to achieve the goal.

The SNAPS Strategy sets out three overarching goals for itself and communities:

  1. Communities use their data to optimize systems of care through making ongoing system performance improvements and determining optimal resource allocation;
  2. Communities operate data systems that allow for accurate, comprehensive, and timely data collection, usage and reporting; and
  3. Federal government coordinates to receive and use data to make informed decisions in coordination with other data sets, across and within agencies.

To end homelessness, communities must be able to analyze data at both the system and project levels and to evaluate their efforts by subpopulation, across project types, and in other ways. Not only must communities continue increasing HMIS bed coverage and improving data quality, they also should be using data to gain a more holistic picture of the communities’ progress toward ending homelessness. To assist with this effort, HUD has produced a number of products and tools to assist communities to improve data quality and engage in system and project-level analysis.

Data Quality

Good data helps a community understand its performance and determine if the right combination of strategies and resources have been deployed. Some Continuums of Care (CoC) may be hesitant to use data because they are not confident in its quality—in other words, they do not know if their data is telling the whole story or providing an accurate picture of what is happening in the community. One of the best ways to improve data quality is to use the data in meaningful ways so that all stakeholders recognize its importance, creating an incentive to improve data quality. The more data is used by community leaders, providers, and others, the more likely they are to continuously improve data quality, which fosters greater assurance in the data that is available for system planning.