Characteristics and Dynamics of Homeless Families with Children. Option 2: Homeless Management Information System

The Homeless Management Information System (HMIS) is a longitudinal, cross-regional study of families using homeless shelters. Using the HMIS universal data elements, the following questions can be investigated:

• Are there regional differences in the number and demographic characteristics of homeless families?
• How large are various subgroups of homeless families, such as families that return to shelters and two-parent families?
• What is the length of stay for various demographic and regional subgroups of families?
• What are the demographic characteristics of families that return to shelter?

Using the program-specific HMIS data elements:

• What are the needs of different subgroups of families?
• What services do homeless families use? Are there differences among various subgroups with respect to their service needs and homeless patterns?
• Is there a relationship between family characteristics, services received, and time until exit and type of destination?

In 2001, Congress directed HUD to provide more detailed information on the extent and nature of homelessness and on the effectiveness of programs funded by the McKinney-Vento Homeless Assistance Act. As a result of this mandate, HUD is requiring each local CoC to develop its own HMIS, a computerized data collection system on homeless individuals and families. As of 2004, there were 444 CoCs operating across the country, with more being established every year. Of these 444 CoCs, 60 percent were already implementing or expanding their HMIS systems, while only one percent were not yet considering any such data collection effort.

By requiring programs and communities to collect demographic, service, and outcome data using standardized data elements, the HMIS system provides a unique opportunity to examine homeless families across programs, providers, and communities. Analyzing HMIS data, particularly from a national sample of CoCs, can help address a number of gaps in what is known about homeless families.

In particular, by showing what services homeless families use and how these services relate to outcomes (such as the length of time a family is homeless, whether they stay out of the homeless system once they leave, and how many exit to more stable housing arrangements), the HMIS data can help allocate appropriate resources to appropriate services. Knowing which families benefit from the various types of services also can inform the development of better treatment matching efforts (e.g., matching families to the appropriate level and intensity of services required).

Using the HMIS universal data elements would help with resource allocation, as these would identify the size and composition of the population to enable resource matching.

Using the program-specific HMIS data elements would help provide data on the following:

• Treatment matching-understand the services and housing needed by particular families to exit homelessness and
• Resource allocation-understand the needs of the population to enable better resource matching.

An advantage of using HMIS data is that the information is already being collected in a number of communities around the country. One problem with the use of such administrative data, however, is that the only information available is that which is already being collected. Although HUD is encouraging CoCs to collect a wide range of information on everyone receiving homeless services, only a smaller set of items is required to be collected on every person. As a result, the knowledge gaps that an analysis of HMIS systems might address will depend upon the comprehensiveness of data collection in the specific HMIS systems examined.

The universal HMIS data elements required to be collected on everyone are as follows:

• Identifying variables (e.g., name, Social Security number);
• Personal identification number;
• Household identification number;
• Date of birth;
• Ethnicity/race;
• Gender;
• Veteran's status;
• Disability status (dichotomy);
• Residence prior to program entry;
• ZIP Code of last permanent address;
• Program entry date; and
• Program exit date.

If only these basic, universal data elements are available, an analysis of HMIS databases from CoCs around the country could provide the following:

• Information on regional differences in the number and demographic composition of homeless families;
• Information on the number and size of some subgroups of homeless families (e.g., two-parent families); and
• Information on the number, size, and characteristics of families that return to shelters after receiving services.

More detailed, program-specific data elements are also collected as part of the HMIS. This information must be collected on all individuals and families participating in various HUD-funded programs, including the Supportive Housing Program, Shelter Plus Care, and Housing Opportunities for Persons with AIDS (HOPWA). CoCs are encouraged to collect this information on everyone tracked in the HMIS, but since this is not mandated, the extent to which this information is available would need to be determined on a case-by-case basis. These program-specific and outcome data elements include the following:

• Income (total monthly and sources);
• Noncash benefits (e.g., food stamps, Medicaid, TANF);
• Physical disability (dichotomy);
• Development disability (dichotomy);
• HIV/AIDS (dichotomy);
• Mental health (if experiencing [dichotomy] and if problem is expected to be long-standing);
• Substance abuse (if experiencing [dichotomy] and if problem is expected to be long-standing);
• Domestic violence (if experiencing and for how long);
• Services received; and
• Destination (for those who leave the homeless system).

If this more detailed information on family characteristics, service use, and outcomes can be obtained, then a study of HMIS databases could also provide the following:

• Information on the needs and services used by homeless families; and
• Information on differences in the types of services used by homeless families and whether these are related to family differences and/or to outcome differences.

Finally, it might be possible in a number of communities to link HMIS data with information from other government databases, such as public assistance or public housing data. This would provide even more information about each family that could be used both descriptively and to better understand what characteristics and services are related to exiting and staying out of homelessness.

Sample. As already noted, by a congressional mandate, HUD is requiring local communities to develop a computerized data collection system. Since 2001, HUD has been working with local jurisdictions to develop and implement the HMIS. Individual CoCs will soon be required to submit information to HUD electronically based on Federal HMIS guidelines published in July 2004. These guidelines outline a set of universal elements that every CoC will be required to collect on all persons receiving homeless services, more detailed information that needs to be collected on everyone receiving services through McKinney-Vento-funded programs, along with a set of additional, recommended data elements.

Individual CoCs will be required to annually submit only aggregate information to HUD, however. As noted earlier, HUD has made it clear that "the HMIS initiative will include no Federal effort to track homeless people and their identifying information beyond the local level." As a result, the Federal guidelines state that "any research on the nature and patterns of homelessness that uses client-level HMIS data will take place only on the basis of specific agreements between researchers and the entity that administers the HMIS."¹⁸ Since it would not be feasible, nor necessary, for a study to coordinate with more than 400 CoCs operating across the nation, a sample of CoCs would need to be created.

To identify CoCs to approach for being in an HMIS study, a stratified, multistage cluster sample would need to be used. The CoCs would first be clustered on the basis of geography (e.g., programs in the South or Northeast), as well as possibly by community size (total population), and estimated size of the homeless population (based on prior research). One important set of criteria would also likely be the extent to which the HMIS is operational in a community, including the number of homeless service providers participating in the HMIS effort and the extent to which detailed information is being collected on everyone in the homeless assistance system. Once various clusters of CoCs have been established based on this sort of criteria, communities could be randomly selected to provide a comprehensive national sample of CoCs and, by extension, homeless families.

This sort of multistage cluster sampling procedure has already been used to select communities involved in the first Annual Homeless Assessment Report (AHAR). Although the AHAR will eventually include information from all CoCs, a sample of 80 communities was selected to provide information for the first annual report. Of these 80 communities, 18 were chosen because they have the largest homeless populations (e.g., New York City, Chicago, Los Angeles). The remaining communities were randomly selected after clustering them by their population size and region. The result is a nationally representative sample of communities.

After a sample of CoCs has been selected, each agency administering the HMIS that agreed to participate in the study would provide client-level data to be analyzed. The data submitted could include retrospective data on people and families already served, as well as periodic updates to enable researchers to track families over time.

Time Frame. The HMIS is designed to track people and families over time and record their history within the homeless service system. As a result, it would be possible to examine families from the beginning of each community's HMIS system. In order to compare results across HMIS systems, however, a common starting point would need to be established. When to set that starting point would be a function of the implementation histories of the HMIS systems in the selected communities.

Another data collection factor that would need to be taken into account, either in selecting communities or determining the starting point for data collection, is the extent of HMIS coverage. In order to be confident in the results obtained from any analyses, the Federal Government recommends that the HMIS cover at least 75 percent of the emergency and transitional housing beds in the community. Since it may have taken each CoC some time to begin collecting information on 75 percent or more of the homeless beds, the date when information can be reliably obtained from an HMIS is, therefore, likely to be later than the date when data collection initially started.

Homeless Management Information System. One advantage of using an administrative database such as the HMIS is that information is being collected on an ongoing basis. Therefore, instead of collecting data through repeated waves of interviews, as is typically done in a survey effort, HMIS data can be collapsed into any time frame desired, such as annually, quarterly, or monthly. There is less flexibility in the extent of information available on each family, or family member, from the HMIS system, however. The universal data elements, listed earlier, are the only variables that will be available on everyone in every community implementing an HMIS. Although this is not a very extensive amount of information, even these data can be used to help address some of the major research questions:

• The percentage of homeless families among the total homeless population in a community;
• Basic descriptive information on homeless families, including the number of people in the household, age of the parent(s) and children, and whether more than one adult is part of the family; and
• Information on the number/percentage of families that return to shelters over whatever time frame can be examined.

More detailed, program-specific data elements can also be collected as part of the HMIS. This information must be collected on everyone involved in various HUD-funded programs, including the Supportive Housing Program, Shelter Plus Care, and HOPWA. The CoCs are encouraged to collect this information on everyone tracked in the HMIS system but, since this is not mandated, the extent to which the information is available would need to be determined on a case-by-case basis. The availability of this more detailed information, also listed earlier, would make it possible to expand the descriptive information available on each family and to create more refined subgroups of families (e.g., families experiencing domestic violence or substance abuse). It would also be possible to examine the services that families received and explore the relationship between services and basic outcomes, such as length of time in the homeless system and whether the family unit, or individual family members, fall back into homelessness over time.

Finally, there are a handful of data elements that are not required for anyone in the HMIS system but that CoCs are encouraged to collect: employment, education, health, pregnancy, more detailed veteran's data, and information on children's education participation. If this level of information is available on most people in the HMIS systems examined, then it would be possible to examine even more closely the relationships among family characteristics, services received, and various types of outcomes, such as finding a job or keeping children enrolled in school.

Other Administrative Data. Another important feature of the HMIS system is that information is collected that can be linked with other databases. Individual CoCs, for example, have been able to link their HMIS records with databases from the following:

• Parole/justice/jails;
• Public assistance (TANF, general assistance, food stamps);
• Public health;
• Health services; and
• Housing (public housing, Section 8 programs).

If these linkages could be established for CoCs involved in a national study, they would provide an opportunity to examine even more about each family. Public assistance records, for example, can help show how many families were receiving services before they became homeless, how many obtained services after becoming homeless, whether public assistance came before or after exiting the homeless system, and whether receipt of public assistance is related to whether a family falls back into the homeless system.

There are a number of advantages to this option:

• Data collection systems are in place in most CoCs in the country;
• There is the ability to maximize the existing HMIS data for study purposes; and
• The cost and burden are relatively low since CoCs are already required to collect this information.

There are also limitations to this option.

Extent of Coverage of Providers Within a Community. Not all homeless service providers necessarily need to participate in the HMIS, and it may take a while for some CoCs to get the participation of most, if not all, providers. To the extent that the HMIS system does not cover all homeless providers, it may miss some homeless families. In particular, there may be biases in the information available because of the lack of participation by certain types of providers. Many domestic violence shelters, for example, have expressed concerns regarding security and client privacy within the HMIS.

Extent of Coverage of Families. The HMIS is limited to providing information on families that receive services from homeless service providers. While it is likely to include most, if not all, families who live in shelters, the HMIS could miss families living in motels, living on the streets, or those who are doubled-up.

Variation in Data Quality. The Federal guidelines provide sites with a great deal of flexibility in how data are collected, including interviews with clients, interviews with staff, review of staff notes, and the like. In addition, many complex variables, such as disability or mental health status, are only grossly measured (Yes/No) and may or may not be based on solid, clinical information. The data also provide little indication of the level of services needed. Finally, the degree to which complete information is available on every person would need to be assessed on a case-by-case basis.

Data May not be Readily Available. As noted earlier, any study that relies on HMIS data would need to negotiate with each individual CoC for access to client-level data. Obtaining approval from multiple CoCs could well be a very cumbersome process and there is no guarantee that any selected CoC will agree to participate in a study. Providing adequate time and resources to establish a good working relationship with any selected CoC is thus likely to be an important aspect of any study involving HMIS records. Furthermore, there is likely going to be a tradeoff in the number of CoCs from which data can be obtained and the depth of information that can be collected. The most detailed studies, those that take advantage of both rich HMIS databases and the ability to link to other databases, can probably be conducted in only a handful of sites at one time, limiting the national representativeness of the study. Conversely, studies that try to use the large number of CoCs operating or developing will likely need to be satisfied with using only the more basic, universal data elements.