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APHA Scientific Session and Event Listing

Recorded presentation

Stephen R. Poulin, MSW, Center for Mental Health Policy and Services Research, University of Pennsylvania, 3535 Market Street, Room 3107, Philadelphia, PA 19104, 215 615-0399, srpoulin@yahoo.com

With the support and encouragement of the US Department of Housing and Urban Development (HUD), a rapidly increasing number of communities are implementing homelessness management information systems (HMIS). An HMIS is a centralized computer database that records the utilization of services by homeless individuals. The data maintained by an HMIS typically records the use of emergency shelters, transitional housing, and permanent supportive housing.

In July of 2004, HUD issued regulations that require the fourteen specific “data elements” to be collected by all homeless services agencies receiving HUD funding. These include personal identifying information, veteran status, prior residence information, and program entry and exit dates. With the personal identifying data collected within an HMIS, unduplicated counts of homeless persons using services can be obtained for any specified period of time. The demographic and circumstances of homelessness information collected can be used to produce profiles of homeless persons using shelter. Program entry and exit dates allow one to calculate the number of days spent in shelter.

The session will include a review of research that has already been conducted with HMIS. The session will also review the types of statistical analysis that can be conducted with HMIS data. Drawing on his 8 years of experience as a trainer for SPSS, Inc., the session presenter will use simulated HMIS data to demonstrate the following statistical techniques available in the SPSS statistical software program: • Linear, binary logistic, and multinomial logistic regression • Cox regression (an event history technique) • Time-series analysis • ANOVA

Learning Objectives: At the conclusion of the session, the participant in this session will be able to

• List at least five types of data elements that should be expected in homelessness management information systems (HMIS);
• Describe at least two examples of research that could use HMIS data to evaluate a policy intervention;
• Describe at least three types of statistical techniques that can be used with HMIS data;

Keywords: Homelessness, Research

Presenting author's disclosure statement:

Any relevant financial relationships? No

Recorded presentation