HUD Advanced Homeless Data Users Meeting, New Orleans, LA Karen DeBlasio May 14, 2007 MARHMIS

HUD Advanced Homeless Data Users Meeting Purpose Facilitate peer-to-peer learning between communities who can demonstrate innovative uses of homeless data at the local level for Continuum of Care (CoC): – Planning – Management (i.e. program evaluation); and – Decision making.

Selection of Presenters Communities were asked to respond to a Request for Presenters that was distributed in December Proposals were evaluated on several factors: – New and/or innovative uses of HMIS data for CoC planning, management, or decision making – The quality of the study design, data, and analytic methods. – The appropriateness of fit with other presentations for the meeting.

Presenters were asked… To provide detailed information on: – Description of the research question or problem investigation – The importance of the project to the CoC. – Highlights of data analyzed and relevant findings. – Impact on how the data made a change in the policy, programming, or management decisions at the local CoC level.

Michigan’s Statewide Baseline Report Barbara Ritter The statewide report serves as the baseline for the launch of the state’s 10-Year Plan to End Homelessness Important to view this report as a “proof of concept” that can be used to plan how they will use data to support accountability, planning, and advocacy. Data from over 32,000 records in the HMIS was analyzed to provide a detailed description of the State’s homeless population. Report primarily presents descriptive information on the state’s homeless population and initial (tentative) prevalence data. Given the data quality constraints inherent in a new implementation, the prevalence data is less certain, but will definitely improve over time.

Hawaii State Homeless Service Utilization Report Brian Johnson & Marika Ripke Partnership between Hawaii Public Housing Authority and the Center on the Family at the University of Hawaii Used several years worth of HMIS data to document characteristics of clients/dispel myths (jobless, don’t want to work, etc.) Able to increase funding

Linking HMIS with Mainstream Healthcare Databases for Cost Avoidance Analyses in Virginia Evan Scully & Michael Shank Minimal data from the HMIS (non-identifying information and enrollment date) compared with local psychiatric hospital and other data to determine: – amount of money spent each year for a homeless adult with psychiatric disabilities, – number of days spent in local hospitals and the costs that could be offset by utilizing a housing first approach to intervene before clients were admitted to the hospital.

The Use of HMIS in a Federally Qualified Health Center Dr. Rockelle Rogers & Melissa Pociask Began using HMIS for clients using the prescription program Emergency Prescription Assistance Program (EPAP) anyone that lives in county in need of emergency prescription can access at one of four sites Helped to link individuals to services they may otherwise not have been linked with Increased collaboration between agencies; HCH recently began using HMIS

Using HMIS to Evaluate Homeless Prevention and Assistance Programs Craig Helmstetter & Jamey Burden Non-profit research center (Wilder) partnered with Minnesota Housing Family Homeless Prevention and Assistance Program (FHPAP) 3 program goals: – Prevent homelessness – Minimize length – No return to shelter Tracked returns to shelter Able to document prevention assistance has helped to keep people out of shelter; succeeded in lobbying the state increase prevention resources

Using HMIS Data for Presumptive Eligibility Antoinette Triplett & Deb Little Helps to identify clients potentially eligible for assistance Documents number of clients referred to mainstream resources Screen shows which services client is most likely eligible to receive

Homeless Certification and HMIS Michelle Budzek & Molly McEvilley Electronic homeless certification via HMIS Replaces “paper” documentation Clients carry documentation with them as they move between providers Has helped to increase participation in HMIS Number of homeless in CoC have decreased with electronic certification

Performance Measurement System in DC Darlene Mathews Use data from HMIS to prioritize programs for funding purposes Report card Performance measures developed to parallel HUD goals and outcomes/measures

Using Data to Facilitate Service Coordination and Results Accountability Kevin Breazeale & Matthew Berg Use of a proven research model to develop performance measurement tools Adopted the Friedman Results Accountability Model to establish performance measures for programs serving Philadelphia’s homeless population Informed by data gathered by the HMIS, staff developed performance measures for emergency and transitional programs. The performance measures answer three basic questions: – 1. How much did we do? – 2. How well did we do it? and – 3. Is anyone better off because of our efforts?