Bridging the Research-Provider Gap
Presenters:
Donna Haig Friedman, Ph.D., Massachusetts/Center for Social Policy
David A. Patterson, Ph.D., Tennessee/University of Tennessee-Knoxville
Craig Helmstetter, Ph.D., Minnesota/Wilder Research Center
National HMIS Conference
September 14th and 15th, 2004
Chicago, IL
Sponsored by the U.S. Department of Housing and Urban Development
1
Public policy to address homelessness is
best informed when homeless
assistance providers and researchers
work together in mutually beneficial
ways.
The partnership can be a bridge for social
change that imbeds the real world
experiences of homeless persons and
providers into policy debates and
choices.
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2
Overview of session
Why create a partnership with researchers?
What are the potential benefits?
What are the potential functions for a university or
research partner?
What are some models of collaboration?
What might a CoC consider in choosing and
creating a partnership with researchers?
Questions to ask potential research partners
Three examples of research partnerships:
Massachusetts, Minnesota, and Tennessee
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Why create a partnership with researchers?
HMIS implementations demand a huge investment by
all involved, including the creation of a technological
and research infrastructure.
Researchers can help build the capacity of the
system and maximize the impact of the whole effort.
A public service mission is shared in many instances.
Researchers bring expertise in:
z
z
z
z
Human subjects protections
Sampling techniques
Sound data collection approaches
Sound data analysis approaches
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What are the potential benefits of such a partnership?
Benefits for clients: Privacy protections in
data collection, sharing, storage, analysis and
reporting; access to data for advocacy;
involvement in HMIS planning and policy
decisions; training case managers in
sensitivity to clients
Benefits for case managers: Skill
development in interviewing, data entry,
analysis and reporting
Benefits for Programs/Organizations:
Systematic, standardized data collection and
analysis as a vehicle for program evaluation
and development
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What are the potential benefits of such a partnership?
Benefits for CoC leads and their partner
organizations: Access to sound data useful for
system-wide planning, outcome measurement,
advocacy, and impact
Benefits for research community: Building a body
of knowledge over time; fulfills public service missions
of public and/or nonprofit research centers
Benefits at the community/policy making level:
Relative objectivity; sound data for policy making
purposes that can moderate the ‘numbers battles’ that
typically occur among stakeholder groups (e.g.
legislators and advocates)
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What are the potential functions for an
university or research partner?
Facilitation/collaboration function: Focus is on
creating a collective vision for social change
Research functions: Focus is on soundness of data
collection, data analysis and reporting
Central Server functions: Focus is on ongoing
administration of the Central Server to ensure:
z
z
z
z
24/7 access by homeless assistance users,
data integrity, security, storage and backup
troubleshooting and liaison with software developer
data linkage
Technical assistance functions: Focus is on skill
building and ongoing assistance for homeless
assistance providers and organizations within the
CoC, using the computer system
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What are some models of collaboration?
One or some combination of the four
functions (facilitation, research, central
server administration, technical
assistance) could be undertaken by:
A university-based research center
z Free-standing research center
z A team within a CoC (in-house model)
z An individual researcher/consultant
z
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What steps might a CoC take in determining
which model of partnership to choose?
1.
2.
3.
4.
Develop consensus and document your
community’s hopes and expectations for a
research partnership. Be specific.
Assess in-house expertise and identify areas in
which additional expertise is needed in an
ongoing way or on an “as needed” basis.
Assess resources and costs associated with
various models.
Speak to community representatives who have
partnered with researchers. What worked
well? What would they do differently?
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What steps might a CoC take in determining which
model of partnership to choose? (cont’d)
5.
6.
Approach a few different researchers in your
community and identify those whose work, fees,
resources, interests, and availability best meet your
community needs. Beware of ‘absent minded
professor’ types if you need clear, concise, and
timely deliverables. Researchers don’t always
communicate in laypersons’ terms.
Determine a realistic set of deliverables/timetables
and available resources, and evaluation processes.
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QUESTIONS TO ASK RESEARCHERS:
Has the research group/researcher worked with
community organizations in the past?
Are they interested in the consumers' and providers’
input on data collection, analysis, and reporting?
Who would have access to what data? Clarification
is needed regarding access to client-level (identified
and/or de-identified) and to de-identified summary
data.
What are the benefits to working with him/her/center
(resources of colleagues, students, other work being
done, respectability in the field)?
Are they committed to the community beyond this
work? Is there potential for a sustained partnership
over time?
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THREE MODELS: MASSACHUSETTS,
MINNESOTA AND TENNESSEE
The three communities profiled below
have approached HMIS development in
a very intentional way to promote
community-wide capacity building that:
enhances service delivery and program
development, and
z produces sound research results relevant
for public policy
z
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MASSACHUSETTS
Description of model:
Since 1995, The Center for Social Policy has
performed all 4 functions: Facilitation, Research,
Central Server and Technical Assistance
Data warehouse includes de-identified client-level
data from 260 homeless assistance programs across
the state; CSP staff do not see client-identifiers
Web-tool (www.csp.umb.edu/MassShelter) for
stakeholders to access summary data that meet an
established data coverage standard and to analyze it
themselves; annual data releases for past 5 years
Multiple funding sources
Broad-based Steering Committee with third-party
facilitation
Strong consumer component
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MASSACHUSETTS (cont’d)
Rationale for design
Importance of privacy protections
z Need for neutral, third party (not an
advocacy group; not state government; not
local government)
z University’s public service mission and its
resources
z
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MASSACHUSETTS (cont’d)
Programs and Services
Practitioner skill building: Computer skill
development; understanding of privacy protection issues;
sensitive interviewing techniques
Program/organizational development: Setting up
organizational technology infrastructure and related
organizational cultural changes; systematic data
collection for program planning/evaluation;
understanding of privacy protection issues at
organizational and inter-organizational levels
System building: Aggregate data now available for
informing state’s and City of Boston’s policy making;
national consortium and technical assistance; creation of
policy papers/ white papers re: HMIS implementation
issues now available on HUD website for broad use
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Challenges and CSP’s approaches for
dealing with them in Massachusetts
Technological roadblocks:
z
Providers, whose first priority is direct service, require
computer tools that work well 100% of the time. The
software tools have been problematic at times.
As researchers we want excellent data on as many persons
as possible; as central server administrators, we have not
been able to fully control the user-friendliness of the vendordeveloped software tools.
z
Our approach:
z
z
z
z
Changing software tools; involving end users in the software
selection process
Creating a consortium with other HMIS communities to be a
strong negotiating network with software vendors;
Moving toward more data linkage approaches
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Challenges and CSP’s approaches for
dealing with them in Massachusetts
Resource limitations: Homeless assistance providers and
nonprofit research team (underscore ‘nonprofit’) are both
working with limited resources
z
Our approach:
z Continually leveraged in-kind resources from the
university
z
Start-up stipends in first years; access to other
technology resources through private corporations and
foundations with technology priorities
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Challenges and CSP’s approaches for
dealing with them in Massachusetts
Sensitive nature of data releases in this field:
z
z
z
z
Providers, advocates, and policy makers want the “numbers” to
support their pre-determined priorities.
CSP objectivity, credibility and respectability is completely
dependent upon the trustworthiness of the data we release.
Sometimes these worlds collide.
Our approach:
z Access to data and data release policies that identify criteria for
data releases, including answers to the questions:
z
z
z
z
Who can have access to identified client-level data, de-identified
client-level data, and to de-identified summary data?
What level of coverage is enough to trigger a data release?
What are the core elements of the statement of limitations that will
be included in each data release?
Consumers’, providers’, advocates’, and policy makers’ input
on data collection, analysis, and reporting
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Challenges and CSP’s approaches for
dealing with them in Massachusetts
Timeliness:
z Providers, advocates, policy makers want solid numbers and
easy to understand data releases right away.
z Reaching a high enough coverage level takes time;
participation for providers has been voluntary; Data cleaning,
analysis and reporting takes time.
z
Our approach:
z
z
Inclusionary approach to creating a realistic set of
deliverables/timetables with our funders and the Steering
Committee.
Consumers‘, providers’, advocates’, and policy makers’ input
on draft reports has helped us as researchers to drop our
‘absent-minded professor’ ways of writing ….
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MASSACHUSETTS (cont’d)
Lessons learned
z
The Collective Vision needs to be the
guiding star
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MASSACHUSETTS (cont’d)
Lessons learned (cont’d)
z Managing expectations is a most
important task
z We’re in it for the long haul…..
z Evolving such a project entails
ongoing evaluation, self-reflection
and periodically re-inventing
ourselves
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Tennessee- University Outreach and
Research Model
Context
z
z
Knoxville is a major
metropolitan area in a
largely rural section of
eastern Tennessee.
Population:
z
Knoxville: 173,890
Knox County: 382,032
z
Metro: 687,249
z
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Tennessee- University Outreach and
Research Model
Description of model:
For 18 years Dr. Roger Nooe of The University of
Tennessee (UT) College of Social Work has joined with
Knoxville homeless service providers to conduct research
on the area’s homeless population.
UT College of Social Work’s Office of Research and Public
Service provides staff development, research and
evaluation, technical assistance, and systems engineering.
UT College of Social Work’s Dr. David Patterson has a
background in health care data analysis and research on
application of information technology in the human services.
UT College of Social Work wrote the HMIS grant for the
Knoxville CoC’s and will manage the HMIS deployment and
operations
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Tennessee- University Outreach and
Research Model
A Partnership with Neighbors
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Tennessee (cont’d)
Rationale for design
z
z
z
z
z
Expertise in homeless research, networks and
systems engineering, and data analysis.
Pre-existing relationship with Knoxville Coalition
for the Homeless.
Importance of privacy protections and data
security.
Need for neutral, third party (not an advocacy
group; not state government; not local
government).
University’s outreach, public service, and research
mission.
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Tennessee (cont’d)
Knoxville HMIS is a partnership between…
The University of Tennessee College of Social Work
The Knoxville Coalition for the Homeless
The City of Knoxville
Knox County
and a local/national cable company
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Tennessee (cont’d)
To develop consensus for the Knoxville
HMIS we formed an HMIS Task Force
to develop a vision statement and
review software solutions.
At the time of our Technical Submission
we had 91% our total beds were in
agencies committed to participate in the
HMIS.
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Challenges and UT-College of Social
Work’s approaches for dealing with them
Political roadblocks:
z
z
z
Some of our providers have a long history of competing with
each other for community/donor resources as well as media
attention.
Some initially expressed reluctance to share service delivery
data.
Our approach:
z
z
z
Focused on mutual benefits of collaboration and participation.
Used existing relationships with community power brokers to
encourage agency participation.
Continual encouragement and involvement of providers in
system rollout.
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Challenges and UT-College of Social
Work’s approaches for dealing with them
Resource limitations: Homeless assistance providers and
nonprofit research team (underscore ‘nonprofit’) are both
working with limited resources
z
Our approach:
z Continually leveraged in-kind resources from the
university
z Enlisted local/national cable company in partnership
z
z
Providing broadband access and services to HMIS
participants.
Providing $100,000 over two years in public service
announcements for the Knoxville Coalition for the
Homeless.
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Challenges and UT-College of Social
Work’s approaches for dealing with them
University of Tennessee Grant and Purchasing Related
Policies and Procedures:
z
Created delays in the initial grant application.
Created delays in the Technical Submission.
Created delays in final signing of the HUD Contract.
z
Our approach:
z
z
z
z
Develop and foster our relationships with the staff of the UT
Office of Research.
Practice patience and “mostly kind thoughts”.
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Tennessee (cont’d)
Lessons learned
z
z
z
z
z
Communicate, communicate, communicate.
Leave the ivory tower and attend meetings and
functions of the Coalition to develop and foster
relationships.
Use community power brokers as necessary.
The university’s reputation can open doors to
resources and requisite support.
Ask questions and ask for help.
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Minnesota
Background on research organization
Wilder Research Center (Wilder) is a non-profit
research division of the Amherst H. Wilder
Foundation
Wilder is well-known throughout Minnesota for
applied social research and evaluation, including
research on homelessness:
z
z
Statewide point-in-time survey of people experiencing
homelessness every three years
Among the nation’s first “HMIS” projects, est.1991:
City of St. Paul / Ramsey County shelter database
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Minnesota
Description of model:
Statewide system overseen by a 20-member advisory board
Wilder Research Center performs all 4 functions:
z
Facilitation: Convene advisory group (with board chair) and
facilitate communication between meetings.
z
Research: Understanding of databases, privacy practices, etc., has
informed system development.
z
Central Server: Wilder contracts with software vendor for hosting.
z
Technical Assistance: Minnesota Housing Partnership provides
group training for end-users. Wilder works with agencies, conducts
site-specific training, and serves as help desk.
Status: Implementing for 1 year
z
70 agencies on board (only 200+ to go!)
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Minnesota
Rationale for design
Wilder was already doing HMIS work in one
jurisdiction and wanted to expand and update
system
Wilder’s reputation:
z
z
z
Able to get work done
Politically neutral
Good existing relationships with many providers
and the state
Some advocates were uncomfortable with the
idea of putting this type of data in the hands
of the state
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Minnesota
Programs and Services
Practitioner skill building:
z
End-user training includes primer on data practices and potential
uses of the system for case management and referral purposes
Program/organizational development:
z
z
Informal consultation on client releases, data practices, HIPAA
Formal consultation clarifies reporting requirements (needs &
wishes)
System building:
z
z
Central intake system for Ramsey County (now web-based)
Potential new initiatives:
z
z
z
Collaborative case management for homeless youth
Data sharing among agencies serving homeless veterans
Continuum-wide evaluation in Hennepin County
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Minnesota: Challenges
Resource limitations: Homeless assistance providers and
nonprofit research team (underscore ‘nonprofit’) are both
working with limited resources
z
Our approach:
z Did the best we could with what we had (i.e., simply
cannot do some of what needs to be done)
z Advisory board developed fundraising sub-committee,
which has met with various state officials and the entire
congressional delegation
z Had to threaten high agency participation fees and
suspension of implementation schedule
z Applied for SHP funds only this year
(Note: Now providers are giving us “technical assistance”)
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36
Minnesota: Challenges
The multiple database problem: Providers
are very wary of yet another data system
z
Our approach:
z
Several state programs quickly adopted HMIS
as their reporting tool:
z
z
MN Housing Finance Agency’s Family Homeless
Prevention and Assistance Program
MN Department of Human Service’s Transitional
Housing and Emergency Services Programs
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Minnesota: Challenges
Business model: Used to doing research
projects with a limited time frame and much
less ‘direct service’ to organizations
z Our approach:
Fortunate to have strong and cooperative
board
z Provide as much service as possible
z Answer questions and concerns as quickly as
possible so that bad information does not get
widely circulated
z
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Minnesota: Lessons Learned
Project a budget – then double it
Convene a widely-representative advisory board &
hope for good members:
z
z
z
Board facilitator from Minnesota Housing Finance Agency
has become strong advocate
Board chair has made a huge commitment to fundraising
Board member took on task of drafting policies and
procedures
Record of involvement and useful research pays off
– may be a pre-requisite for direct researcher
involvement in HMIS
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Minnesota: Example of data from Ramsey County
5,000
4,000
3,000
2,000
1,000
Transitional Housing
Emergency shelter
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
0
“23,732 different adults used emergency shelter
in Ramsey County during the years 1991 to 2002”
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Minnesota: Example of data from statewide survey
Number of People in emergency shelters (including domestic violence and
emergency vouchers) and transitional housing programs, October 23, 2003
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Q&A
Panelists take questions from the
audience on Bridging the ResearchProvider Gap
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