1. How Do I and Why Would I Share My Data?
Subtitle
Wendy Smith
HMIS System and Implementation Administrator
Portland Housing Bureau- City of Portland
Megan Bolton
Senior Research Analyst
Oregon Housing and Community Services

2. Session Topics
What does it mean to share data, and how can that look different at a local vs. state vs. other level?
What are the different ways to share data?
What are the documents and agreements you need to have in place for secure and transparent data sharing?
What are the benefits to sharing data?
How can you use shared data in your community?

3. Local Data Sharing
So let’s talk about local sharing … sharing data within the software.
Agency’s serving same client using same record
Collecting information and sharing parts or all of the data with a signed-in user from another agency
Coordinated Entry
SubGrantees
Client Consent
Why share data in community
As we know it takes a village to end homelessness. And One agency can’t do it all.
Of course, some data is protected and all data is confidential. The data belongs to the client and depending on our roles, we are caretakers. Perhaps you need it for eligibility….
Are you in a grantee/Sub-grantee relationship?
Are you working with the same client?
Have you referred client to the coordinated entry system?
Perhaps you’ve housed someone from the coordinated entry?
Ending Veteran’s homelessness..
Ending Youth homelessness….

4. Local Data Sharing- Multnomah County

5. Local Data Sharing Who ‘owns’ the data? Whose data is correct?
Provider?
Client?
Whose data is correct?
Who can change data?
Do you need Guidelines?
HUD does not require a community to share data within HMIS, but does encourage it
Can you imagine going to a doctor and pulling our your entire file of visits, lab results, testing, each time you get a referral?
Can we share and still not share – of course there are considerations
RHY data, Minors without adult consent
VAWA for victim service providers
HIV/AIDS
Disability Information (Diagnosis versus client self-report)
Client Consent!
Privacy Notice
Security Officer

6. Local Data Sharing- Multnomah County

7. Data Elements to consider sharing
Client
Demographics
Services
Entries
Assessments
Coordinated Entry
Other

8. Local Data Sharing- Multnomah County

9. State Data Sharing
Vision: Help inform and strengthen a statewide strategy to alleviate the interrelated issues of poverty through the analysis of cross-system data related to homelessness and at-risk populations.
Goals:
Identify cross-system patterns and trends
Assess the impact of investments
Inform funding and policy decisions
Identify gaps and opportunities
Educate the public, elected officials, and policymakers

10. State Data Sharing Integrated Client Services (ICS) Data Warehouse
Created and maintained by DHS/OHA
Mission:
Provide a reliable data source that represents the scope, depth, and interconnected nature of DHS/OHA clients.
Goals:
Provide timely data
Make data accessible
Provide accurate and consistent data
Match clients across systems

11. How Does ICS Make This Happen?
Extract data from existing client-based sources every month: longitudinal data going back to January 2000
De-duplicate clients within and across programs
Geo-code all residential addresses
Standardize data across all sources and transform source data into ICS caseload categories
Maintain a single, consistent, cross-agency view of clients and their services

12. DHS Programs in ICS Aging and People with Disabilities (APD)
Child Welfare (CW)
Intellectual/Developmental Disabilities (I/DD)
Self Sufficiency Programs, including SNAP and TANF (SSP)
Vocational Rehabilitation (VR)

13. OHA Programs in ICS Contraceptive Care (C-Care)
Health Systems-Medicaid (MAP)
Health Systems-Mental Health (MH)
Women Infants Children (WIC)
Vital Statistics – Birth and Death records

14. External Agencies in ICS
Department of Corrections (DOC)
Oregon Housing and Community Services (OHCS)
Oregon Employment Department (OED), Wage data
Oregon Department of Education (ODE), Student index only

15. Variables collected Transformations The person (identified):
Name (identified)
Source ID (identified)
SSN (identified)
DOB
Sex
Race
Ethnicity
Language
The services (identified):
The services/eligibility period/benefit
Source ID (identified)
Case ID (identified)
Start Date
End Date
Branch/Provider ID
Fields used for rules to create caseload buckets
Person’s residence (identified):
Client ID (created by ICS)
Street Address (identified)
Zip
City
County
State
Effective date of address
Transformations
Client Matching
Create caseloads
Address Geocoding
The address (de-identified):
Master ID (de-identified)
Effective date of address
Effective end date
Lat/Long placed inside the polygons for:
Senate District House District County
Congressional District DHS District School District
Flag added for Urban/Rural
The person (de-identified):
Master_ID (de-identified)
DOB (Month-15-Year)
Sex
Race
Ethnicity
Language
DOD
The caseloads(de-identified):
Caseload category code
Master ID (de-identified)
Case ID (de-identified)
Start Date
End Date
Branch/Provider ID

16. What are the Benefits?
Examples of Research Reports from Washington’s Data Warehouse:
Employment Outcomes Associated with Rapid Re-housing Assistance for DSHS Clients in Washington State
Achieving Successful Community Re-Entry upon Release from Prison
Homeless and Unstably Housed K-12 Students in Washington State
Predicting Homelessness among Low-Income Families on TANF
The Housing Status and Well-Being of Youth Aging Out of Foster Care in Washington State
Impact of Housing Assistance on Outcomes for Homeless Families
A Profile of Housing Assistance Recipients in Washington State: History of Arrests, Employment, and Social and Health Service Use
See more at

17. What’s Needed? Agency Participation Agreement
Interagency Data Sharing Agreement
Client Consent/Release of Information
Data Export
What Else?

18. How About You? Is anyone already participating in local data sharing?
What were the challenges in setting it up?
Is data sharing helping you do your job better and/or better serve your clients?
Is anyone already participating in some sort of data warehouse or other data export?
What challenges/successes have you experienced?

19. Questions?