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Data and Evaluation Sub Committee 3/8/2016 | 2:00 – 4:00pm| Mercer Island Community Center
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Agenda
2:00 – 2:05
Welcome and Introductions
Hallerman & Bezemer
2:05 – 2:15
Learnings on Vets Consent Rates
Thompkins
2:15 – 3:00
Coordinated Entry for All Measurement
Thompkins/Hickman
3:00 – 3:15
Follow Up on Single Adult Housing Goal Model
Hickman
3:15 -3:55
Overview of Research and Policy at SHA
Bezemer
3:55 – 4:00
Updates
-HMIS transition (Thompkins)
-Others?
Hallerman
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allhomekc.org

3. Improvements in Veteran consent rates for HMIS and CE
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Consent Rates – 2015
Dramatic improvements in veteran consent rates in 2015
74% consent in Q2 2015
98% consent in Q1 2016
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5. Consent Rates - Learnings
Veterans Operational Leadership Team identified learnings in four areas:
Structure and organization
Assessment packets contain all relevant forms
Client information and perceived value
Clearly explain improved communication that occurs when clients consent
Accurately relay information about security, storage, and use
Population- specific
Veterans are accustomed to providing identifying information
Requirements
SSVF requires that enrollees consent
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6. Consent Rates - Message
This is called a Release of Information. By signing this form, you're giving us permission to talk with other agencies and coordinate your entry into housing options for you. We can then all work together to help you find housing. If we talk to other agencies, we will only share information that is directly related to helping to find you housing. We won't share anything else. The purpose and intent of this form is to connect you with housing resources. Refusal to sign the form will limit the coordination of housing options; however, choosing not to sign will not affect your ability to obtain health care services or other supports that exist outside of coordinated entry.
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Discussion
What stands out to you?
What’s replicable to our larger system?
Key takeaways?
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8. Coordinated entry for all: Evaluation & measurement
Intro:
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HUD’s primary goals for coordinated entry processes are that assistance be allocated as effectively as possible and that it be easily accessible no matter where or how people present. Most communities lack the resources needed to meet all of the needs of people experiencing homelessness. This combined with the lack of well-developed coordinated entry processes can result in severe hardships for people experiencing homelessness. They often face long waiting times to receive assistance or are screened out of needed assistance. Coordinated entry processes help communities prioritize assistance based on vulnerability and severity of service needs to ensure that people who need assistance the most can receive it in a timely manner. Coordinated entry processes also provide information about service needs and gaps to help communities plan their assistance and identify needed resources.
HUD Coordinated Entry Policy Brief, February 2015
Before we dive into thinking about the measures that are important for monitoring the impact of coordinated entry, we thought it would be helpful to ground ourselves in the purpose of coordinated entry. This quote is from the HUD policy brief released around this time last year (read quote)
As this quote illustrates, coordinated entry is about system transformation that will
change the way people access the homeless housing system and
will provide us with an opportunity to identify areas where our system may not be meeting the needs of the most vulnerable people in our community.
Because of this, we want to identify measures that will allow us to monitor how Coordinated Entry is impacting how clients move through our system to obtain housing and how our current housing stock and program models are meeting client need, with an eye on evaluating how the system transformation at the heart of Coordinated Entry is contributing to our goals of making homelessness rare, brief and one-time and to addressing disproportionality for minority groups and people of color.
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Prior CE Measurement
Inconsistent schedule and approach across populations
Family Housing Connection, Youth Housing Connection, and Vets
Information in different places
Some from CCS, some from All Home, some from King County Evaluation
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11. FHC – Profile of Families
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FHC - Outputs
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FHC – System Data
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14. YHC – Profiles of Young Adults
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YHC – Vulnerability
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Proposed Framework
Quarterly Updates
Person-centered
Measure experience of the client
Oriented around rare, brief, and one-time measures
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RARE
Number of newly homeless
By Population Type
Young Adults, Families, Singles
By racial/ethnic group
By VI-SPDAT score
By Regional Access Point
Number of clients on the waitlist
Newly homeless would reflect those accessing CEA for the first time and would include all scores upon initial assessment.
Waitlist would reflect only those that are scored >3
(unless we chose to look at all completed assessments and compared statistics in that pool to who is on the waitlist).
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BRIEF
Time from assessment to housing
By Population Type
Young Adults, Families, Singles
By racial/ethnic group
By VI-SPDAT score/housing type
May also consider assessment to program acceptance
Number of clients skipped in referral process
By VI-SPDAT score
Reason for each
Skipped clients – aka the number of clients who were passed over and a lower vulnerability client was housed before them
We also want to track the reason here – what was the justification for skipping this client? Availability of housing stock in their band? They were not eligible for available units?
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ONE TIME
Number and % of referrals to programs that result in a housing placement
By Population Type
Young Adults, Families, Singles
By racial/ethnic group
By VI-SPDAT score
By program
Refusals/denials
Goal: All referrals result in a housing placement (Clients are referred one-time)
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Discussion Questions
Are these measures a good reflection of a system that works for clients?
How can we move toward targets for each of these measures?
What else is essential to know?
Beyond discussion of the proposed measures, we should also consider the following points:
Brief measures:
Should we say “placement” rather than “move-in” since some referrals are made to Rental Assistance programs and wouldn’t move in at the same time as the referral is made. Our system evaluation of RRH would tell us how rapidly people are moved into housing from the time of referral.
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21. Single adult housing goal models
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22. What is a Housing Goal Model?
Chart that allows us to visualize our progress toward the Federal goal of ending homelessness by the year 2020
Tracks how many households we need to house vs. how many households we actually placed in Permanent Housing
Fixed Target based on four components:
Timeframe: 5 years (2016 through end of 2020)
Coordinated Entry Placement Roster (number of households waiting for housing placement)
Number of households in Emergency Shelter and Transitional Housing
Projected monthly inflow of newly homeless households
The goal is to make one model for our entire community, with subpopulation specific models
Fixed target of the number of people we need to house each month in order to reach functional zero by the end of 2020
Thinking that this system-wide measure will replace our current “rare” measure (currently exits to permanent housing from ES, RRH and TH)
We need to estimate the monthly inflow, last month we reviewed a few estimation methods with a lot of variability between the estimations.
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23. Number of Newly Homeless
What if the number of newly homeless people we see in our community each year remains constant?
“Newly homeless” is the number of consenting clients in 2014 who were not enrolled in HMIS programs in 2012 or 2013 (2 years prior)
Assuming a constant number of newly homeless Single Adults (HMIS) to estimate inflow
In 2014, 3523 Single Adults were “Newly Homeless”
(3741 unsheltered ES and TH) + (3523 newly homeless * 5 years) / 60 months = 409 per month
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24. Annualized Point In Time
Based on the Annualized PIT calculation from Corporation for Supportive Housing (Brief 2005), used to project from PIT to an annual estimate of the number of homeless people in a community
Calculated using this formula, can send people the link below to the report PDF if they are super curious:
A + ((B*365/C) * (1-D) = Annual Estimate
A = PIT count of currently homeless (CH) people – (Single Adults in this case)
B = number of CH who were counted in emergency shelters only
C = average LOS for all emergency shelters contributing people to the PIT count.  Average LOS in SA shelters was 62 days
D = correction factor for more than one emergency shelter stay during a 12-month
period, either returning to the same shelter or going to a different one. If you just used C
to project, and did not correct for duplication using D, you would be making the
assumption that new people occupy each shelter bed as soon as it is vacated, and that
every person uses emergency shelter for one and only one spell during the 12-month
index period.
D = .27, equal to # of consenting SA with multiple shelter enrollments in 2015/total # of consenting SA who enrolled in shelter in 2014
Since 49% of consenting Single Adult clients were newly homeless in 2014, is it reasonable to assume that 49% of clients in future years will also be newly homeless?
14,915 Annual Estimate * .49 = 8217 newly homeless each year
(3741 unsheltered ES and TH) + (8217 newly homeless * 5 years) / 60 months = 805 per month
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Zero 2020 Vets Multiplier
Based on 2.03 multiplier we received from Zero 2020 for ending Veterans Homelessness
(3741 unsheltered ES and TH) * 2.03 = Annualized PIT
14106 * .49 = 6912 newly homeless each year
(3741 unsheltered ES and TH) + (6912 newly homeless * 5 years) / 60 months = 692 per month
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Summary of Models
Large variability - Monthly Housing Goal ranges from 409clients to 805 clients depending on estimation method
Estimating inflow by the proportion of newly homeless clients (49% each year) results in highest values
Assuming constant number of newly homeless clients each year (3523) resulted in lower value
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27. Where does this leave us?
No method is perfect, these are rough estimates based on research findings and national guidance
Local expert opinion helps us to “gut check” the inflow estimations we derive from these methods and see if any of these reflect the need that providers and funders see in our community
It may be possible that none of these monthly targets seem to align with need we see in King County, in which case, is it best to wait until Coordinated Entry for All comes online?
Other estimation methods not included here?
Ce for all launches with phase 1 in June, and will implemented in phases– can we wait that long, or should be proceed with one of these?
Is anyone aware of other techniques that would allow us to estimate an annual/monthly inflow?
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updates
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