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5.7 From Research to Policy to Action (PPT)

5.7 From Research to Policy to Action (PPT)



The Homelessness Prevention and Rapid Re-Housing Program (HPRP) changed the way many communities think about and deliver housing services. Moving toward a more prevention-oriented approach to ...

The Homelessness Prevention and Rapid Re-Housing Program (HPRP) changed the way many communities think about and deliver housing services. Moving toward a more prevention-oriented approach to homelessness requires an understanding of the benefits and possible drawbacks. Recently, researchers have focused their efforts on the effectiveness of prevention initiatives. This workshop will highlight these studies and discuss the implications at the community-level.



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  • Most of the households interviewed experienced an interim period after losing their housing and prior to entering an emergency shelter during which they stayed with various family members or friends. During this period, most were not connected with any resources to help them to identify long term affordable housing or assist them to address other barriers to housing. Only four of nineteen households indicated making use of Information and Referral from the “211” resource line. Most households had not recently had their own housing. The four households which had recently been residing in their own housing where they were paying rent had lost their housing due to an inability to pay rent. In all four cases the family’s income was inadequate to sustain the housing over time and would have required a longer term rent subsidy in order to maintain them in their current housing.

5.7 From Research to Policy to Action (PPT) 5.7 From Research to Policy to Action (PPT) Presentation Transcript

  • From Research to Policy to Action: Prevention National Conference on Ending Homelessness July 13, 2010 Washington, DC Katharine Gale Consulting Berkeley, CA (510) 710-9176, [email_address]
  • Developing a local prevention system based on local and national research
    • Alameda County’s 10 year plan “EveryOne Home” called for a redoubled emphasis on preventing homelessness
    • In 2008, Everyone Home hired consultants to:
      • Research and describe the current prevention system
      • Look at national literature on prevention to identify best practices
      • Use locally available data to describe the population that needs prevention assistance
  • Our system findings
    • System was fragmented and underfunded compared to demand
    • Prevention programs were generally limited to one-time assistance to households with their own lease who could demonstrate they would be stable in the following month
    • No outcome data was kept to know the impact of any assistance provided
  • Common assumptions of the prevention programs we looked at
    • Households being evicted will become homeless if we don’t help them (so when we do help them we have successfully prevented homelessness.)
    • Households who can’t prove they can stabilize very quickly without assistance are “bad risks.”
    • Households know when they are at risk of homelessness and will seek out help
  • National and local research made us question these assumptions
    • Virtually every entry in the literature points out that while there is a large pool of people who might become homeless at any given time, only a small number of them actually do, and that predicting who will is very challenging!
  • The crux of the matter
    • “ Effective activities must be capable of stopping someone from becoming homeless or ending their homelessness quickly.
    • An efficient system must target well, delivering its effective activities to people who are very likely to become homeless unless they receive help.” (Burt et al. 2007, p.xvii, italics in original)
  • Another way to say it…
    • Prevention programs are faced with the challenge of designing targeting strategies that identify those most-likely to become homeless and then providing those individuals, and as far as possible only them, with support that is sufficient to prevent them from becoming homeless.
    • * Problem: No one knows quite how to do that!
  • Challenge: research showed most evictions don’t lead to homelessness
    • Shinn et. al found that only 20% of families that received eviction notices went on to be homeless: 80% did not
    • They also found that only 22% of families entering homeless shelters had ever had an eviction
    • 44% of families entering shelter had never had their own apartment
  • Challenge: research showed prevention programs may not reach those who most need them
    • Boston Foundation study (2007) compared results of those who received one-time assistance with those who were turned down because program was out of funds:
    • 71% of people who were not assisted retained their housing
    • 79% of people who were assisted retained their housing
    • [Note: This study did conclude that those households not assisted continued to be “unstable.”]
  • My review of locally available data showed similar results
    • The CORE agency in Redwood City (San Mateo County, CA) collected data on those it assisted and those it did not assist with prevention assistance
    • Prevention assistance followed traditional guidelines (one time, must have eviction notice, must be able to retain housing afterwards)
    • Most common reason for being refused assistance was not having adequate ongoing income (i.e. too poor)
  • Comparing those assisted and not…
    • We compared the CORE agency’s database with the largest shelter provider in the same geographic region over a three year period
    • We expected to see a difference in subsequent shelter entries…
    • Results showed a negligible difference in shelter entry rates over three years for those who received and those who were denied the prevention assistance
  • Comparison of shelter entry rates: assisted versus non-assisted . Applied for Prevention assistance Entered Shelter w/in 3 year window % that entered shelter Households that were turned down for prevention assistance 1019 40 3.9% Households that received prevention assistance 243 12 4.9% Total 1262 52 4.1%
  • The “Aha!” For Us
    • Without the data on those turned away we would assume we have a 5% homeless entry rate for those assisted: looks like they are doing pretty good at preventing homelessness!
    • With the data we see we that this program may not be effectively preventing homelessness; don’t seem to be reaching the people who actually become homeless
  • So, where do we find the people who will become homeless?
    • In Alameda County, CA we looked at data in the HMIS system and conducted interviews to find out who is entering shelter
    • We found in HMIS that the smallest number of shelter entries were people who had had their own housing in the seven days prior to entry (5%), while the largest number came from staying with family and friends( 28%)
  • Where do we find the people who will become homeless?
    • The second largest groups came from either another shelter or service site (23%) or a place not meant for human habitation (23%).
    • Other places that were reported were a hotel or motel using own funds (7%) and in an institutional setting such as a hospital, jail, substance abuse treatment program or foster care (11%).
  • Alameda County HMIS data (2008)
  • Going Deeper: Interviews with families in shelter in Alameda County
    • Most reported having stayed with family or friends prior to recognizing a need to seek help
    • All had some past or current relationship to TANF but only two had been assisted by TANF program
    • Few knew of prevention assistance or the 211 hot line: Those few who had called were not successful in getting prevention assistance.
    • None would have qualified for our one-time rental assistance because they could not show they had enough income to sustain their housing
  • Implications of the Alameda County Research
    • We concluded that our programs should target our limited prevention and rehousing resources, especially to those:
      • staying with friends and family
      • staying in hotels and motels using their own resources
      • Receiving TANF
      • exiting institutional care, especially substance abuse treatment programs
      • Losing housing subsidies
    • None of these groups were likely to get help at the time
  • 2009 - HPRP! A big opportunity to make our system better
    • Community meetings used to create program design. People wanted
    • Single point of referral: 2-1-1 phone line
    • Network of Housing Resource Centers across the county
    • Common set of eligibility; no “shopping”
    • Target to those with highest likelihood of becoming homeless
    • Share data, Track results!
  • Incorporating risk factors in our local targeting
    • Looked at HUD risk factors in HPRP notice and our own shelter data
    • We decided to prioritize higher risk living situations and incorporate HUD’s household risk factors in eligibility determination
    • Didn’t prioritize which risk factors more important ( <30% AMI, disability, age of head of household, recent medical event, etc.)
  • First Step: Initial Screening at 211
    • 2-1-1 conducts initial phone screening and asks about current income, housing situation and risk factors.
    • To be referred to a Housing Resource Center caller must meet certain of our top situational criteria (already homeless, doubled up or losing a subsidy) or be otherwise at risk of losing housing and have one or more risk factors
    • 211 enters info into HMIS on all callers with a housing crisis, whether they are referred or not .
  • Second Step: Household assessment further targets financial assistance
    • When household gets referred to the Housing Resource Center further assessment done
    • Check for eligible housing situation and income (verifications of 2-1-1 info)
    • A financial assessment tool is used that attempts to target:
      • Those who really need the assistance, and
      • Those who can be reasonably anticipated to stabilize in the time the program has to work with them
  • Financial Assessment acts like a funnel
      • Score is based on current and past income, housing costs, debt, and barriers such as past housing and legal history
      • 50-65 generally provided one time referrals
      • < 25 generally referred to longer-term programs or shelter
      • People who score in the mid range (25-50) and are eligible are recommended for HPRP or TANF assistance
      • BUT, case managers can override the score if they disagree with the recommendation. We track the original score and the reason for overriding .
  • What will we do with the data?
    • We will review our scoring system for households we assisted and see if there are differences in lengths of stay, amounts of assistance or initial outcomes relative to the scores, the reasons for overrides or other characteristics (we are just starting this process with first 6 months of data…)
  • What will we do with the data?
    • Beginning in the September (we hope), we will have volunteers make calls to some of those screened by 2-1-1 (both those who we assisted and those we didn’t) to determine if they resolved their crisis and how they rate their housing stability now.
  • What will we do with the data?
    • We will look at HMIS beginning in 12 months from start date of program to see who shows up again, and compare return rates for
      • Those who got assisted
      • Those who were “assessed out” at step 2 or disappeared between steps 1 and 2
      • Those who weren’t referred
    • We will look to see if there are differences in homeless entries for the three groups.
  • Late breaking news: Initial findings from score analysis
    • Quick review of 108 closed prevention records shows:
    • - High scores are strongly associated with higher household income (not surprising… part of what tool looks for)
    • - High scorers (avg. 46) had slightly fewer days assistance but more average cost (!)
    • - Higher incomes associated with more days and more average cost (!!)
  • Initial findings from score analysis
    • - Lower scores (avg 35) associated with higher rates of reporting a disability (51% vs. 37%)
    • - Lower scores got slightly longer assistance but a lower total amount of assistance
    • - People who reported a disability got lower amounts of assistance and had shorter stays in program
    • - The average assessment score for singles and families was virtually the same, though assistance was significantly smaller for singles.
  • How will we use our findings?
    • We hope to use the findings from our research on our program to help us refine our targeting and program design
    • Hope to contribute to the national conversation on the efficacy of prevention and the utility of assessment tools
    • Looking for people who want to study our data!!! (The Bay Area is lovely!)
  • More Information on Prevention
    • National Alliance to End Homelessness
      • www.endhomelessness.org
    • HUD Homelessness Resource Exchange www.hudhre.info
    • Alameda County EveryOne Home (including 2008 prevention study and info on county-wide program model) ww.everyonehome.org
    • Me  email: [email_address]