2.4 Preventing Family Homelessness

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2.4 Preventing Family HomelessnessSpeaker: Andrew Greer and Marybeth ShinnOne of the keys to ending homelessness is to prevent it from happening in the first place. This workshop will examine the most effective strategies to prevent family homelessness, including using homelessness data to target interventions and partnering with providers serving high-risk families. Presenters will cover a wide array of services and solutions.

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<ul><li>1.TARGETINGHOMELESSNESSPREVENTION SERVICESMORE EFFECTIVELY:INTRODUCING ASCREENER FORHOMEBASEAndrew Greer and Marybeth ShinnVanderbilt University</li></ul> <p>2. Background &amp; Rationale Targeting services to prevent homelessness isdifficult: Numbers of shelter entrants are small and people with many risk factors for shelter entry avoid shelter Prevention should be aimed at those most at-risk of becoming homeless 3. Study Questions Question 1: What was the pattern of shelterentry over time among families who applied forHomebase services? Question 2: What families were at highest riskof entering shelter? Question 3: Is it possible to develop a shortscreening instrument to target services? Question 4: If Homebase adopted bettertargeting, how much more effective might itbe? 4. Data base City provided a database of 11,105 familieswho applied for services between Oct 1, 2004and June 30, 2008 Intake workers interviewed families aboutprogram eligibility and risk factors forhomelessness The City provided administrative data onshelter entry over the next 3 years 5. Risk Factor Domains Demographics Human capital and poverty Housing Disability Interpersonal discord Childhood experiences Previous Shelter Dependent Variable: Time to Shelter Entry 6. Methods: Question 1 What was the pattern of shelter entry? Survival Analysis Technique borrowed from medicine where survival is how long a patient lived after treatment Forus, the end point was not mortality, but shelter entry Questions: how long did people stay out of shelter? (SurvivalCurve) which periods of time were applicants at greatest riskof shelter entry? (Hazard Estimate) 7. Survival and Hazard Curves Survival and Hazard Curves Usedto illustrate survival and hazard rates for subjects over time 8. Results: Question 1 What was the pattern of shelter entry over timeamong families who applied for Homebaseservices? 12.8%entered shelter within three years ofapplying Most families who entered shelter did so shortlyafter applying for services 9. Methods: Question 2: What families were at highest risk of enteringshelter? Survival Analysis Included predictors of shelter entry to seewhich families were most at risk of enteringshelter 10. Results: Questions 2CoefficientHaz Ratio RiskConf Interval directionDemographicsFemale 1.28+1.01-1.63Black1.35.90-2.04 Hispanic1.07.71-1.62 Age .98 -.98-.99 Child under 2 yrs old 1.14+1.01-1.29 # of Children 1.04 1.00-1.09Pregnant 1.24+1.08-1.43Married1.09 .906-1.31Veteran 1.119.54-2.34 11. Results: Question 2Coefficient Haz Ratio Risk Direction Conf IntervalHuman Capital/ PovertyHigh School / GED.85- .75-.96Currently Employed .81- .71-.93 Public Assistance History 1.30 +1.13-1.49 Lost benefits in past year1.14.96-1.35HousingName on lease.816 - .75-.96 Overcrowding or Discord 1.02.87-1.20 Doubled up1.14.93-1.38Threatened with eviction 1.20 +1.04-1.38Rent &gt; 50% Income.93 .79-1.08 Arrears 1.001.00-1.00 Level of disrepair1.02.99-1.05Number of times moved in past1.16 +1.08-1.24 yrCurrent subsidy.85 .68-1.07 12. Results: Question 2Coefficient Haz Ratio Direction Conf IntervalDisability Chronic health probs or1.10 .96-1.26 hospMental illness or hosp .82 .67-1.02 Substance abuse1.22 .95-1.56 Criminal justice 1.11 .92-1.33Interpersonal DiscordDomestic violence.87 .73-1.04History with protective 1.37+1.13-1.66servicesLegal involvement.98 .75-1.28 Av Discord with1.09+1.05-1.13 landlord/household 13. Results: Question 2CoefficientHaz Ratio Risk Direction Conf IntervalChildhood Experiences Teen mother.95 .81-1.10Childhood Disruption index 1.15+1.08-1.22ShelterShelter as an adult (self1.43+1.22-1.66 report) Applied for shelter in last 3 1.63+1.31-2.02 mos Seeking to reintegrate into 1.29+1.06-1.59community 14. Results: Question 2CoefficientHaz RatioRisk Direction Conf IntervalAdministrativeVariables Previous Shelter1.15.89-1.50 # Prior shelter 1.18+ 1.08-1.30 applications Previously found1.10.85-1.43eligible for shelterExited shelter to a.96 .73-1.24subsidy 15. How well does the model work? 16. Methods: Question 3 Is it possible to develop a short screeninginstrument? Eliminatedlocation and administrative variables Eliminated racial categories Omitted variables that didnt contribute reliably toprediction of shelter entry Examined hazard ratios to assign 1-3 points foreach predictor For continuous variables like age, examinedpatterns of shelter entry at different ages todecide on cut points 17. Results Question 3: Screener 1 pointadult Pregnancy Age Child under 2 1 pt: 23 - 28; No high school/GED 2 pts: 22 Not currently employed Moves last year Not leaseholder 1 pt: 1-3 moves; Reintegrating into community 2 pts: 4+ moves 2 points Disruptive experiences in Receiving public assistance (PA) childhood Protective services 1 pt: 1-2 experiences; Evicted or asked to leave by 2 pts: 3+ experienceslandlord or leaseholder Discord (landlord, leaseholder, or Applying for shelter in last 3 household)months 1 pt: Moderate (4 5.59); 3 points 2 pts: Severe (5.6 9) Reports previous shelter as an 18. Methods: Question 4If Homebase adopted better targeting, how much more effective might it be?Compare decisions based on our screening model to:1. Administrative data only2. Current Decisions3. Our full modelConsider the percentage of shelter entrants targeted at different levels of risk 19. Results: Question 4 AccurateModelTargetingRisk Criterion % % Shelter Applicants Entrants Served TargetedCurrent Approach Judged eligible 62.4% 69.1% The intake worker assessment approach gives services to 62% ofapplicants and correctly targets 69% of shelter entrants. 20. Results: Question 4 AccurateModelTargetingRisk Criterion % % Shelter Applicants Entrants Served TargetedAdmin Data Any admin data 13.0% 25.7%Current Approach Judged eligible 62.4% 69.1% People with past contact with the shelter system are at very high risk, butonly 13% of HomeBase applicants have any past contact Giving services to them would reach only 26% of shelter entrants 21. Results: Question 4 AccurateModelTargetingRisk Criterion % % Shelter Applicants Entrants Served TargetedAdmin DataAny admin data13.0% 25.7%Current ApproachJudged eligible62.4% 69.1%Full ModelCutoff based on %62.5% 89.6%of Applicants If we use the full model to target the same proportion of HomeBaseapplicants who currently get services, we do a much better job ofreaching those families who enter shelter We would reach almost 90% of shelter entrants, while the current systemreaches 69% 22. Results: Question 4 AccurateModelTargetingRisk Criterion % % Shelter Applicants Entrants Served TargetedAdmin Data Any admin data 13.0% 25.7%Current Approach Judged eligible 62.4%69.1%Full Model Cutoff based on % 62.5%89.6% of ApplicantsScreener 62.3%88.9% A quick screener does almost as well as the full model Is this the right proportion? Thats a hard question that depends on lotsof factors: How much do prevention or shelter stays cost? What aresome of the other financial and moral costs of homelessness? Howeffective are services? Our data dont answer these questions. But we can say what proportionof shelter entrants are reached at different proportions of applicants 23. Results: Question 4 AccurateModelTargetingRisk Criterion % % Shelter Applicants Entrants Served TargetedAdmin DataAny admin data13.0% 25.7%Current ApproachJudged eligible62.4% 69.1%Full ModelCutoff based on %62.5% 89.6%of ApplicantsScreener 62.3% 88.9%Screener5 or more points 67.8% 91.9%Screener6 or more points 53.6% 84.4%Screener7 or more points 41.6% 73.8%Screener8 or more points 30.5% 61.0% The last lines show what happens when we target people by their risk 24. Conclusions Our short screener can predict likelihoodof shelter entry more accurately thancurrent decisions Prediction is hard: Even at the highestlevels of risk, most families avoid shelter. Determination of the proportion of familiesto serve is a question of available fundsand costs, both to the homeless servicesystems and to society. 25. Recommendations Workers should be able to override therecommendation of the model with writtenexplanations Although this exact screener may not workas well in other locations, the methods canbe shared Any model should be tested periodically tosee if it misses recently vulnerablepopulations </p>

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