Does Homelessness Preven-on Work: Evalua-on of the NYC Homebase Program - ICPH Conference, 1/17/14

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Does Homelessness Preven-on Work: Evalua-on of the NYC Homebase Program - ICPH Conference, 1/17/14
Does	
  Homelessness	
  Preven-on	
  Work:	
  
Evalua-on	
  of	
  the	
  NYC	
  Homebase	
  Program	
  	
  
	
  
ICPH	
  Conference,	
  1/17/14	
  

                                                           1	
  
Does Homelessness Preven-on Work: Evalua-on of the NYC Homebase Program - ICPH Conference, 1/17/14
New York City Context

    Right to Shelter

Work Supports
  TANF Cash Grant
         Diversion at Intake

   Eviction Prevention         2	
  
Does Homelessness Preven-on Work: Evalua-on of the NYC Homebase Program - ICPH Conference, 1/17/14
Over	
  a	
  million	
  households	
  in	
  
  NYC	
  live	
  in	
  poverty	
  or	
  face	
  
steep	
  rent	
  burdens,	
  threat	
  of	
  
evic:on,	
  and	
  similar	
  housing	
  
  risks,	
  but	
  less	
  than	
  10,000	
  
    enter	
  shelter	
  each	
  year.	
  	
  

                                                   3	
  
Does Homelessness Preven-on Work: Evalua-on of the NYC Homebase Program - ICPH Conference, 1/17/14
Was	
  ini:ated	
  in	
  2004	
  in	
  six	
  communi:es	
  

Non-profit organizations run 14 Homebase offices in
the highest need communities, serving over 10,000
households each year

Flexible service plans including family and landlord
mediation, budgeting, entitlements advocacy,
employment, legal advice and short-term
financial assistance
                                                               4	
  
Does Homelessness Preven-on Work: Evalua-on of the NYC Homebase Program - ICPH Conference, 1/17/14
Program Model
Since 2005, Homebase has served almost 50,000
households    and providedto$24
 8 non-profit organizations    runmillion in financial
                                   11 Homebase
assistance….
 programs in the highest need communities serving
 over 10,000 each year
But how many would have come to shelter if not for
services?	
  
 Flexible service plans including family and landlord
 mediation, budgeting, entitlements advocacy,
 employment, legal advice and short-term
 financial assistance

“Brief” and “full” service model

                                                    5	
  
Does Homelessness Preven-on Work: Evalua-on of the NYC Homebase Program - ICPH Conference, 1/17/14
Need	
  for	
  An	
  Evalua-on	
  

• To	
  determine	
  how	
  targeted	
  and	
  effec:ve	
  
  preven:on	
  programs	
  are,	
  researchers	
  have	
  
  long	
  called	
  for	
  randomized	
  control	
  trials	
  (RCT)	
  
• Program	
  evalua:on	
  results	
  are	
  important	
  
  indicators	
  of	
  the	
  value	
  obtained	
  from	
  
  government	
  programs	
  and	
  expenditures	
  

                                                                      6	
  
In	
  2009,	
  DHS	
  commissioned	
  a	
  comprehensive	
  mul:-­‐
part	
  evalua:on	
  to	
  examine	
  the	
  Homebase	
  
homelessness	
  preven:on	
  program	
  in	
  order	
  to	
  
measure	
  effec:veness,	
  learn	
  how	
  the	
  program	
  could	
  
be	
  improved	
  upon,	
  and	
  contribute	
  to	
  the	
  na:onal	
  
conversa:on	
  on	
  preven:on.	
  	
  	
  	
  
	
  
New	
  York	
  City	
  is	
  the	
  first	
  locality	
  in	
  the	
  na:on	
  to	
  
examine	
  the	
  impact	
  of	
  homelessness	
  preven:on	
  
programs	
  and	
  to	
  develop	
  a	
  research-­‐based	
  risk	
  
assessment	
  to	
  improve	
  targe:ng.	
  	
  
                                         	
  
                                                                                       7	
  
The	
  Comprehensive	
  Evalua-on	
  Study	
  

• Neighborhood	
  shelter	
  trends	
  	
  
• The	
  community	
  impact	
  of	
  Homebase	
  
• Family	
  risk	
  factors	
  that	
  predict	
  
  shelter	
  entry	
  
• Random	
  assignment	
  study	
  

                                                 8	
  
1. What	
  makes	
  a	
  community	
  high	
  risk	
  for	
  shelter	
  entries	
  and	
  is	
  
   Homebase	
  targe@ng	
  services	
  to	
  these	
  high	
  risk	
  communi@es?	
  
   John	
  Mollenkopf,	
  City	
  University	
  of	
  New	
  York,	
  Center	
  for	
  Urban	
  
   Research	
  

2. Do	
  communi@es	
  served	
  by	
  Homebase	
  see	
  a	
  reduc@on	
  in	
  shelter	
  
    entries?	
  Brendan	
  O’Flaherty	
  and	
  Peter	
  Messeri,	
  Columbia	
  Center	
  
    for	
  Homelessness	
  Preven:on	
  Studies	
  

3. What	
  makes	
  a	
  household	
  high	
  risk	
  for	
  shelter	
  entry	
  and	
  can	
  
   Homebase	
  target	
  services	
  to	
  these	
  high	
  risk	
  individuals?	
  	
  
   MaryBeth	
  Shinn	
  and	
  Andrew	
  Greer,	
  Vanderbilt	
  University	
  

4. Do	
  households	
  served	
  by	
  Homebase	
  enter	
  shelter	
  at	
  a	
  lower	
  rate	
  
    than	
  those	
  who	
  are	
  not	
  served?	
  	
  Howard	
  Rolston	
  and	
  Gretchen	
  
    Locke,	
  Abt	
  Associates	
  

                                                                                                      9	
  
Part	
  I.	
  Neighborhood	
  Shelter	
  Trends	
  	
  
What	
  are	
  the	
  neighborhood	
  and	
  familial	
  factors	
  
that	
  contribute	
  to	
  homelessness?	
  

Geo-­‐coded	
  last	
  addresses	
  of	
  families	
  found	
  
eligible	
  2004	
  through	
  2009	
  by	
  census	
  tract	
  

Matched	
  that	
  with	
  extensive	
  range	
  of	
  tract-­‐level	
  
data	
  (socio-­‐economic,	
  housing,	
  etc)	
  from	
  the	
  
2005-­‐2009	
  combined	
  ACS	
  file,	
  residen:al	
  sales,	
  
and	
  assisted	
  housing	
  loca:ons.	
  

                                                                      10	
  
11	
  
Neighborhood	
  Shelter	
  Trends	
  	
  
Findings:	
  	
  Shelter	
  Entry…	
  
• Correlates	
  strongly	
  with	
  race	
  and	
  ethnicity	
  
• Also	
  correlates	
  strongly	
  with	
  poverty,	
  family	
  
  form,	
  marginality	
  
• Correlates	
  moderately	
  with	
  neighborhood	
  
  characteris:cs	
  (rent	
  levels,	
  rent	
  to	
  income	
  
  ra:os)	
  
• Correlates	
  only	
  weakly	
  with	
  changes	
  in	
  
  residen:al	
  sales	
  prices	
  or	
  trends	
  in	
  rent	
  levels	
  

                                                                          12	
  
Part	
  II.	
  Community	
  Impact	
  of	
  Homebase:	
  A	
  Quasi-­‐
                       Experimental	
  
Do	
  communi@es	
  served	
  by	
  Homebase	
  see	
  a	
  reduc@on	
  in	
  shelter	
  entries?	
  
	
  
Would	
  these	
  par:cipants	
  have	
  become	
  homeless	
  in	
  the	
  absence	
  of	
  
preven:on	
  efforts?	
  

How	
  many	
  non-­‐par:cipants	
  became	
  homeless	
  as	
  a	
  result	
  of	
  the	
  
preven:on	
  program—i.e.	
  “musical	
  chairs”	
  

When	
  would	
  	
  par:cipants	
  and	
  non	
  par:cipants	
  have	
  become	
  homeless?	
  
	
  
Did	
  Homebase	
  impact	
  the	
  length	
  of	
  stay	
  for	
  non-­‐par:cipants	
  or	
  
households	
  already	
  in	
  shelter?	
  	
  	
  
	
  
What	
  is	
  the	
  impact	
  of	
  foreclosures	
  on	
  shelter	
  entries?	
  
	
  
                                                                                                 13	
  
	
  
Data	
  
• Anonymous	
  lis:ng	
  of	
  families	
  entering	
  NYC	
  shelter	
  system	
  
  between	
  January	
  2003	
  and	
  November	
  2008	
  	
  
• Separate	
  lis:ng	
  	
  of	
  HB	
  cases	
  opened	
  between	
  November	
  2004	
  
  and	
  November	
  2008.	
  
• Iden:fying	
  informa:on	
  
     – Census	
  tract	
  	
  and	
  community	
  district	
  of	
  residence	
  
     – Month	
  of	
  shelter	
  entry/HB	
  case	
  opened	
  
• Other	
  useful	
  informa:on	
  
     – Official	
  	
  start	
  of	
  HB	
  opera:ons	
  in	
  each	
  CD	
  
     – Length	
  of	
  shelter	
  stay	
  
     – Distance	
  between	
  each	
  community	
  district	
  and	
  closest	
  HB	
  
       center	
  
     – Monthly	
  count	
  of	
  housing	
  units	
  in	
  buildings	
  in	
  which	
  	
  
       foreclosure	
  proceedings	
  were	
  ini:ated	
  

     	
                                                                                       14	
  
Model	
  	
  Design	
  and	
  Specifica-on	
  
• HB	
  effects	
  could	
  be	
  iden:fied	
  because	
  DHS	
  ini:ally	
  limited	
  	
  HB	
  
  services	
  to	
  six	
  CDs	
  in	
  November	
  2004,	
  then	
  expand	
  eligibility	
  
  to	
  31	
  more	
  CD’s	
  in	
  July	
  2007	
  and	
  to	
  the	
  en:re	
  City	
  in	
  January	
  
  2008.	
  

• Complica:ng	
  the	
  quasi	
  experiment:	
  
     – DHS	
  purposely	
  selected	
  high	
  shelter	
  use	
  neighborhoods	
  for	
  
       phasing	
  in	
  	
  CD’s	
  and	
  loca:on	
  of	
  HB	
  centers	
  
     – Great	
  Recession	
  result	
  in	
  secular	
  rise	
  in	
  shelter	
  entries	
  	
  

                                                                                                       15	
  
Results	
  

During	
  the	
  November	
  2004	
  through	
  
         November	
  2008	
  period:	
  
	
  
• Homebase	
  reduced	
  shelter	
  entries:	
  
     	
  Between	
  10	
  and	
  20	
  family	
  entrants	
  were	
  
         averted	
  	
  per	
  100	
  HB	
  cases	
  opened.	
  

                                                                    16	
  
More	
  Results	
  
• Homebase	
  is	
  more	
  effec:ve	
  at	
  aver:ng	
  shelter	
  
entries	
  in	
  higher	
  risk	
  neighborhoods	
  
• Homebase	
  does	
  not	
  cause	
  “musical	
  chairs.”	
  
Shelter	
  entries	
  are	
  not	
  pushed	
  to	
  neighboring	
  
areas.	
  
• Families	
  are	
  not	
  simply	
  delaying	
  entry.	
  
• HB	
  doesn’t	
  affect	
  length	
  of	
  shelter	
  stay.	
  
• For	
  every	
  100	
  Lis	
  Pendens	
  (pre-­‐foreclosure	
  
filings	
  ),	
  between	
  3	
  and	
  5	
  families	
  enter	
  shelter	
  
                                                                           17	
  
Part	
  III.	
  Risk	
  Assessment	
  
	
  
                     A	
  risk	
  assessment	
  tool	
  
	
  
       Who	
  is	
  most	
  likely	
  to	
  come	
  into	
  shelter	
  	
  	
  
	
  
                                                                          18	
  
Study	
  Ques-ons	
  
• Q1:	
  What	
  was	
  the	
  pamern	
  of	
  shelter	
  entry	
  
over	
  :me	
  among	
  families	
  who	
  applied	
  for	
  
Homebase	
  services?	
  
• Q2:	
  What	
  families	
  were	
  at	
  highest	
  risk	
  of	
  
entering	
  shelter?	
  	
  
• Q3:	
  Is	
  it	
  possible	
  to	
  develop	
  a	
  short	
  screening	
  
instrument	
  to	
  target	
  services?	
  	
  
• Q4:	
  If	
  Homebase	
  adopted	
  bemer	
  targe:ng,	
  
how	
  much	
  more	
  effec:ve	
  might	
  it	
  be?	
  
                                                                            19	
  
Data	
  
11,105	
  Homebase	
  families	
  who	
  applied	
  for	
  
services	
  between	
  Oct	
  1,	
  2004	
  and	
  June	
  30,	
  
2008	
  
	
  
Analyzed	
  intake	
  and	
  program	
  eligibility	
  data	
  
for	
  families	
  with	
  children	
  	
  
	
  
DHS	
  provided	
  administra:ve	
  data	
  on	
  shelter	
  
entry	
  over	
  the	
  next	
  3	
  years	
  

                                                                     20	
  
Risk	
  Factor	
  Domains	
  
•   Demographics	
  
•   Human	
  capital	
  and	
  poverty	
  	
  
•   Housing	
  
•   Disability	
  
•   Interpersonal	
  discord	
  	
  
•   Childhood	
  experiences	
  
•   Previous	
  Shelter	
  
•   Dependent	
  Variable:	
  Time	
  to	
  Shelter	
  Entry	
  

                                                                   21	
  
Survival	
  Analysis	
  
What	
  was	
  the	
  pamern	
  of	
  shelter	
  entry?	
  
• Survival	
  Analysis	
  
          – Technique	
  borrowed	
  from	
  medicine	
  where	
  “survival”	
  
            is	
  how	
  long	
  a	
  pa:ent	
  lived	
  aner	
  treatment	
  
   	
  
          – For	
  us,	
  the	
  end	
  point	
  was	
  not	
  mortality,	
  but	
  shelter	
  
            entry	
  
   	
  
          – Ques:ons:	
  	
  
               • “how	
  long	
  did	
  people	
  stay	
  out	
  of	
  shelter?”	
  (Survival	
  Curve)	
  
               • “which	
  periods	
  of	
  :me	
  were	
  applicants	
  at	
  greatest	
  risk	
  of	
  
                 shelter	
  entry?”	
  (Hazard	
  Es:mate)	
  
   	
  
                                                                                                      22	
  
Results	
  -­‐>	
  Q1	
  
What	
  was	
  the	
  pamern	
  of	
  shelter	
  entry	
  over	
  :me	
  
among	
  families	
  who	
  applied	
  for	
  Homebase	
  
services?	
  
     – 12.8%	
  entered	
  shelter	
  within	
  three	
  years	
  of	
  
       applying	
  
     – 	
  Most	
  families	
  who	
  entered	
  shelter	
  did	
  so	
  
       shortly	
  aner	
  applying	
  for	
  services	
  
	
  
                                                                       23	
  
 
           Results	
  -­‐>	
  Q2	
  (Risk	
  Factors)	
  
                                       	
   risk	
  of	
  entering	
  shelter?	
  	
  
What	
  families	
  were	
  at	
  highest	
  
Coefficient	
                                                  Haz	
  Ra-o	
     Risk	
  direc-on	
     Conf	
  Interval	
  

                                            Female	
            1.28	
                   +	
            1.01-­‐1.63	
  
                                                  Age	
          .98	
                   -­‐	
            .98-­‐.99	
  
                     Child	
  under	
  2	
  yrs	
  old	
        1.14	
                   +	
            1.01-­‐1.29	
  
                                         Pregnant	
             1.24	
                   +	
            1.08-­‐1.43	
  
                         High	
  School	
  /	
  GED	
            .85	
                   -­‐	
            .75-­‐.96	
  
                      Currently	
  Employed	
                    .81	
                   -­‐	
            .71-­‐.93	
  
               Public	
  Assistance	
  History	
                1.30	
                   +	
            1.13-­‐1.49	
  
                               Name	
  on	
  lease	
            .816	
                   -­‐	
            .75-­‐.96	
  
              Threatened	
  with	
  evic:on	
                   1.20	
                   +	
            1.04-­‐1.38	
  
 Number	
  of	
  :mes	
  moved	
  in	
  past	
  yr	
            1.16	
                   +	
            1.08-­‐1.24	
  
                                                                                                                          24	
  
 
                        Results	
  -­‐>	
  Q2	
  (Risk	
  Factors)	
  
Coefficient	
                                       	
   Risk	
  Direc-on	
   Conf	
  Interval	
  
                                         Haz	
  Ra-o	
  

 History	
  with	
  protec:ve	
  services	
                1.37	
     +	
           1.13-­‐1.66	
  
           Av	
  Discord	
  with	
  landlord/              1.09	
     +	
           1.05-­‐1.13	
  
                               household	
  
        Childhood	
  Disrup:on	
  index	
                  1.15	
     +	
           1.08-­‐1.22	
  
  Shelter	
  as	
  an	
  adult	
  (self	
  report)	
       1.43	
     +	
           1.22-­‐1.66	
  
 Applied	
  for	
  shelter	
  in	
  last	
  3	
  mos	
     1.63	
     +	
           1.31-­‐2.02	
  
         Seeking	
  to	
  reintegrate	
  into	
            1.29	
     +	
           1.06-­‐1.59	
  
                               community	
  
         #	
  Prior	
  shelter	
  applica:ons	
            1.18	
     +	
           1.08-­‐1.30	
  

                                                                                                      25	
  
 
                           Results	
  -­‐>	
  Q3	
  
                                    	
   a	
  short	
  screening	
  
Is	
  it	
  possible	
  to	
  develop	
  
instrument?	
  
• Eliminated	
  loca:on	
  and	
  administra:ve	
  variables	
  
• Eliminated	
  racial	
  categories	
  	
  
• Omimed	
  variables	
  that	
  didn’t	
  contribute	
  reliably	
  to	
  
  predic:on	
  of	
  shelter	
  entry	
  	
  
• Examined	
  hazard	
  ra:os	
  to	
  assign	
  1-­‐3	
  points	
  for	
  each	
  
  predictor	
  	
  
• For	
  con:nuous	
  variables	
  like	
  age,	
  examined	
  pamerns	
  
  of	
  shelter	
  entry	
  at	
  different	
  ages	
  to	
  decide	
  on	
  cut	
  
  points	
  
                                                                               26	
  
Risk	
  Assessment	
  Screener	
  
1	
  point	
                                                    – Reports	
  previous	
  shelter	
  as	
  an	
  
       – Pregnancy	
                                                   adult	
  
       – Child	
  under	
  2	
                             Age	
  	
  
       – No	
  high	
  school/GED	
                             – 1	
  pt:	
  23	
  -­‐	
  28;	
  	
  
       – Not	
  currently	
  employed	
                         – 2	
  pts:	
  ≤22	
  	
  
       – Not	
  leaseholder	
                              Moves	
  last	
  year	
  	
  
       – Reintegra:ng	
  into	
  community	
                    – 1	
  pt:	
  1-­‐3	
  moves;	
  	
  
                                                                – 2	
  pts:	
  4+	
  moves	
  	
  
2	
  points	
  
       – Receiving	
  public	
  assistance	
  (PA)	
   Disrup:ve	
  experiences	
  in	
  childhood	
  	
  
                                                                – 1	
  pt:	
  1-­‐2	
  experiences;	
  	
  
       – Protec:ve	
  services	
  	
  
                                                                – 2	
  pts:	
  3+	
  experiences	
  	
  
       – Evicted	
  or	
  asked	
  to	
  leave	
  by	
  
         landlord	
  or	
  leaseholder	
                   Discord	
  (landlord,	
  leaseholder,	
  or	
  
                                                              household)	
  
       – Applying	
  for	
  shelter	
  in	
  last	
  3	
  
         months	
                                               – 1	
  pt:	
  Moderate	
  (4	
  –	
  5.59);	
  	
  
                                                                – 2	
  pts:	
  Severe	
  (5.6	
  –	
  9)	
  
3	
  points	
  
                                                                                                            27	
  
Conclusions	
  
• The	
  short	
  screener	
  can	
  predict	
  likelihood	
  of	
  
shelter	
  entry	
  more	
  accurately	
  than	
  subject	
  decisions	
  
(a	
  26%	
  increase	
  in	
  targe:ng	
  accuracy)	
  
• Predic:on	
  is	
  hard:	
  	
  even	
  at	
  the	
  highest	
  levels	
  of	
  
risk,	
  most	
  families	
  avoid	
  shelter.	
  
• Workers	
  should	
  be	
  able	
  to	
  override	
  the	
  
recommenda:on	
  of	
  the	
  model	
  with	
  wrimen	
  
explana:ons	
  
• Determina:on	
  of	
  the	
  propor:on	
  of	
  families	
  to	
  
serve	
  is	
  a	
  ques:on	
  of	
  available	
  funds	
  and	
  costs,	
  
both	
  to	
  the	
  homeless	
  service	
  systems	
  and	
  to	
  
society.	
                                                                    28	
  
Part	
  IV.	
  The	
  Random	
  Assignment	
  Study	
  

• 295	
  families	
  were	
  enrolled	
  in	
  Summer	
  2010	
  
  and	
  followed	
  for	
  27	
  months	
  through	
  
  December	
  2012	
  	
  
• 150	
  were	
  in	
  the	
  treatment	
  group	
  and	
  145	
  in	
  
  the	
  control	
  
• Abt	
  released	
  its	
  final	
  report	
  on	
  May	
  28,	
  2013	
  

                                                                             29	
  
Research	
  Ques-ons	
  
• Confirmatory	
  
   – Does	
  the	
  Homebase	
  Community	
  Preven:on	
  program	
  
     affect	
  the	
  rate	
  of	
  shelter	
  use,	
  as	
  defined	
  by	
  nights	
  in	
  
     shelter	
  during	
  the	
  study’s	
  follow-­‐up	
  period?	
  
   – Do	
  any	
  savings	
  that	
  result	
  from	
  reduced	
  shelter	
  costs	
  
     offset	
  the	
  cost	
  of	
  opera:ng	
  the	
  program?	
  
• Exploratory	
  
   – Are	
  clients	
  who	
  are	
  offered	
  access	
  to	
  the	
  program	
  less	
  
     likely	
  to	
  spend	
  at	
  least	
  one	
  night	
  in	
  shelter	
  during	
  the	
  
     follow-­‐up	
  period?	
  
   – Are	
  clients	
  who	
  are	
  offered	
  access	
  to	
  the	
  program	
  less	
  
     likely	
  to	
  apply	
  for	
  shelter	
  during	
  the	
  follow-­‐up	
  period?	
  

                                                                                            30	
  
Data	
  
• En:rely	
  based	
  on	
  administra:ve	
  records	
  
• Baseline—Homebase	
  Universal	
  Pre-­‐Screen	
  
    – Personal	
  iden:fiers—used	
  just	
  for	
  matching	
  
    – Demographic:	
  household	
  composi:on,	
  income,	
  
      employment,	
  benefits;	
  past	
  and	
  current	
  housing	
  situa:on;	
  
      risk	
  of	
  homelessness	
  
• Follow-­‐up:	
  up	
  to	
  27	
  months	
  (December	
  2012)	
  
    – Shelter	
  use:	
  Department	
  of	
  Homeless	
  Services	
  
    – Child	
  Protec:on	
  Services:	
  Administra:on	
  for	
  Children’s	
  
      Services	
  
    – Public	
  Assistance:	
  Human	
  Resources	
  Administra:on	
  
    – Employment:	
  New	
  York	
  State	
  Department	
  of	
  Labor	
  
      (aggregate)	
  

                                                                                  31	
  
Model	
  and	
  Significance	
  Tests	
  
• Intent	
  to	
  Treat	
  Analysis	
  
• Es:ma:on—Ordinary	
  Least	
  Squares	
  with	
  robust	
  
  standard	
  errors	
  
• One-­‐tailed	
  test—If	
  the	
  program	
  either	
  fails	
  to	
  
  reduce	
  nights	
  in	
  shelter	
  or	
  actually	
  increases	
  it,	
  
  the	
  policy	
  conclusion	
  is	
  that	
  the	
  program	
  is	
  not	
  
  successful	
  in	
  mee:ng	
  its	
  primary	
  goal	
  
• .10—Because	
  there	
  is	
  limle	
  likelihood	
  that	
  the	
  
  program	
  will	
  produce	
  harm,	
  the	
  research	
  team	
  
  risk	
  greater	
  chance	
  of	
  a	
  false	
  posi:ve	
  to	
  decrease	
  
  risk	
  of	
  a	
  false	
  nega:ve	
  
                                                                              32	
  
Homebase	
  Successfully	
  Reduces	
  Shelter	
  Applicants	
  

                                                 20%	
  
                                                                18.2%	
           49%	
  Fewer	
  Shelter	
       Homebase	
  cut	
  
                                                                                  Applicants	
                    the	
  number	
  of	
  
Percentage	
  of	
  Households	
  Applying	
  

                                                 16%	
  
                                                                                                                  study	
  households	
  
                                                                                                                  who	
  applied	
  for	
  
                                                 12%	
  
                                                                                                9.3%	
            shelter	
  in	
  half.	
  

                                                  8%	
  

                                                  4%	
  

                                                  0%	
  
                                                           Control	
  Group	
            Treatment	
  Group	
  
                                                                                                                                      33	
  
Homebase	
  Significantly	
  Reduces	
  Average	
  Nights	
  in	
  
                      Shelter	
  

                                 35	
           32.2	
  
                                 30	
  
                                                                  22.6	
  (70%)	
  Fewer	
  Nights	
  
                                 25	
  
   Nights	
  in	
  Shelter	
  

                                 20	
  

                                 15	
  
                                                                                9.6	
  
                                 10	
  

                                   5	
  

                                   0	
  
                                           Control	
  Group	
           Treatment	
  Group	
  
                                                                                                         34	
  
Homebase	
  is	
  Cost	
  Effec-ve	
  

                Average	
  Shelter	
  Cost	
  Per	
  Study	
  Household	
  
                                                                                     City	
  Funds	
  Only	
  
$2,500	
  	
  
                                                                                    $765	
  	
  
                                                                                                             $558	
  	
  
$2,000	
  	
  

$1,500	
  	
  

                                                                               Shelter	
  Cost	
   Homebase	
  Cost	
  
$1,000	
  	
  
                                                                              Every	
  dollar	
  invested	
  in	
  
                                                                              Homebase	
  saves	
  $1.37	
  
   $500	
  	
                                                                 in	
  City	
  dollars	
  spent	
  on	
  
                                                                              shelter.	
  
       $0	
  	
  
                        Shelter	
  Cost	
        Homebase	
  Cost	
  
                                      City	
     State	
  &	
  Federal	
  
                                                                                                                            35	
  
Summary	
  
• Homebase	
  reduced	
  average	
  nights	
  in	
  shelter,	
  
  shelter	
  entry	
  and	
  applica:on	
  for	
  shelter	
  
• The	
  data	
  suggest	
  it	
  did	
  so	
  by	
  a	
  combina:on	
  of	
  
  reducing	
  shelter	
  entry	
  and	
  average	
  nights	
  in	
  
  shelter	
  for	
  those	
  who	
  entered	
  or	
  would	
  have	
  
  entered	
  in	
  the	
  absence	
  of	
  the	
  program	
  
• The	
  analysis	
  suggests	
  that	
  the	
  savings	
  from	
  the	
  
  es:mated	
  reduc:on	
  in	
  nights	
  in	
  shelter	
  was	
  
  greater	
  than	
  the	
  es:mated	
  cost	
  of	
  opera:ng	
  
  Community	
  Preven:on	
  
                                                                                 36	
  
Summary	
  of	
  Key	
  Findings	
  of	
  the	
  
               Evalua-on	
  Study	
  
                                                 	
  
Homelessness	
  is	
  concentrated	
  in	
  a	
  small	
  number	
  of	
  communi-es:	
  nearly	
  
two-­‐thirds	
  of	
  all	
  family	
  shelter	
  entrants	
  come	
  from	
  15	
  communi:es	
  	
  
	
  
Homebase	
  affects	
  the	
  paeern	
  of	
  shelter	
  usage	
  in	
  the	
  highest	
  risk	
  
                                                 	
   in	
  the	
  highest	
  risk	
  communi:es	
  
communi-es:	
  Having	
  a	
  Homebase	
  office	
  
prevents	
  at	
  least	
  10%	
  of	
  all	
  families	
  served	
  from	
  entering	
  shelter	
  
	
  
New,	
  more	
  sophis-cated	
  tools	
  can	
  be	
  used	
  by	
  front-­‐line	
  workers	
  to	
  target	
  
at-­‐risk	
  families:	
  a	
  new	
  risk	
  assessment	
  tool	
  created	
  from	
  years	
  of	
  program	
  
data	
  will	
  improve	
  the	
  targe:ng	
  of	
  services	
  by	
  26%	
  
	
  
There	
  are	
  no	
  families	
  who	
  are	
  too	
  hard	
  to	
  serve:	
  Homebase	
  was	
  most	
  
successful	
  with	
  the	
  highest	
  need	
  families	
  
	
  
Homebase	
  is	
  successful	
  in	
  preven-ng	
  homelessness	
  and	
  saving	
  government	
  
resources.	
  

                                                                                                                    37	
  
Challenges	
  of	
  Homelessness	
  Preven-on	
  
• If	
  preven:on	
  were	
  perfectly	
  targeted	
  and	
  
     perfectly	
  effec:ve	
  (and	
  scaled	
  to	
  serve	
  
     everyone	
  at	
  risk),	
  it	
  could	
  solve	
  homelessness	
  	
  
• Preven:on	
  will	
  never	
  be	
  perfectly	
  targeted	
  or	
  
     perfectly	
  effec:ve	
  (or	
  large	
  enough)	
  
• Preven:on	
  cannot	
  replace	
  the	
  shelter	
  system,	
  
     but	
  it	
  can	
  reduce	
  the	
  demand	
  for	
  shelter.	
  It	
  is	
  
     a	
  cri:cal	
  component	
  of	
  the	
  homeless	
  service	
  
     system.	
  
	
                                                                               38	
  
What	
  Can	
  We	
  Do?	
  
What	
  makes	
  a	
  household	
  high	
  risk	
  for	
  shelter	
  
entry	
  and	
  can	
  Homebase	
  target	
  services	
  to	
  these	
  
high	
  risk	
  individuals?	
  

Targe:ng	
  services	
  to	
  prevent	
  homelessness	
  is	
  
difficult:	
  	
  
 • Numbers	
  of	
  shelter	
  entrants	
  are	
  small	
  and	
  many	
  people	
  with	
  
   mul:ple	
  risk	
  factors	
  for	
  shelter	
  entry	
  avoid	
  shelter	
  
   	
  
• Preven:on	
  should	
  be	
  aimed	
  at	
  those	
  most	
  at-­‐risk	
  
  of	
  becoming	
  homeless	
  

                                                                                               39	
  
Individual Risk
Assessment

Neighborhood
Targeting

Enrollment

Client
Outcomes

                  40	
  
 

 Neighborhood	
  TMapping
Neighborhood      arge-ng
                       	
  
                              41	
  
 

                                              Targe-ng	
  Enrollment	
  Resources	
                                         	
  

                                                  Focus vast majority of
                                                  resources on highest risk
                                                  cases, but also create low
                                 1600	
  
                                                  resource, light touch “brief”
                                                  services: workshops,
                                 1400	
  
                                                  housing advice, meaningful
                                                  referrals
                                 1200	
  
Number	
  of	
  Households	
  

                                 1000	
  

                                  800	
  

                                  600	
  

                                  400	
  

                                  200	
  

                                      0	
  
                                              ARCHNY	
     ARCHNY	
  II	
     BXW	
     CAMBA	
  I	
     CAMBA	
  II	
     CCNS	
             CCNS	
  II	
     HELP	
  I	
     HELP	
  II	
     PALLADIA	
     RBSCC	
  
                                                                                                   FULL	
  SERVICE	
               BRIEF	
  SERVICE	
  

                                                                                                                                                                                                                           42	
  
Tying Client Outcomes to Risk Level
                Align incentives to support those who
                take on the higher risk cases that are
                     more likely to become homeless

                                                  43	
  
Next	
  Steps:	
  	
  
                                	
  
        -­‐Use	
  analy:cs	
  to	
  create	
  predic:ve	
  
            models	
  and	
  real-­‐:me	
  tools	
  for	
  
                  neighborhood	
  outreach	
  
                                	
  
           -­‐Con:nually	
  evaluate	
  and	
  
        augment	
  the	
  risk	
  assessment	
  tool	
  
                                	
  
        -­‐Con:nue	
  to	
  evaluate	
  Homebase	
  
What tools does Homebase use
        service	
  package	
  and	
  iden:fy	
  best	
  
                        prac:ces	
  

to target services?           	
  

                                                              44	
  
 
           For	
  more	
  informa-on	
  
                           	
  
• Sara	
  Zuiderveen:	
  szuiderveen@dhs.nyc.gov	
  	
  
• Zhifen	
  Cheng:	
  zcheng@dhs.nyc.gov	
  	
  

                                                           45	
  
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