Data Collection on Unsheltered Homelessness for Continuous S ystem Performance Improvement

1. Data Collection on Unsheltered Homelessness for Continuous System Performance Improvement

2. Presenters • Ann Howard, Executive Director, Ending Community Homelessness Coalition, Inc. • Colleen Murphy, Manager CES Access, Los Angeles Homeless Services Authority (LAHSA) • Kira Zylstra, Director, All Home King County • Joyce Probst MacAlpine, Senior Associate, Abt Associates Inc.

3. Annual Point in Time Counts 2010-2018

4. Literally Homeless Population Known persons experiencing homelessness in a given year 7,101 2016 7,054 2015 6,104 2014 6,232 2013

5. So many numbers… confusing, creates doubt 10,564 9,986 7,498 5,949 2,590 2,500 2,311 2,036 308 Unduplicated number of people in HMIS identifiedas literally homeless (1year) Unduplicated number of people who enter the shelter (1year) Uniquenumber of homeless individuals entering the APD system (1year) Number of household homeless identified in Coordinated Entry (1year) Individuals identified during ECHO’s Point in Timecount (1day) Uniquenumber of homeless individuals served by CentralHealth (1year) Uniquenumber of homeless individuals served by DACC (1year) Number of homeless students identifiedby AISD (survey at enrollment) Households (out of17,000 applicants)on waitlist for Section8 (2014) 12

6. Population Changes in Travis County, 2010 - 2015 1,121,645 1,092,810 1,063,248 1,034,842 1,007,264 979,712 2014 2010 2011 2012 2013 2015

7. Comparing Rates of Homelessness 23.5 21.7 21.3 19.7 18.3 17.7 20.6 20 19.8 19.3 18.2 16.3 Travis County rate of homeless persons/10,000 residents National rate of homeless persons/10,000 residents

8. Persons Experiencing Homelessness Categories are not mutually exclusive

9. Persons Experiencing Homelessness

10. Persons Experiencing Homelessness

11. Black Americans Face Large Disparities

12. Coordinated Assessment & Race

14. Costs for Top 250 Utilizers $178,000 37 days @ $4,800/day Inpatient Hospital Stay $30,000 Emergency Room Visit 21 visits @ $1,400/visit 8 visits @ $876/ transport $222,000 $14,000 EMS Transport Average annual total cost per person 1 booking @ $153 $153 Jail Booking

15. 1 2 3 4 5 Target Population 1. Calculated assuming utilization over the last 24 mos.; the project team is currently refreshing these to understand how it would change with an 18 month look back There are three eligibility criteria for the PFS Project 1 2 3 ~1,000 individuals would be eligible using these criteria. For the top 250 eligible participants, the average historical baseline encounters over the past two years are… 18 163 6.5 13 Bookings Jail Days Inpatient Days ER Visits

16. Where Do People Sleep? 28% Shelter Street, sidewalk, or doorway 28% 16% Car, van, or RV 16% Beach, riverbed, or park Unsheltered 72% Other (e.g. bridges, abandoned buildings) 10% 2% Bus or subway 100%

17. 832 unsheltered persons identified across Austin’s City Council Districts on one night in Jan. 2017 District 6 8 District 7 49 District 4 79 District 10 6 District 1 54 District 9 397 District 3 101 District 8 45 District 5 40 District 2 53

18. Downtown Homelessness Concentration 650 Total persons identified waking up homeless within ¼ mile of downtown homeless resources

19. Mapping entities, data, andservices

20. 2017 Community Assets

21. Estimated Funding Gap Current system investment: $30,155,741 per year Estimated additional need: $30,000,000 per year

22. Current Housing Needs 2,133 affordable + low barrier housing units needed now 4+ person HH 102 (4%) 2-3 person HH 357 (14%) Household (HH) Types Studios/1 Bedroom Units 2,133 357 1-2 Bedroom Units 102 3+ Bedroom Units Single-person HH 2,133 (82%) +

23. Current Housing Interventions Needed High 1,184 (39%) Recommended Intervention Total Needed: 2,592 1,572 Rapid Re-Housing Level of Need Permanent Supportive Housing 1,020 Moderate 2,119 (61%)

24. Cross System Youth Homelessness in Austin, TX 1,944 Homeless Students 607 Literally Homeless Youth Accompanied: 1,758 • Ages: Under 25 • HUD Definition: youth in shelter, or who live in a place not meant for human habitation Unaccompanied: 186 • Ages: 3 - 20 • McKinney Vento Definition:youth staying in shelters, unsheltered, in hotels/motels, or doubled up

25. Data is where it’s at!Using a data-driven, systematic approach to better serve people experiencing unsheltered homelessness in Los Angeles Breakout VI: 6.02 Data Collection on Unsheltered Homelessness for Continuous System Performance Improvement Harbor Island | 2:45 – 4:00 PM | February 22, 2019 Colleen Murphy, PGDip Manager, CES Access Los Angeles Homeless Services Authority (LAHSA)

26. What do you know about unsheltered homelessness in your community? • What trends do you see, if any?

27. https://www.lahsa.org/documents?id=2059-2018-greater-los-angeles-homeless-count-presentation.pdfhttps://www.lahsa.org/documents?id=2059-2018-greater-los-angeles-homeless-count-presentation.pdf

28. https://www.lahsa.org/documents?id=2059-2018-greater-los-angeles-homeless-count-presentation.pdfhttps://www.lahsa.org/documents?id=2059-2018-greater-los-angeles-homeless-count-presentation.pdf

29. What kinds of data do you collect about people who are living unsheltered that is used to inform program, policy, and funding decisions to better serve this population?

30. How we’ve thought about data in LA • What data do we already have? • And how can we better use? • What data is missing • And how can we get these? • What data is captured in disparate ways • And how can we harmonize? • What does the data tell us? • And how can we use it to improve the system • What doesn’t the data tell us • And how do we fill in the blanks? • How do we effectively and efficiently disseminate these data? • And how do we most effectively tell the story of our work?

31. How we’ve thought about data in LA, cont. • We need to think about our great unsheltered need • We need to think about scale • We need to think about streamlining • We need to think about integration of systems and entities • We need to think about coordinating many entities • We need to think about how to ensure its not just coordinated entry but coordinated passage • We need to think about the needs of our street outreach workers • We need to think about how to evaluate all this • We need to do all of this in a space of chaos and crisis

32. What data do we use? • Who and where? • Annual Homeless Count Data • PIT • Demographic Surveys • LA-HOP, other community concerns • HMIS • How? • Outreach worker rapid assessments, surveys • Old-fashioned street knowledge • Is it working? • HMIS

33. How have you used that data/How do you plan to use that data to make changes to your homeless response system to reduce unsheltered homelessness?

34. Establishing the “where”

37. How we assign, deploy teams • LA County outreach landscape includes teams funded by Measure H, Cities, SDs, CDs, COGs, other entities/funding sources • Measure H funding for MDTs is determined by Homeless Count data for each SPA • Through SPA-level planning, we created outreach hubs in each SPA, then assigned teams to these hubs according to need (and in accordance with any contractual requirements) for proactive outreach • Coordinating the work of these teams is spearheaded by Outreach Coordinators in each SPA • Teams then meet at least monthly in these hubs to coordinate care, discuss challenging cases/areas • Outreach requests received via LA-HOP are deployed via teams assigned to these hubs and any other considerations (population, MH need, etc) • Seamless for person filling in the request

38. Understanding the who and how many How many teams and staff and roles do we actually have?

39. Understanding the who and how many And how do I find them and communicate with them?

40. What kinds of data do you collect about people who are living unsheltered that is used to inform program, policy, and funding decisions to better serve this population?

41. Data not for the sake of data

42. Using these data to inform program design

43. Establishing how we measure our impact

44. Measure H-Funded Outcomes, 18 months

45. LA’s outreach infrastructure and permanent housing placements • Most clients are exited from Outreach Programs (and enrolled in Navigation Programs) before PHP • This means Outreach teams’ PHP data is artificially low • We wanted to look at PHP and Outreach team overlap • Data increased dramatically

46. Tracking reactive outreach work

47. How can you look at data you’re currently collecting to assess whether your homeless system/programs are causing racial disparities in your unsheltered population? • What data do you need to collect that you aren’t collecting to assess this issue and respond with solutions to reduce disparities, if they exist?

48. Assessing racial equity Source: REPORT AND RECOMMENDATIONS OF THE AD HOC COMMITTEE ON BLACK PEOPLE EXPERIENCING HOMELESSNESS, LOS ANGELES HOMELESS SERVICES AUTHORITY, DECEMBER 2018 https://www.lahsa.org/documents?id=2823-report-and-recommendations-of-the-ad-hoc-committee-on-black-people-experiencing-homelessness.pdf

49. Assessing racial equity Source: REPORT AND RECOMMENDATIONS OF THE AD HOC COMMITTEE ON BLACK PEOPLE EXPERIENCING HOMELESSNESS, LOS ANGELES HOMELESS SERVICES AUTHORITY, DECEMBER 2018 https://www.lahsa.org/documents?id=2823-report-and-recommendations-of-the-ad-hoc-committee-on-black-people-experiencing-homelessness.pdf

50. Assessing racial equity Source: REPORT AND RECOMMENDATIONS OF THE AD HOC COMMITTEE ON BLACK PEOPLE EXPERIENCING HOMELESSNESS, LOS ANGELES HOMELESS SERVICES AUTHORITY, DECEMBER 2018 https://www.lahsa.org/documents?id=2823-report-and-recommendations-of-the-ad-hoc-committee-on-black-people-experiencing-homelessness.pdf