September 18-19, 2006 – Denver, Colorado Sponsored by the U.S. Department of Housing and Urban...

September 18-19, 2006 – Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development

Understanding the Extent and Nature of Homelessness at the Local Level:

Implementing More Efficient and Accurate Point-in-Time Counts

Dr. Martha Burt, Urban InstituteMary Joel Holin, Abt Associates Inc.

Karen Booth, Baltimore Homeless Services, Inc.Jay Bainbridge, NYC Department of Homeless Services

September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 2

Overview

• Learning objectives

• Conducting point-in-time counts – the basics

• Guidance for integrating HMIS into your count– Baltimore City case study

• Karen Booth – Office of Homeless Services, Baltimore, MD

• Techniques for assessing the accuracy of counts– New York City case study

• Jay Bainbridge – New York City Department of Homeless Services


Learning Objectives

• To increase understanding of the key components of unsheltered and sheltered point-in-time counts and be prepared to increase the efficiency of counts in your own community.

• To learn how HMIS can assist with tracking bed inventories, determining unduplicated counts, and conducting a street and shelter count.

• To identify strategies to cope with challenges of gathering point-in-time data and using HMIS for point-in-time counts.


What Does It Mean to “Count” Homeless People?

• A point-in-time count enumerates the sheltered and unsheltered homeless population in your community

• A “count” = to collect information about1. Enumeration data on the number of homeless persons2. Descriptive information on those counted

• Demographic• Service use• Needs


Why Count Homeless People?

• To raise public awareness

• For planning and program development– Understand characteristics and needs – Develop programs based on need– Access resources for services and housing

• To measure progress in eliminating homelessness and to ensure accountability


Raising Public Awareness

• Conducting a count draws attention to the issue of homelessness– Possible opportunity for media attention– Especially useful in rural and suburban areas where

homeless people are not typically visible– Opportunity for community discussion

• Opportunity to educate the public and local government officials about homelessness– Who becomes homeless and why– Service and housing needs


Planning and Program Development

• A point-in-time count/survey is a planning tool– Identifies characteristics and needs – Guides decisions about program development and

resource allocation– Helps to quantify needed resources

• Point-in-time counts provide information that helps secure resources for homeless services– McKinney-Vento grant application – Other grant applications or private support– Justify requests for local or state government funds


Progress and Accountability

• Point-in-time counts can help measure progress in addressing homelessness over time– At the CoC and neighborhood levels

• Help answer the question: Do available services meet the existing needs?– Feeds into planning process and thoughtful program

development


Whom to Count and Gather Information About

• According to HUD, point-in-time counts must be: • “statistically reliable, unduplicated counts or estimates of

homeless persons in sheltered and unsheltered locations at a one-day point in time” (SuperNOFA 2006)

• Conducted at least every other year and during the last seven days of January

• At minimum, count homeless persons according to HUD definitions and guidelines

• Information is reported in the Population and Subpopulations Chart in the McKinney-Vento application (Exhibit 1, Chart K)


HUD Guidelines and Reporting Requirements

• Count sheltered and unsheltered adults, children, and unaccompanied youth – Unsheltered homeless people reside in a places not

meant for human habitation, such as cars, parks, sidewalks, abandoned buildings, on the street

– Sheltered homeless people reside in emergency shelter or a transitional housing (include hotel or motel vouchers for homeless people)

• Count the number of individuals, number of families, and number of persons in families



• Number of sheltered and unsheltered chronically homeless people

• Six other subpopulation categories required for sheltered and optional for unsheltered persons

Part 2: Homeless Subpopulations

Sheltered Unsheltered Total

a. Chronically Homeless (For sheltered, list persons in emergency shelter only)

b. Severely Mentally Ill * c. Chronic Substance Abuse * d. Veterans * e. Persons with HIV/AIDS * f. Victims of Domestic Violence * g. Unaccompanied Youth (Under 18) *



• Housing Inventory Charts– Number of beds and units– By program type and individual project– Emergency shelter, transitional housing, AND

permanent supportive housing

• Update inventory every year


Methods for Counting Homeless Persons

• Probably need a ‘menu’ approach, using a combination of where, when, how to count

• Unsheltered Counts (Street or public places counts) – Where to count

• Complete coverage• Known locations• Non-shelter services

– When to count• Night designated for the count: Last seven days in January• Length of data collection

– A ‘blitz’ count, 24 hours or less– More than 24 hours


Methods for Counting Homeless People

• Unsheltered Counts (cont.) – How to count unsheltered homeless people

• Simple count with observation• Count plus interviews• Service-based count (includes interviews) • Probability sampling

– Used by large cities and requires statistical expertise

• What methods are best for your community?• Urban / Suburban• Suburban / Rural


Methods for Counting Homeless People

• Sheltered Counts– Already know where and when to count– How to count

• Homeless Management Information System– Extract client-level count and/or subpopulation data

• Provider report or survey– Aggregate count of people in program– Subpopulation information or estimate for entire program

• Client-level survey using standardized instrument– Interview each client or a sample of clients– Program staff complete survey based on case records or knowledge of client

• Always collect count information from the provider, even if client interviews are completed


Challenges for Rural CoCs and Colonias

• Covering the territory

• Differentiating poorly housed from homeless people• The continuum of residential instability• Finding allies by including some high-risk-of-

homelessness populations—assuming you differentiate when you report

• Special populations (migrant workers, border crossers, “snowbirds”)


Benefits of Using HMIS for Point-in-Time Counts

• Requires fewer resources over time than a non-HMIS PIT count

• Helps avoid duplicate counting

• Provides in-depth subpopulation data on persons who are counted without repetitive interviews

• Reinforces the value of the HMIS and contributes to year-round HMIS participation and data quality


How Can HMIS Be Usedfor a Point-in-Time Count?• HMIS is a tool for gathering information about people

who use services– More useful for sheltered count

• Communities will need to continue street or service-based counts even if outreach workers are using HMIS

• Potential uses for unsheltered counts– Provides an opportunity to populate the HMIS – Helpful with de-duplicating street or service-based

counts


How Can HMIS Be Usedfor a Point-in-Time Count?

• Provides two components: 1. Count 2. Subpopulation information

• Typically used in combination with other data collection techniques

• Key considerations:– Data quality, data quality, data quality!– Make sure information is gathered or extrapolated for

each provider



• Examples

1. HMIS for count + subpopulation information

2. HMIS for participating providers + paper survey for non-participating providers

3. HMIS for count + paper survey for subpopulation information

4. HMIS for subpopulation information + paper survey for count



• Examples (cont.)

5. HMIS for participating providers + extrapolation for non-participating providers

6. Have participating providers generate paper surveys using HMIS-canned reports


Methods for Collecting Housing Inventory Information• HMIS bed management (possibly supplemented by

surveys for non-HMIS providers)

• Survey providers– During point-in-time population count– Send the last Housing Inventory Chart for providers to

update

• Include instructions on how to count seasonal beds, overflow beds, family units, vouchers


Key Considerations for Using HMIS

• Start planning early

– 4 to 6 months prior to count

– Leave adequate time to assess data quality, improve data quality, and decide whether and how to use HMIS

– Create a plan to gather sheltered data from non-participating providers

– Refer to Guidance on Counting Sheltered Homeless People for details


Using HMIS for a Point-in-Time Count: Baltimore City’s Experience

Karen BoothInformation Systems Coordinator

Baltimore Homeless ServicesBaltimore City Health Department



• Background:

– Conducted in January 2005

– BHS worked with the Center for Poverty Solutions

– PIT consisted of 3 components:• Street count/interviews• Shelter count (HMIS)• Shelter surveys



• Street Count/Surveys:

– BHS staff and volunteers– Service-based approach– Count ran from 6:30am until 9:00pm– Counted individuals on the street and engaged some to

conduct in-depth interviews



• Shelter Survey:

– BHS staff and volunteers– Went to emergency and transitional programs– Engaged clients and conducted in-depth interviews



• Shelter Count:

– BHS attempted to use the HMIS to count the number of clients housed in both emergency and transitional programs on January 30, 2005

– Gaps Analysis report from HMIS• Number of individuals and individuals in families in shelter• Number of families and average family size• Number of chronically homeless• Other “special population” characteristics



• What we found:– Numbers in the Gaps analysis did not match what BHS

believed to be the utilization rate for all shelters for that night

• What it meant:– Programs were not entering and exiting clients as

diligently as they should have been



• What we found:– Excess number of volunteers were sent to shelters that

were using the HMIS

• What it meant:– Need to re-think how we allocate valuable resources for

the next PIT. Need to put volunteers out on the street and in shelters that do not use the HMIS.



• What we found:– Other special characteristics (chronic, substance abuse,

etc.) numbers were not as high as expected

• What it meant:– Shelter staff needed more PIT-specific training and more

advance notice about the PIT and what information would be collected

AND– BHS staff needed to employ more rigorous data quality

measures


Using HMIS for a Point-in-Time Count: Lessons Learned

• It’s not just about coverage

– Just because an agency’s beds are accurately reflected in your system, does not mean their data is 100% accurate



• Verify data quality and accuracy prior to PIT date

– Work with providers to verify:• Number of beds and/or units represented on HMIS• Staff enter data on a timely basis• Staff are aware of importance of data quality and accuracy



• Conduct PIT/HMIS training with provider staff

– Review data that will be used for PIT– Train on data quality and accuracy


Using HMIS for a Point-in-Time Count: Recommendations

• Recommendations:

– PIT staff and HMIS staff should work collaboratively to plan

– Providers should also be involved in planning

– Review previously used PIT instruments, HMIS data fields, current reports, etc.


Using HMIS for a Point-in-Time Count: Recommendations

• Recommendations (cont’d):

– Look at coverage on HMIS• Parameters - Which programs participate in your HMIS and

which do not?This will tell you how to allocate your “manpower”

• What percentage of emergency beds and transitional beds/units are represented on your HMIS?

This will help to inform your decision about only using your HMIS or supplementing


New York City HMIS Count: Use of Sampling and Plant-Capture

for a Point-in-Time Estimate

Jay Bainbridge, Ph.D.Assistant Commissioner

Policy and Planning DivisionNew York City Department of Homeless Services


NYC HMIS Point-in-Time Count

Sheltered• DHS shelters• Drop-in centers• Private shelters • Other CoC shelters

Unsheltered• Streets• Subway trains• Subway stations• Parks• Transportation hubs• Hard-to-reach areas


NYC HMIS Sheltered Count

Prepare for the count

Use existing databases

Survey programs without HMIS

Estimate subpopulation counts


NYC HMIS Unsheltered CountHomeless Outreach Population Estimate (HOPE)

Counts within public places Uses a sampling strategy

Relies on volunteers

Builds in a plant-capture method for quality assurance


NYC HOPE – Sampling Frame

Divide the City into small geographic areas Treat subways as their own entity

Sort the areas into those with many unsheltered individuals and those with few, based on:• Previous year’s data• Experience and knowledge of experts


NYC HOPE – Sampling Strategy

Cover all areas designated as having many homeless people

Draw a stratified random sample from the remaining areas

Stratify by borough and subway

Determine the appropriate sample sizes, based on:• Standard deviations• Confidence level (95 percent)• Precision (differs by borough)


Assign 3-5 volunteers per team

Select a team leader who has:• Outreach experience,• Detailed local knowledge, or • HOPE experience

Cover 1-4 areas/subway stations

NYC HOPE – Survey Teams


Administer quickly• If sleeping, consider person homeless• If awake, ask a series of 4-7 questions

Determine homeless status

Eliminate double-counting

Make available in both English and Spanish

NYC HOPE – Survey Instrument


Assign 70-150 volunteers per training site

Have a leader with several helpers manage each site

Train volunteers from 11-12 p.m.

Survey from 12:05 – 4:00 a.m.

Take security measures

Allow for contingencies

NYC HOPE – The Night of the Survey


Survey everyone in the assigned areas

Cover the assigned areas only once

Approach everyone respectfully

Follow rules to determine homeless status

Call on outreach if a person wishes to come inside

Follow protocol for emergency weather conditions

Stay safe

NYC HOPE – Volunteer Training


Increasing HOPE Accuracy through a Plant-Capture Study

Goal: Determine if volunteers successfully found and counted the visible homeless in their assigned study areas

Approximation: Deploy decoys and see if they are counted

Adjust the census count to correct for the estimated number of uncounted decoys


Stratify allocation of plants: by borough + density, according to City’s sampling-fractions

Randomly distribute according to above formula –150 plants to cover 75 sites

Assign plants in pairs (for safety) to precise positions after advance reconnaissance of sites

Instruct plants to stay awake, behave appropriately, and turn over stickers when approached by HOPE survey teams

Plant-Capture Design


Plant-Capture Benefits

Enables CoC to better quantify the unsheltered

Helps provide visibility to the count

Motivates volunteers and enhances overall success

Does not interfere with general operations

Lends credence with independent evaluation


Plant-Capture Challenges

Managing logistics

Ensuring adequate coverage by decoys• Having more plants would be better, but at a cost

Recruiting decoys who look and act like stereotypical street-dwellers

Determining who was “missed”


Lessons Learned

Good News• Focus on data and targets is leading to fewer homeless

The Count is Better Every Year• More volunteers showed and more decoys were counted

It’s not just about the numbers

Important Work Ahead

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