Practical Strategies for IncreasingHMIS Bed Coverage

Presenters• Jeff Ward – Abt Associates

– TA Provider– Served as El Paso, TX HMIS System Administrator

• Valerie Bouriche – Canavan Associates– TA provider– Served as Birmingham, AL HMIS System Administrator

• Su Nottingham – Bergen County, NJ– HMIS Administrator -- developing Biometric application

Workshop Introduction

Jeff Ward, Abt Associates

Learning Objectives

Participants should:• Have a thorough understanding of the meaning and

importance of HMIS Bed Coverage• Understand some common barriers to increasing

HMIS Bed Coverage• Understand strategies and tools developed by other

communities to successfully increase HMIS BedCoverage

• Be able to assess local barriers and apply workshopconcepts to increase local HMIS Bed Coverage

Workshop Introduction

Low HMIS Bed Coverage prevents many communitiesfrom understanding the true nature and extent ofhomelessness in their jurisdictions and from fullyparticipating in the AHAR.

We will discuss some factors that lead to poor bedcoverage, present strategies that have worked in othercommunities and allow participants to discuss theirunique problems with experienced practitioners.

Bed Coverage Rate

HMIS-bed coverage rate refers to the proportion of bedsin a community that participate in HMIS. The HMIS-bed coverage rate is equal to the total number ofHMIS-participating beds divided by the total number ofbeds in a community.

Example:Total Beds = 150Beds in HMIS = 45Bed coverage = 45/150 = 30% HMIS Bed Coverage

Importance of Bed Coverage Rate

“The indicator is important because the accuracy of theextrapolation technique depends on obtainingreasonably high bed coverage rates. The study teamevaluated each reporting category on its own merits—that is, calculated an HMIS-bed coverage rate for ES-IND, ES-FAM, TH-IND, and TH-FAM separately—andexcluded from the final AHAR analysis any reportingcategory with an HMIS-bed coverage rate below 50percent.”

- 2009 Annual Homeless Assessment Report to Congress

Insights from the 2009 AHAR (10/1/08-9/30/09)

• Many communities were unable to submit usable data for allHMIS categories. 397 communities (out of 463) submittedsomething to the 2009 AHAR. Only 137 (35%) submittedacceptable data for all four categories.

• ES-IND had the fewest usable submissions• ES-IND 179• TH-FAM 232

• ES also had the lowest bed coverage rate• ES 65%• AHAR 68%

Barriers to Increasing HMIS Bed Coverage

• Lack of agency resources

– Staffing• Too few, too little time• Limited computer skills• Shelter may be dependent on homeless ‘volunteers’• Don’t see the need for HMIS (management/staff)

– Technology• Few computers, may not be adequate for HMIS• Limited access to internet• Existing HMIS software may not be adequate for high volume,

high turnover shelters

Barriers to Increasing HMIS Bed Coverage (cont.)

• Many housing programs are not required to participatein HMIS and choose not to participate.– Secular organizations with limited resources – staff, computers,

internet access– Faith-based Organizations (FBOs)

• Catholic Charities, Salvation Army, Jewish Federations, etc.• Rescue Missions affiliated with the Association of

Gospel Rescue Missions (AGRM):– 300 member Rescue Missions– 70% of these Missions accept no federal funding– Provide an estimated 11% of all ES and TH beds– Many have Mission focused software (about 100 Missions)

– Independent, local FBOs

Increasing HMIS bed coverage

For many communities, increased HMIS bed coveragewill not be possible until:

• Difficult, high volume, high turnover shelters withlimited resources can be successfully integrated intoHMIS; and,

• The community commits to engaging Faith-basedOrganizations – often the primary providers ofEmergency Shelter – as full partners the HMIS

Comments and Workshop Discussion

• Is this introduction consistent with your experience? Ifnot, how does your community differ?

• What other factors limit HMIS bed coverage in yourcommunity?

• Do FBOs provide housing for the homeless in yourcommunity? Are they participating in HMIS?

• Were you able to submit an acceptable ES-IND to the2009 AHAR?

Strategies

• Engage Faith-based Organizations

• Use technology to– Simplify daily check in– Improve data quality, adding value to HMIS participation by

allowing better reporting– Eliminate duplicate data entry by using HUD’s HMIS XML

v.3.0 to transfer data from FBOs and other legacy systems

Engaging Faith-Based Organizations

Valerie Bouriche, Canavan Associates

Learning Objectives

Participants should:• Understand how Faith-based Organizations (FBOs)

differ from secular organizations• Understand how ‘Talking Points’ can help communities

engage FBOs• Understand factors that can cause HMIS

implementations in similar FBOs to have differentoutcomes

• Be prepared to return home increase their local FBOHMIS Bed Coverage

Motivations for Data Collection AmongFaith-Based Service Providers• Faith-based organizations have different reasons for

gathering data:– Ideas of success– Long range goals– Funding– Accountability models (internal and external)– Interfaith/community partnerships– Denominational viewpoints (Why do they help people?)

• Understanding the realities of faith-based partnershipsis critical for success—every situation is unique

Talking Points: Engaging Faith-Based Providers

• Why join a community information system/HMIS?– Modifiable and Scalable Systems– Information and Resource Sharing– Funding Leveraging– Collaboration among Service Providers

Community Examples: North Carolina

• Two Emergency Assistance Networks (EAN)comprised of faith-based service providers withdifferent HMIS participation outcomes– Winston-Salem EAN– High Point EAN

Winston-Salem EAN

• United Way of Forsyth County approached HMISTeam for– Data migration from a legacy software– Technical assistance– Software customization– End user training– On-going network support

• United Way provided Leadership and Support– Organized and held all of the community meetings– Paid for first-year costs– Secured additional financial subsidies from other grantors

Winston-Salem EAN (cont.)

• In less than one year, Winston-Salem EAN abandonedCHIN because of the following reasons– Client consent model was inconvenient. Too long and difficult

to explain– HMIS opt-outs defeated the primary purpose of the network—

to minimize double-dipping and fraud– No history of services screen that showed services received

and denied– Software difficult to use. User interface not intuitive– Too many data fields/questions. (Winston-Salem EAN

created assessments)– Insufficient staff to meet data entry needs

Winston-Salem EAN (cont.)

• The Winston-Salem EAN abandoned HMIS in favor ofa less intensive (and less capable) software solution

– HMIS was just another problem, not an opportunity– Site-based inconveniences outweighed community

issues– Agencies reverted to previous client consent protocols– New software displays a continuous history screen

Winston-Salem EAN (cont.)

• Data integrity is questionable• Unable to generate unduplicated reports and

community reports through an integrated HMIS• Did not understand how data could be used to help

individuals and strengthen programs• Did not understand the value of the data they gathered

outside of preventing double-dipping

High Point EAN

• High Point CoC agreed to expand their usage of HMISto include Emergency Assistance Network providers

• Used the assessments and reports pioneered by theWinston-Salem group

• Evaluated several vendors before choosing CHIN• CHIN was brought in late in the process• Leadership was familiar with HMIS standard operating

procedures and network policies• All agencies had to pay their own share of network

fees

High Point EAN (cont.)

• High Point EAN reasoning and goals– Collaboration and reporting requirements between agencies

using FEMA funds– Standardization between HMIS and EAN providers made

business sense– Ability to generate community wide data – data that can be

used in program planning– Long term expansion is possible

Similarities Between EANs

• Served comparable populations• Exhibited similar leadership and community support

models (both projects heavily subsidized)• Operated from the same cultural and interfaith

viewpoints• Saw the interconnectedness of their work• Encountered the same technical, implementation,

training and personnel issues• Comprised of less than excited faith-based groups

Differences Between EANs

• Winston-Salem agencies were continually concernedwith identifying and eliminating fraud.

• High Point understood how collaboration betweenemergency service providers and traditional HMISagencies could have a positive long-term impact forservice providers and homeless clients.

Additional Tips to Consider

• Practice relationship building• Assist with infrastructure creation within faith-based

community• Offer financial incentives• Adapt processes to specific agency needs• Gain support and insight from colleagues

Adding Technology to HMIS

Jeff Ward, Abt Associates

Learning Objectives

Participants should:• Understand how technology can augment the

capability of existing HMIS software and improveHMIS Bed Coverage

• Understand client’s PIN and why it is critical• Understand differences between barcode scan,

biometric and XML technologies• Understand key considerations in applying technology

to increase HMIS Bed Coverage

What Do You Mean By ‘Technology’?

For this presentation we are referring to electronicdevices, software and data protocols that augment thecapabilities of existing HMIS software by:

– Identifying the client – Devices and ancillary software thatprovide a client’s permanent and unique PersonIdentification Number (PIN - data element 3.14) to theCoC’s HMIS software.

– Eliminating duplicate data entry -- Protocols fortransferring a minimal data set from legacy software to theCoC’s HMIS software.

How Can Technology Improve Bed Coverage?

Appropriate use of available technology can encourageHMIS participation by reducing administrativeoverhead – making HMIS easier to use

– Simplify check-in/check-out process in high volume, highturnover emergency shelters. Note UDE 2.12

– Reduce need for staff computer and keyboard skills– Run shelter check-in without internet access or HMIS

passwords– Eliminate the need for duplicate data entry

Is This Really Feasible for My HMIS?• These solutions do work in real shelters with real clients.

• CoCs should only implement technology appropriate to theirneeds:– Simple/complex– Inexpensive/expensive– Single shelter/statewide

• Most HMIS software providers have some provision for usingbarcode scanning and XML technology. Others are indevelopment.

• Many communities have extensive experience with thesetechnologies – many models already exist.

How Do I Start?

• Understand how new technology might work with yourcurrent HMIS.

• Have a basic understanding of the technologies andhow they work – we will present a simple primer onscan, biometric and XML tools.

• Appreciate the importance of process. The technologyis really the easy part – developing community andagency ‘buy in’ is crucial and often challenging

• Know this will be an iterative effort. Pilot, pilot, pilot.

Identifying the Client – the PIN Data Element

The client’s Personal Identification Number (PIN) is aUniversal Data Element at the core of HMIS software:

“A PIN must be created, but there is no required format as longas there is a unique PIN for every client served in the CoCusing a consistent format and it contains no personallyidentifying information.” (2010 Data Standard – March 2010)

By linking directly to the PIN, electronic input devicesbypass traditional HMIS de-duplication schemes, yetreduce the potential for client duplication

Obtaining the Client’s PIN

There are currently two technology based methods for‘reading’ a client’s PIN:

– Card scan technology: Read the PIN directly from somethinga client has (optical, magnetic or RFID).

– Biometric technology: Read the client – finger scan, capillaryvein scan, retina recognition, iris recognition, etc. Link theclient’s biometric characteristics to their HMIS PIN.

Recording Program Participation/Attendance

Once the client’s unique PIN has been obtained, it issubmitted to the HMIS along with programparticipation or attendance information

• The PIN is placed into an existing HMIS search field. Nosoftware modification is required and technology only simplifiesthe existing client search process.

• Client PINs and program identifiers are collected in a simple ‘text’batch file. A ‘front end’ program collects PIN and programinformation and formats it for transmission to the HMIS. TheHMIS system must be able to accept information from a batch file.

Recording Program Participation/Attendance (cont.)

• The HMIS system may be able to collect and process programparticipation and attendance information online from scanners orbiometric devices. Capability varies by HMIS software supplier.

• Scripts can be developed to collect scan or biometric informationand enter that data into the HMIS. The script is a program thatelectronically duplicates or ‘mimics’ the steps that a person wouldtake to enter data into the HMIS. A biometric system wouldtypically use scripts to automate the process of sensing, matchingand submitting data to the HMIS. No HMIS software modificationis required.

Card Scan

Advantages• Simple – Provides direct access to PIN• Inexpensive – Scanners < $80• Mature – UPCs, FedEx and UPS,• Flexible – Online, offline batch, memory

Disadvantages• Easily lost, stolen or traded.• Lost cards must be replaced.• Does not uniquely identify the client

Typical Scan Card Components

• Scanners – Tethered, memory, RF• Photo ID Card software• Camera for photo ID Cards – Digital or webcam• Card media with barcode, magnetic stripe, RFID• Card Printers – Plastic, paper, thermal• May require HMIS software modifications

Biometric Systems

Advantages• “Reads” client – no cards to lose or trade• No media cost• Should eliminate duplicate client records

Disadvantages• More complex – Must compare the physical characteristics read by

the biometric sensor to a database of known clients, select best fitand return a PIN to the HMIS software. Must be online to thebiometric database to return a client PIN.

Typical Biometric System Components

• Sensor – finger scanner, capillary vein reader, etc. Converts aclient’s physical characteristic into a numerical value

• Biometric database/server – database of known client biometriccharacteristics and matching PINs

• Matching algorithms/decision software– FAR – False Acceptance Rate (0.0001% or 1 in 1,000,000)– FRR – False Rejection Rate (0.01% or 1 in 10,000)

• Enrollment/Sync process• Software script to transfer client PIN and program participation

information to HMIS software

Which Is Best?It depends on many factors:• What do you expect from the technology?• Community commitment

– Cutting edge?– What financial and technical resources are available?

• Size of the application – scalability issues– Single agency– Statewide

• Your HMIS software– What technology – if any – is supported?– Are you required to maintain a third-party biometric server?

Which Is Best? (cont.)

• Consider ancillary benefits– Would an ID card be useful beyond HMIS?

• Facilitate service delivery from mainstream providers• Streamline Project Homeless Connect/VA Stand Down

registration and follow up

– Do you need increased security?• Eliminate duplicate identities

Key Considerations

• Appreciate the importance of process– Seek diverse participation in system development– Take time to develop community and agency ‘buy in’

• Obtain inexpensive components to demonstrate the technology• Encourage innovative applications – don’t be afraid to dream• Imagine uses beyond HMIS

– Remember that change can be difficult

• Pilot, pilot, pilot– Consider developing simple prototype systems to challenge

assumptions– Try to minimize your investment until concepts are tested

Eliminating Duplicate Data Entry – HMIS XML

• Many Faith-based Organizations (FBOs), such asRescue Missions, already have non-HMIS software– Record basic client data– Track client progress– Manage bed assignments

• Transferring data from the FBO’s legacy system to theCoC’s HMIS would simplify and encourageparticipation– Eliminate the need for duplicate data entry– Allow FBOs to continue using software that meets their needs

Challenges

• FBO software must be modified– Collect Universal Data Elements in compliance with HUD 2010

Data Standards– Map Mission software to HUD HMIS XML Schema v.3.0– Manage data export to CoC HMIS

• FBO staff must be trained– Enter timely, accurate, complete data collection– Maintain client privacy and confidentiality

• The CoC’s HMIS software must accept HMIS XML 3.0input

Current Rescue Mission XML Transfer Status

• The primary Rescue Mission software provider hasdeveloped an HMIS XML 2.7 export and plans to upgradeto the 2010 Data Standards/XML 3.0.

• An HMIS XML 3.0 subset has been developed to facilitatetransfer of UDEs for AHAR. This subset of the 3.0 schemasimplifies export of data from Rescue Missions and otherlegacy software systems by focusing on only the dataelements needed to meet AHAR requirements.

• Some communities report that their Rescue Mission wouldbe willing to participate in HMIS if they could export theirlegacy data.

Summary

• Many communities have low HMIS bed coverage in atleast one AHAR category that– Limits understanding of local homelessness– Limits participation in AHAR

• Emergency shelter bed coverage is often the mostdifficult category for HMIS bed coverage– Agencies often have limited resources. Even agencies

required to participate in HMIS often produce unusable data.– Some housing providers are not required to participate in

HMIS, and have little incentive to join the HMIS.

Summary (cont.)

• Bed coverage can be increased– Engaging Faith-based Organizations– Adding technology to current HMIS software

• Identify the client– Scan– Biometric

• Transfer existing data from FBO or legacy systems

• We have the discussed tools, but the key to increasingbed coverage is– Community commitment– Process – working through the options in a systematic way

• Pilot, Pilot, Pilot

More Information• Faith-Based Engagement Talking Points – a community

resource developed by the Southeast Region HMIS Collaborative(SERHC) Faith-Based Engagement Subcommittee is available at:

http://hmis.info/Resources/7514/Faith-Based-Engagement-Talking-Points.aspx

• HUD XML 3.0 Schema and resources are available at:

http://www.hmis.info/Resources/7528/HMIS-XML-3.0-Schema-Directory.aspx

Questions, Comments and Discussion