HMIS Data Quality PlanSouth Alamo Regional Alliance for the Homeless

(SARAH)San Antonio/Bexar County Approved: October 20th 2016

Developed by HMIS Lead Agency, CoC, & HMIS Committee

I INTRODUCTIONThis document describes the Homeless Management System (HMIS) data quality plan for San Antonio/Bexar County Continuum of Care (CoC) – the South Alamo Regional Alliance for the Homeless (SARAH). HMIS is a locally administered electronic system that stores client-level information about persons who access homeless services in a community. The document includes a Data Quality Plan and protocols for ongoing data quality monitoring that meet requirements set forth by the Department of Housing and Urban Development (HUD). It is developed by the HMIS Administrator (Haven for Hope), the CoC in coordination with the HMIS Committee of SARAH and HMIS participating agencies, and community service providers. This HMIS Data Quality Plan is to be updated annually, considering the latest HMIS data standards and locally developed Data Quality Thresholds.

HMIS Data and Technical StandardsEach CoC receiving HUD funding is required to implement and participate in HMIS to capture standardized data about all persons accessing homeless assistance in the area. The Homeless Management Information System complies with HUD’s official data and technical standards published on HUD’s Resource Exchange.

In 2010, the U.S. Interagency Council on Homelessness (USICH) affirmed HMIS as the official method of measuring outcomes for homelessness in Opening Doors: Federal Strategic Plan to Prevent and End Homelessness. Many federal partners that provide services to specific homeless populations have joined together to work in a coordinated effort to end homelessness using HMIS data:

• U.S. Department of Housing and Urban Development (HUD)• U.S. Department of Health and Human Services (HHS)• U.S. Department of Veteran Affairs (VA)

In May of 2014, HUD published final HMIS Data Standards to ensure consistent reporting across federal agencies. The 2014 Data Standards revise and replace the 2010 HMIS Data Standards which guide client- and program-level data reporting. The 2014 Data Standards identify Universal Data Elements and Program Specific Data Elements that are required of all homeless programs participating in the HMIS.

What is Data Quality?Data quality is the reliability and validity of client-level data collected. Good data quality accurately reflects actual client information in the real world and has the ability to tell a client’s story. It also aids case management in assessing client needs and determining appropriate services. Data quality is determined by several factors such as timeliness, completeness, and accuracy. For system performance measurement, HUD’s expectation is that HMIS data be complete and accurate dating back to October 1st, 2012.

What is a Data Quality Plan?A data quality plan is a community-level document that assists the CoC in achieving statistically valid and reliable data. The plan sets expectations for both the community and the end users to capture reliable and valid data on persons accessing the homeless assistance system. The plan:

Establishes specific data quality benchmarks for timeliness, completeness, accuracy, and consistency;

2

Identifies the responsibilities of all parties within the CoC with respect to data quality; Establishes a timeframe for monitoring data quality on a regular basis.

What is a Data Quality Monitoring Plan?A data quality monitoring plan is a set of procedures that outlines a regular, on-going process for analyzing and reporting on the reliability and validity of the data entered into the HMIS at both the program and aggregate system levels. This plan includes roles and responsibilities for the CoC, the HMIS Administrator, and the HMIS Committee.

II DATA QUALITY PLAN

Data Entry Expectations:

Universal Data Elements (UDEs)The Universal Data Elements are baseline data collection elements required for all projects reporting data into the HMIS. These include:

Name Social Security Number Date of Birth Race Ethnicity Gender Veteran Status Disabling Condition Living situation

Project Entry Date Project Exit Date Destination Personal ID (Generated by HMIS) Household ID (Generated by HMIS) Relationship to Head of Household Client Location

Program Specific Data Elements (PDEs)Program Specific Data Elements (PDEs) differ from the Universal Data Elements (UDEs) in that no one project must collect every single element in this section. Required data elements are dictated by the reporting requirements set forth by each Federal partner for the projects they fund. A Partner may require all of the fields or response categories or may specify which of the fields or response categories are required for their report. Data Quality Thresholds are included in Appendix C of the Data Quality Plan outlining required data elements and thresholds for each Federal partner.

The Program Specific Data Elements include the following:

Housing Status Income and Sources Non-Cash Benefits Health Insurance Physical Disability Developmental Disability

3

Chronic Health Condition HIV/AIDS Mental Health Substance Abuse Domestic Violence Contact Date of Engagement Services Provided Financial Assistance Provided Referrals Provided Residential Move-In Date Housing Assessment Disposition Housing Assessment at Exit

Benchmarks and Goals:

TimelinessTimeliness answers the question: “Is the necessary client information entered into HMIS within a reasonable period of time?”

When data is entered in a timely manner, it can reduce human error due to too much time between data collection and data entry. Relying on notes or memory of a conversation can lead to incorrect or incomplete data entry. Timely data entry also ensures accessibility of information for the entire CoC for Coordinated Entry and project evaluation. There is a Timeliness Report that agencies can use under “Data Quality Reports” in the HMIS Administration section to monitor the timeliness of data entry for entry into a project and exit from a project.

Each type of project has different expectations on timely data entry. Timeliness is measured by comparing the enrollment entry/exit date to the assessment entry/exit created date. Timeliness cannot be edited, only improved going forward – but assessment information dates should match the date the client interview occurred.

Data entry timeframe by project type:

Emergency Shelter projects: Universal Data Elements and Housing Check-In/Check-Out must be entered within 2 business days.

Transitional Housing projects: Universal Data, Program-Specific Data, and Housing Check- In/Check-Out must be entered within 2 business days.

Permanent Housing projects: Universal Data, Program-Specific Data, and Housing Check- In/Check-Out must be entered within 2 business days.

Rapid Re-Housing projects: Universal and Program-Specific Data Elements must be entered within 2 business days.

4

Prevention projects: Universal and Program-Specific Data Elements must be entered within 2business days.

Supportive Services Only (including SSVF and safe sleeping) projects: Universal and Program- Specific Data Elements must be entered within 2 business days.

Safe Haven projects: Universal Data, Program-Specific Data, and Housing Check-In/Check-Out must be entered within 2 business days.

Outreach Projects: Limited data elements must be entered within 3 business days of the first outreach encounter. Universal Data Elements should be collected upon engagement in services.

CompletenessCompleteness answers the question: “Are all of the clients we serve being entered into HMIS? Are all of the necessary data elements being recorded into HMIS?”

Complete data is the key to assisting clients in finding the right services and benefits to end their homelessness. Incomplete data may hinder an organization’s ability to provide comprehensive care to the clients it serves. Incomplete data can also negatively impact SARAH’s ability to make generalizations of the population it serves, track patterns in client information and changes within the homeless population, and adapt strategies appropriately. HMIS data quality is also part of funding applications, including CoC and ESG funding. Low HMIS data quality scores may impact, and could result in denial of future funding requests.

SARAH’s goal is to collect 100% of all data elements. Therefore, the HMIS Committee, with the CoC Board’s approval, has established Data Quality Thresholds (see Table 1 through 7, Appendix C). The Data Quality Thresholds set an acceptable range of “null/not collected”, and “client doesn’t know/client refused” responses, depending on the data element. To determine compliance, percentages will be rounded (example: .04% becomes 0%).

All programs using the HMIS shall enter data on one hundred percent (100%) of the clients they serve. These standards will be reviewed and revised annually to make sure the thresholds are reasonable.

TABLE 1: CoC Data Quality Thresholds – See Appendix C

Bed/Unit Utilization Rates:

One of the primary features of an HMIS is the ability to record the number of client stays or bed nights at a homeless residential facility. Case managers or shelter staff enter a client into the HMIS and assign them to a bed and/or a unit. The client remains there until he or she exits the program. When the client exits the project, they are also exited from the bed or unit in the HMIS. All Emergency Shelters and Transitional Housing units funded by the COC must use the bed check-in software in HMIS. Bed/unit utilization will be determined based on bed check-ins and by project enrollment dates.

5

Acceptable range of bed/unit utilization rates for established projects: Emergency Shelters: 65%-105% Transitional Housing: 65%-105% Permanent Supportive Housing: 65%-105% Safe Haven: 65%-105%

The CoC recognizes that new projects may require time to reach the projected occupancy numbers and will not expect them to meet the utilization rate requirement during the first six months of operating.

AccuracyAccuracy answers the question: “Does HMIS data accurately reflect true client information? Are the necessary data elements being recorded in HMIS in a consistent manner?”

Information entered into the HMIS needs to be valid, i.e. it needs to accurately represent information on the people that enter any of the homeless service programs contributing data to the HMIS. The best way to measure accuracy of client data is to compare the HMIS information with more accurate sources, such as a social security card, birth certificate, or driver’s license. To ensure the most up-to-date and complete data, data entry errors should be corrected on a monthly basis.

As a general rule, it is a better practice to select “client doesn’t know/refused” than to misrepresent the population.

Data consistency will ensure that data is understood, collected, and entered consistently across all projects in the HMIS. Consistency directly affects the accuracy of data; if an end user collects all of the data, but they don’t collect it in a consistent manner, then the data may not be accurate. All data in HMIS shall be collected and entered in a common and consistent manner across all programs. To that end, all intake and data entry workers will complete an initial training before accessing the live HMIS system, and access additional training opportunities offered by the HMIS Lead.

Data Consistency Checks

The HMIS staff may check data accuracy and consistency by running reports that check for entry errors such as duplicate files created, overlapping enrollments or inconsistent assessment responses. The HMIS team also reserves the right to provide HMIS client identification numbers to the CoC for their program auditing or monitoring purposes.

III DATA QUALITY MONITORING PLAN

Roles and Responsibilities:

CoC Board of Directors The CoC Board of Directors will provide overall direction to the HMIS team and provide oversight of the HMIS Committee. Additionally, the CoC Board of Directors will enforce measures of community data quality.

6

HMIS Lead (Haven for Hope)

Report Maintenance –

The HMIS Administrator is responsible for building reports and making them available to the CoC. This includes the data quality reports necessary for data correction. The HMIS staff will be responsible for the ongoing maintenance of existing reports as well, which includes changes in reports as updates are made to the system.

Training –

The HMIS team at Haven for Hope is also responsible for providing the necessary training for the CoC. Currently, the HMIS team offers the following trainings: New User training, Management Training, Report training, HMIS Security Awareness Training, Refresher Training (groups or one-on-one sessions) and Role Specific training. In addition, HMIS staff is available to provide technical assistance to users that need help correcting data entry errors.

Monthly Monitoring –On a quarterly basis, the HMIS staff will provide to the HMIS committee data quality reports for all agencies using HMIS, and offer additional training to those agencies that need to improve their data quality. The quarterly reports for the HMIS committee will provide information on timeliness, bed utilization rates, and data completeness for all projects.

Quarterly Monitoring - On a quarterly basis, the HMIS staff will provide to the HMIS committee data quality reports for all agencies using HMIS, and offer additional training to those agencies that need to improve their data quality. The quarterly reports for the HMIS committee will provide information on timeliness, bed utilization rates, and data completeness for all projects.

HMIS CommitteeThis HMIS Committee of his HMIS Committee of the CoC Board of Directors is responsible for reviewing data quality reports quarterly and working with HMIS staff and providers to correct data that does not comply with community-wide standards as established in the Data Quality Plan. The HMIS Committee will maintain an ongoing relationship with HMIS to identify training needs for the continuum based on the reports provided by the HMIS Team.

The quarterly data quality reports provided by the HMIS Team to the HMIS Committee will include several categories: CoC, ESG, HOPWA, RHY, VA, PATH, and a Universal Data Quality Report. The Universal Data Quality Report will include all agencies that do not have program-specific data element requirements based on a Federal funding source.

7

The HMIS Team will provide these reports to the HMIS Committee members with a recommended plan of action for the agencies out of compliance. The HMIS Committee will discuss and vote to approve the recommended plan. An e-mail should be sent by the HMIS Lead to the agencies identified as having data quality issues within 5 business days of the committee meeting, and saved for record keeping purposes.

At the next quarterly review, if the agency does not show significant improvement in the areas identified by the HMIS Team, the HMIS Committee Chair will report the agency with issues to the CoC Board of Directors. Additionally, the HMIS Committee may require that the agencies provide a corrective action plan which may include HMIS refresher training for all staff members in the project and technical assistance to the agencies’ program manager(s).

If the data quality issues are not resolved by the third quarterly review, the HMIS Committee may also request a meeting with agency directors, and recommend to the CoC Board that the agency’s access to HMIS be suspended.

8

IV APPENDICES

Appendix A: Suggestions for Accuracy

Attend regular trainings sponsored by the Haven for Hope HMIS team.

You may request training online through the virtual helpdesk at HMIS.spport@havenforhope.org under the HMIS Resources section. See types of trainings below in the “HMIS Lead Agency” section of this plan.

Read through the training guide posted online as needed.

An up-to-date training guide is available online at www.havenforhope.org under the HMIS Resources section. It covers most sections within HMIS and can be a helpful tool to ensure data is entered accurately.

Maintain a personal Data Quality Log

As you find data quality issues, keep a log of information. Issues include items such as duplicate files or incorrect demographic information. If you aren’t sure how to correct a data entry mistake, submit a service request online instead of ignoring the data quality issue. The virtual helpdesk can be found online at HMIS.support@havenforhope.org under the HMIS Resources section. A member of the HMIS team will be able to assist you with technical issues such as these.

Maintain uniform data collection techniques. Some examples include:

No numerals in name fields (except Suffix)

Use “01/01” for Month/Day if only year of birth is known.

Spot-check data entered monthly and compare to paper documents.

If a copy of an official document is obtained, compare those responses with the responses within HMIS to perform data quality checks on intake staff.

Have a document explaining your individual intake forms.

Have a document available to all intake/data entry staff that includes explanations on all questions covered on intake forms. HUD offers examples on the HUD Exchange.

Work with intake specialists on interviewing techniques and wording of questions.

Regular training of intake staff to improve on interviewing techniques and wording of questions can assist in increasing consistency of data quality.

9

Review HUD’s HMIS Data Standards.

The 2014 HMIS Data Standards, Released August 2016, Version 5.1, are available online at www.hudexchange.info. This resource includes information on required data elements, when they should be captured (at entry or exit), and which types of programs are responsible for capturing them. Make sure your programs are meeting HUD’s baseline compliance requirements.

Appendix B: References

Homeless Resource Exchange. U.S. Department of Housing and Urban Development. https://www.hudexchange.info/resources/documents/HMIS-Data-Standards-Manual.pdf

Homeless Resource Exchange. U.S. Department of Housing and Urban Development.<http://www.hudhre.info/documents/HUDDataQualityToolkit.pdf>

Homeless Resource Exchange. U.S. Department of Housing and Urban Development.<http://www.hudhre.info/documents/4thHomelessAssessmentReport.pdf>

Homeless Resource Exchange. U.S. Department of Housing and Urban Development.<http://www.hudhre.info/documents/DataQualityMonitoringPlan_Handout.pdf>

Homeless Resource Exchange. U.S. Department of Housing and Urban Development. < http://www.hudhre.info/documents/VPHD_HMISDataStandards.pdf>

Department of VA. U.S. Department of Veterans Affairs <http://www.va.gov/

Homeless Resource Exchange. U.S. Department of Housing and Urban Development. https://www.hudexchange.info/resources/documents/HMIS-Data-Standards-Manual.pdf

Appendix C: Universal Data Quality Thresholds

10

Pr

oject

Type

Requ

irem

ent

Unive

rsal D

ata E

lemen

tAl

l Clie

nts,

Adult

s, or

HOH

Acce

ptab

le %

Null/

Not

Colle

cted

Acce

ptab

le %

Clien

t Doe

sn't

Know

/Ref

used

Acce

ptab

le %

Null/

Not

Colle

cted

Acce

ptab

le %

Clien

t Doe

sn't

Know

/Ref

used

Acce

ptab

le %

Null/

Not

Colle

cted

Acce

ptab

le %

Clien

t Doe

sn't

Know

/Ref

used

Acce

ptab

le %

Null/

Not

Colle

cted

Acce

ptab

le %

Clien

t Doe

sn't

Know

/Ref

used

Acce

ptab

le %

Null/

Not

Colle

cted

Acce

ptab

le %

Clien

t Doe

sn't

Know

/Ref

used

Nam

eAl

l0%

0%0%

0%0%

0%1%

10%

0%0%

Socia

l Sec

urity

Num

ber

All

0%2%

0%1%

0%2%

1%10

%0%

3%Da

te of

Birth

All

0%0%

0%0%

0%0%

1%10

%0%

0%Ra

ceAl

l0%

2%0%

1%0%

2%1%

5%0%

3%Et

hnici

tyAl

l0%

2%0%

1%0%

2%1%

5%0%

3%Ge

nder

All

0%0%

0%0%

0%0%

1%5%

0%0%

Vete

ran S

tatu

sAd

ults

0%2%

0%1%

0%2%

1%5%

0%3%

Disa

bling

Cond

ition

All

0%2%

0%1%

0%2%

1%5%

0%2%

Living

Situ

ation

HO

H &

Adult

s0%

2%0%

1%0%

0%1%

5%0%

2%Pr

oject

Entry

Dat

eAl

l0%

0%0%

0%0%

0%0%

0%0%

0%Pr

oject

Exit D

ate

All

0%0%

0%0%

0%0%

0%0%

0%0%

Desti

natio

nAl

l5%

1%2%

1%5%

2%20

%5%

5%1%

Perso

nal ID

All

2%2%

0%0%

0%0%

5%5%

0%0%

Hous

ehold

ID

All

0%0%

0%0%

0%0%

0%0%

0%0%

Relati

onsh

ip to

Hea

d of H

ouse

hold

All

0%0%

0%0%

0%0%

1%10

%0%

1%Cli

ent L

ocati

onHO

H0%

0%0%

0%0%

0%0%

0%0%

0%

Unive

rsal D

ata Q

ualit

y Thr

esho

lds FY

2016

Dem

ogra

phics

ES, D

ay Sh

elter

TH, P

SH, S

H, O

PH Pr

ev/R

RHSt

reet

Out

reac

hSS

O/Ot

her H

omele

ss

Assis

tanc

e Pro

vider

Unive

rsal T

hres

holds

Prog

ram

Spe

cific

All C

lient

s, A

dults

, HO

H an

d/or

U

nacc

ompa

nied

You

thES

TLP

Data

Ele

men

tsAl

l Clie

nts,

Adu

lts,

HOH,

or U

nacc

ompa

nied

You

th

Acce

ptab

le %

Nul

l/Not

Co

llect

ed/C

lient

Doe

sn't

Know

/Ref

used

Acce

ptab

le %

Nul

l/Not

Co

llect

ed/C

lient

Doe

sn't

Know

/Ref

used

Inco

me

and

sour

ceHO

H a

nd A

dults

N/A

5%No

n-Ca

sh B

enefi

tsHO

H a

nd A

dults

N/A

5%He

alth

Insu

ranc

eAL

L5%

5%Ph

ysic

al D

isab

ility

AL

L5%

5%De

velo

pmen

tal D

isab

ility

AL

L5%

5%Ch

roni

c H

ealth

Con

ditio

nAL

L5%

5%M

enta

l Hea

lth P

robl

emAL

L5%

5%Su

sbta

nce

Abus

eAL

L5%

5%Se

rvice

Pro

vide

d- P

ATH

Fund

edHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%Re

ferr

als P

rovi

ded-

PAT

H F

unde

dHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%RH

Y: B

CP S

tatu

sAL

L5%

N/A

Sexu

al O

rient

ation

HO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%La

st G

rade

Com

plet

edHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%Sc

hool

Sta

tus

HOH

, Adu

lts a

nd U

nacc

ompa

nied

You

th

5%5%

Empl

oym

ent S

tatu

sHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%Ge

nera

l Hea

lth S

tatu

sHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%De

ntal

Hea

lth S

tatu

sHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%M

enta

l Hea

lth S

tatu

sHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%Pr

egna

ncy

Stat

usFe

mal

e- H

OH,

Adu

lts a

nd U

nacc

ompa

nied

You

th

5%5%

Form

erly

a W

ard

of C

hild

War

fare

/Fos

ter C

are

Agen

cyHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%Fo

rmer

ly a

War

d of

Juve

nile

Justi

ce S

yste

m

HOH

, Adu

lts a

nd U

nacc

ompa

nied

You

th

5%5%

Youn

g Pe

rson

's cr

itica

l Iss

ues

HOH

, Adu

lts a

nd U

nacc

ompa

nied

You

th

5%5%

Refe

rral

sour

ceHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%Co

mm

erci

al S

exua

l Exp

loita

tion

HOH

, Adu

lts a

nd U

nacc

ompa

nied

You

th

5%5%

Com

mer

cial

Lab

or E

xplo

itatio

nHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%Tr

ansi

tiona

l, Ex

it-ca

re, o

r Afte

rcar

e Pl

an a

nd A

ction

sHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%Pr

ojec

t Com

pleti

on S

tatu

sHO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%Fa

mily

Reu

nific

ation

Ach

ieve

d HO

H, A

dults

and

Una

ccom

pani

ed Y

outh

5%

5%

Prog

ram

Spe

cific

Dat

a Q

ualit

y Th

resh

olds

FY

2016

RHY

Prog

ram

Spec

ific

Requ

irem

ent

Prev

entio

nRR

HSt

reet

Out

reac

h

Data

Elem

ents

All C

lient

s, Ad

ults

, or H

OHAc

cept

able

% Nu

ll/No

t Co

llect

ed/D

oesn

’t Kn

ow/R

efus

ed

Acce

ptab

le %

Null/

Not

Colle

cted

/Doe

sn't

Know

/Ref

used

Acce

ptab

le %

Null/

Not

Colle

cted

/Clie

nt D

oesn

't Kn

ow/R

efus

edIn

com

e and

sour

ces

HOH

and

Adul

ts5%

5%5%

Non-

Cash

Ben

efits

HOH

and

Adul

ts5%

5%5%

Healt

h In

sura

nce

ALL

5%5%

5%Ph

ysica

l Disa

bilit

y AL

L5%

5%5%

Deve

lopm

enta

l Disa

bilit

y AL

L5%

5%5%

Chro

nic H

ealth

Con

ditio

nAL

L5%

5%5%

HIV/

AIDS

ALL

5%5%

5%M

enta

l Hea

lth Pr

oblem

ALL

5%5%

5%Su

bsta

nce A

buse

ALL

5%5%

5%Do

mes

tic V

iolen

ceHO

H an

d Ad

ults

5%5%

5%Co

ntac

tHO

H an

d Ad

ults

N/A

N/A

5%Da

te o

f Eng

agem

ent

HOH

and

Adul

tsN/

AN/

A5%

Resid

entia

l Mov

e-in

Dat

eAL

LN/

A5%

N/A

Hous

ing A

sses

smen

t Disp

ositi

on

HOH

2%2%

2%Ho

usin

g ass

essm

ent a

t Exit

ALL

5%N/

AN/

A

Prog

ram

Spec

ific D

ata Q

ualit

y Thr

esho

lds F

Y 201

6ES

G

Prog

ram

Spe

cific

Re

quire

men

tSt

reet

Out

reac

h

Data

Ele

men

tsAl

l Clie

nts,

Adu

lts, o

r HO

HAc

cept

able

% N

ull/N

ot

Colle

cted

/Clie

nts D

oesn

't Kn

ow/R

efus

ed

Hous

ing

Stat

us a

t Ent

ry

HOH

and

Adul

ts5%

Inco

me

and

Sour

ceHO

H an

d Ad

ults

5%No

n-Ca

sh B

enefi

ts

HOH

and

Adul

ts5%

Heal

th In

sura

nce

ALL

5%Ph

ysica

l Disa

bilit

y AL

L5%

Deve

lopm

enta

l Disa

bilit

y AL

L5%

Chro

nic

Heal

th C

ondi

tion

ALL

5%HI

V/AI

DS

ALL

5%M

enta

l Hea

lth P

robl

emAL

L5%

Susb

tanc

e Ab

use

ALL

5%Co

ntac

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L5%

Date

of E

ngag

emen

tHO

H an

d Ad

ults

5%Se

rvice

Pro

vide

d-PA

TH F

unde

d HO

H an

d Ad

ults

5%Re

ferr

als P

rovi

ded-

PATH

HOH

and

Adul

ts5%

PATH

Sta

tus

HOH

and

Adul

ts5%

Conn

ectio

n to

SO

ARHO

H an

d Ad

ults

5%

Prog

ram

Spe

cific

Dat

a Q

ualit

y Th

resh

olds

FY

201

6PA

TH

Requ

irem

ent

Prev

entio

nPS

HRR

HTH

Dat

a Ele

men

tAl

l Clie

nts,

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ts, o

r HOH

Acce

ptab

le %

Null/

Not

Colle

cted

/Clie

nt D

oesn

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ow/R

efus

ed

Acce

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/Clie

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oesn

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Acce

ptab

le %

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cted

/Clie

nt D

oesn

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ow

Acce

ptab

le %

Null/

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cted

/Clie

nt D

oesn

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efus

ed

Inco

me

and

sour

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HOH

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5%No

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se B

enefi

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H an

d Ad

ults

5%5%

5%5%

Heal

th In

sura

nce

ALL

5%5%

5%5%

Phys

ical D

isabi

lity

ALL

5%5%

5%5%

Deve

lopm

enta

l Disa

bilit

y AL

L5%

5%5%

5%Ch

roni

c Hea

lth C

ondi

tion

ALL

5%5%

5%5%

HIV/

AIDS

ALL

5%5%

5%5%

Men

tal H

ealth

Pro

blem

AL

L5%

5%5%

5%Su

bsta

nce

Abus

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L5%

5%5%

5%Do

mes

tic V

iole

nce

HOH

and

Adul

ts5%

5%5%

5%Ho

usin

g Ass

essm

ent D

ispos

ition

HOH

2%2%

2%2%

Hous

ing A

sses

smen

t at E

xitAL

L5%

N/A

N/A

N/A

Prog

ram

Spec

ific D

ata Q

ualit

y Thr

esho

lds F

Y 20

16

CoC

Prog

ram

Spec

ific

Prog

ram

Spe

cific

Requ

irem

ent

PHTH

Data

Ele

men

tsAl

l Clie

nts,

Adu

lts, o

r HO

HAc

cept

able

% N

ull/N

ot

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cted

/ Clie

nt D

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efus

ed

Acce

ptab

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l/Not

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llect

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lient

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sn't

Know

/Ref

used

Hous

ing

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us a

t Ent

ry

HOH

and

Adul

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5%In

com

e an

d So

urce

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d Ad

ults

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Non-

Cash

Ben

efits

HOH

and

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5%He

alth

Insu

ranc

eAL

L5%

5%Ph

ysica

l Disa

bilit

y AL

L5%

5%De

velo

pmen

tal D

isabi

lity

ALL

5%5%

Chro

nic H

ealth

Con

ditio

nAL

L5%

5%HI

V/AI

DSAL

L5%

5%M

enta

l Hea

lth P

robl

emAL

L5%

5%Su

bsta

nce

Abus

eAL

L5%

5%Do

mes

tic V

iole

nce

HOH

and

Adul

ts5%

5%Se

rvice

Pro

vide

d-HO

PWA

ALL

5%5%

Hous

ing

Asse

ssm

ent a

t Exi

tAL

L5%

5%M

edica

l Ass

istan

ceAl

l hou

seho

ld m

embe

rs w

ith H

IV/A

IDS

5%5%

T-ce

ll an

d Vi

ral L

oad

Onl

y cli

ents

fund

ed in

a H

OPW

A pr

ojec

t with

HIV

/AID

S5%

5%

HOPW

A

Prog

ram

Spe

cific

Dat

a Q

ualit

y Th

resh

olds

FY

2016

Prog

ram

Spe

cific

Requ

irem

ent

Data

Ele

men

tsAl

l Clie

nts,

Adu

lts, o

r HOH

Acce

ptab

le %

Nul

l/Not

Co

llect

ed/C

lient

Doe

sn't

Know

/Ref

used

Acce

ptab

le %

Clie

nt

Does

n't K

now

/Ref

used

Acce

ptab

le %

Nu

ll/No

t Col

lect

ed

Acce

ptab

le %

Cl

ient

Doe

sn't

Know

/Ref

used

Inco

me

and

sour

ces

HOH

and

Adul

ts5%

5%5%

5%No

n-Ca

sh B

enefi

ts

HOH

and

Adul

ts5%

5%5%

5%He

alth

Insu

ranc

eAL

L5%

5%5%

5%Ph

ysica

l Disa

bilit

yAL

LN/

AN/

A5%

5%De

velo

pmen

tal D

isabi

lity

ALL

N/A

N/A

5%5%

Chro

nic H

ealth

Con

ditio

nAL

LN/

AN/

A5%

5%HI

V/AI

DSAL

LN/

AN/

A5%

5%M

enta

l Hea

lth

ALL

N/A

N/A

5%5%

Subs

tanc

e Ab

use

ALL

N/A

N/A

5%5%

Dom

estic

Vio

lenc

eHO

H an

d Ad

ults

N/A

N/A

5%5%

Serv

ices P

rovi

ded-

SSVF

ALL

5%5%

N/A

N/A

Fina

ncia

l Ass

istan

ce- S

SVF

ALL *

5%5%

N/A

N/A

Last

gra

de co

mpl

eted

HO

H, A

dults

and

Una

ccom

pani

ed y

outh

5%

5%5%

5%Em

ploy

men

t Sta

tus

ALL

N/A

N/A

5%5%

Gene

ral H

ealth

Sta

tus

HOH,

Adu

lts a

nd U

nacc

ompa

nied

you

th

N/A

N/A

5%5%

Resid

entia

l Mov

e-in

Dat

eAL

L5%

(RRH

onl

y)5%

(RRH

onl

y)N/

AN/

AVe

tera

n's i

nfor

mati

on#

5%5%

N/A

N/A

Perc

ent o

f AM

I HO

H 5%

5%N/

AN/

ALa

st P

erm

anen

t Add

ress

HOH

5%5%

N/A

N/A

VAM

C St

ation

Num

ber

HOH

5%5%

5%5%

SSVP

HP

Targ

eting

HOH

5%

(HP

only

)5%

(HP

only

)N/

AN/

AUs

e of

Oth

er C

risis

Serv

ices

HOH

and

Adul

ts5%

5%N/

AN/

A

* =

limite

d to

thos

e w

ho re

ceiv

e fin

ancia

l ass

istan

ce

Prog

ram

Spe

cific D

ata

Qua

lity

Thre

shol

ds F

Y 20

16

# =

All p

erso

ns w

ho a

nsw

ered

'YES

" to

Vete

ran

Stat

us

SSVF

VASH

VA