Philadelphia Continuum of Care HMIS Data Quality Plan

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1 Philadelphia Cntinuum f Care HMIS Data Quality Plan Backgrund Fr mre than a decade, Cngress has expressed the need fr better lcal and natinal infrmatin abut persns experiencing hmelessness in a series f Cngressinal directives, beginning with the FY 1999 U.S. Department f Husing and Urban Develpment (HUD) Apprpriatins Act. In 2001 Cngress directed HUD t take the lead in requiring every jurisdictin t have unduplicated clientlevel data within three years. In subsequent years, Senate and Huse Apprpriatins Cmmittee reprts have directed HUD t assist cmmunities in implementing lcal Hmeless Management Infrmatin Systems (HMIS) and t develp an Annual Hmeless Assessment Reprt (AHAR) that is based n HMIS data. HMIS is nw used by the fllwing federal partners and their respective prgrams in the effrt t end hmelessness: U.S. Department f Health and Human Services (HHS) U.S. Department f Husing and Urban Develpment (HUD) U.S. Department f Veterans Affairs (VA) Philadelphia Cntinuum f Care s (CC) HMIS is a client infrmatin system designed t recrd and stre client-level infrmatin n the characteristics and service needs f persns experiencing hmelessness. HMIS assists the Philadelphia CC t becme better infrmed abut the extent and nature f hmelessness ver time. Specifically, HMIS can be used t prduce an unduplicated cunt f persns experiencing hmelessness, understand patterns f service use, measure the effectiveness f hmeless prgrams, and assist in the efficient prvisin f services t hmeless persns. HMIS is als used t help with system planning and design including lng-term strategic planning and shrter-term evaluatins and interventins. The City f Philadelphia Office f Hmeless Services (OHS) has been designated by the Philadelphia CC as the HMIS Lead Agency in accrdance with federal HMIS rules and regulatins. Purpse The purpse f the Philadelphia Cntinuum f Care Hmeless Management Infrmatin System Data Quality Plan (HMIS Data Quality Plan) is t standardize expectatins and prvide guidance t HMISparticipating prjects n the extent, cmpleteness, and quality data elements entered int HMIS t meet participatin and reprting requirements established by HUD and the federal partners. In ding s, the CC hpes t streamline the prcess f cmpleting Annual Perfrmance Reprts (APR) fr HUD and submitting infrmatin fr the Annual Hmeless Assessment Reprt in full cmpliance with HUD s expectatins. In additin, the HMIS Data Quality Plan is intended t assist the CC in its preparatins fr the new system-wide perfrmance measures cntained in the McKinney- Vent Hmeless Assistance Act as amended by S. 896 The Hmeless Emergency Assistance and Rapid Transitin t Husing (HEARTH) Act f Further, the imprvement f HMIS data will assist the CC t cntinue t achieve a high scre in the cmpetitive annual applicatin fr CC Prgram funding.

2 Develpment Prcess HMIS Data Quality Plan The HMIS Data Quality Plan was develped thrugh a cllabrative effrt acrss hmeless service prviders and spearheaded by the HMIS & HEARTH Data Subcmmittee f the McKinney Public/Private Strategic Planning Cmmittee, which included representatives frm the fllwing rganizatins: City f Philadelphia Office f Hmeless Services (frmerly Office f Supprtive Husing), Peple s Emergency Center, Kutztwn University, Prject HOME, Dignity Husing, The Salvatin Army Red Shield Family Residence, SELF, Inc., and Temple University. Definitins Prject vs Prgram: Acrss the federal agencies the terms prject and prgram are used differently. In this dcument, and fr the purpses f data cllectin in HMIS, a prgram refers t the federal funding surce (e.g., HUD CC, HHS PATH, VA SSVF etc.). A prject refers t a distinct unit f an rganizatin, which may r may nt be funded by HUD r the federal partners, that prvides services and/r husing and is identified by the CC as part f its service system. A cntinuum prject can be classified as ne that prvides husing (husing prject) r ne that des nt prvide husing (services prject). Prjects may enter data directly int HMIS r submit data extract files fr uplad int HMIS. Prjects which submit via data extract have chsen t participate in HMIS in this way because they have their wn prprietary data systems in place t track and maintain data n their cnstituents. They create an annual exprt fr imprt int HMIS. Husing Prject: Prvides vernight accmmdatins and whse primary purpse is t meet the specific needs f peple wh are experiencing hmelessness. This includes prjects classified as the fllwing under the data element Prject Type: Emergency Shelter, Safe Haven, Transitinal Husing, Rapid Re-Husing, Permanent Supprtive Husing, Permanent Husing with Services, and Permanent Husing: Husing Only. Services Prject: Des nt prvide husing and whse primary purpse is t prvide services that meet the specific needs f peple wh are experiencing r at-risk f hmelessness. This includes prjects classified as the fllwing under the data element Prject Type: Crdinated Assessment, Hmelessness Preventin, Street Outreach, Day Shelter, Services Only, and Other. HMIS Universal Data Elements (UDE) are elements required t be cllected by all prjects participating in HMIS, regardless f funding surce. They establish the baseline data cllectin requirements fr all cntributing CC prjects; and are the basis fr prducing unduplicated estimates f the number f peple experiencing hmelessness, accessing services frm hmeless assistance prjects, basic demgraphic characteristics f peple experiencing hmelessness, and patterns f service use, including infrmatin n shelter stays and hmelessness ver time. Prgram Specific Data Elements (PSDE) differ frm the Universal Data Elements in that n ne prject must cllect every single element in this sectin. Required data elements are dictated by the reprting requirements set frth by funding surce. HMIS Data Quality refers t the extent that data recrded in HMIS accurately reflects the same infrmatin in the real wrld. T meet the Philadelphia CC s gal f presenting accurate and cnsistent infrmatin n hmelessness, it is critical that HMIS have the best pssible representatin f reality as it relates t hmeless peple and the prgrams that serve them. Specifically, the gal is t recrd the mst accurate, cnsistent and up-t-date infrmatin in rder t draw reasnable June 1, 2017 HMIS Data Quality Plan Page 2

3 cnclusins abut the extent f hmelessness and the impact f hmeless services and t utilize fr planning and evaluatin purpses. HMIS User means the individual wh uses r enters data in an HMIS r a cmparable database apprved by the CC. HMIS Lead means the entity designated by the Cntinuum f Care in accrdance with the HMIS Prpsed Rule2 (24 CFR Part 580) t perate the Cntinuum s HMIS n the Cntinuum s behalf. HMIS System Administratr means the individual(s) whse jb it is t manage the HMIS implementatin at the lcal level: enrlling prgrams and managing apprpriate use, supprting users thrugh cnnectin t, r direct prvisin f, user training, and verseeing system setup. Applicability f Data Quality Standards The Data Quality Standards cntained herein are applicable t all HMIS participating prjects, including prjects that enter data directly int HMIS and prjects that submit data extract files fr uplad int HMIS. Fr thse prjects that submit data extract files, the HMIS Data Quality Standards apply t the entry f data int the agency s in-huse client infrmatin system. The Standards als apply t all actins taken by prviders leading up t the creatin f their extract files; in ther wrds, all infrmatin entered int the data systems used t create extract files must cnfrm t the guidelines set ut in this dcument. Key Dcuments Key dcuments needed as supprting references t this dcument are listed belw: a. Federal Register, Vl. 69, N. 146, Part II, Department f Husing and Urban Develpment, Hmeless Management Infrmatin Systems (HMIS); Data and Technical Standards Final Ntice; Ntice, July 30, 2004 ( HUD HMIS 2004 Final Ntice ), including subsequent rule releases, and b. U.S. Department f Husing and Urban Develpment, Office f Cmmunity Planning and Develpment, 2017 Hmeless Management Infrmatin System (HMIS) Data Standards: Manual and Dictinary Versin 1.2, July 2017 ( 2017 HMIS Data Standards ), including succeeding revisins, and c. The McKinney-Vent Hmeless Assistance Act as amended by S. 896 The Hmeless Emergency Assistance and Rapid Transitin t Husing (HEARTH) Act f HMIS Data Quality Standards The HMIS Data Quality Standards fr the Philadelphia CC are split int six (6) categries: Timeliness, Cmpleteness, Accuracy, Cnsistency, Mnitring, and Incentives. Unless therwise nted, all HMIS participating prgrams, including thse that prvide data extract files fr uplad int HMIS, are expected t achieve and maintain the Data Quality Standards. Training f HMIS system users is recgnized t be imprtant in assuring the cmpleteness, accuracy, and cnsistency f data. T that end, data quality will be supprted thrugh timely and apprpriate system training, including the utilizatin f methdlgies such as Train-the-Trainer and Cmputer- Based Training (CBT). June 1, 2017 HMIS Data Quality Plan Page 3

4 1. Timeliness The purpse f this timeliness standard is t reduce human errr that ccurs when t much time has elapsed between data cllectin (service transactin) and data entry int HMIS. The individual ding the data entry may be relying n handwritten ntes r his/her wn recall f a case management sessin, service transactin, r prgram exit date; therefre, the sner the data is entered, the better chance the data will be crrect. Timely data entry als ensures that data is as clse t real-time as pssible and accessible when it is needed either pr-actively (fr mnitring purpses, publishing infrmatin t increase awareness, r t meet reprting requirements) r reactively (in respnse t a request fr infrmatin r t respnd t inaccurate infrmatin) Timeliness Standard All Prjects will ensure that data elements fr new clients, services, and entry/exits are entered in a timely manner int HMIS. Data must be cllected, at a minimum, at prject entry, during prgram enrllment, and at prject exit accrding t the baselines fund in the Appendix. All prjects are encuraged t cllect all f the required Data Elements as clse t each client s prject entry and exit as pssible. In additin: HMIS participating agencies Emergency Husing prgrams must cllect the required Data Elements within the timeframe established in the Scial Wrker/Case Management Perfrmance Standards and Hmeless Management Infrmatin System Standards (HMIS) fund in the OHS Emergency Husing Standards. Hmelessness Preventin, Husing Retentin, and Rapid Re-husing Prgrams must cllect the HUD-required Data Elements in accrdance with the timeframes set frth in the mst recent Request fr Prpsals as well as the prgram s mst recent OHS cntract dcuments. Once cllected, prjects will enter the data in HMIS accrding t the fllwing timeframes: HMIS participating agencies Emergency Husing Prjects: All required UDEs and PSDEs will be entered within 24 hurs f the data cllectin. Transitinal and Permanent Supprtive Husing Prjects receiving funding thrugh OHS and/r the McKinney-Vent Act: All required UDEs and PSDEs will be entered within three (3) days f data cllectin. OHS Centralized Intake Sites, Service-Only, and After Hurs Prcessing Sites: All required UDEs will be entered at the time f data cllectin. Hmelessness Preventin, Husing Retentin, Outreach and Rapid Re-husing Prgrams: All required UDEs and PSDEs will be entered at the time f data cllectin. OHS Emergency Assistance and Respnse Unit: All required UDEs and PSDEs will be entered at the time f data cllectin. Nn-Cntracted Emergency Husing, Transitinal Husing, and Permanent Supprtive Husing Prjects (Prjects nt receiving funding thrugh OHS and/r June 1, 2017 HMIS Data Quality Plan Page 4

5 the McKinney-Vent Act): All UDEs will be entered within three (3) days f data cllectin. 2. Cmpleteness The purpse f cmpleteness is t ensure sufficient demgraphic and service use data is cllected t facilitate cnfident reprting and analysis n the extent and characteristics f persns experiencing hmelessness in Philadelphia including: Unduplicated cunts f clients served at the lcal level Patterns f use f peple entering and exiting the hmeless assistance system Evaluatin f the effectiveness f hmeless systems Systems planning fr future husing and service needs In effect, cmplete data tells the full stry f hmelessness Cmpleteness Standard All Prjects will ensure each f their required Data Elements is entered int HMIS fr all clients served by the prject. Please, refer t the table belw fr a detailed listing f the required Data Elements. In additin, all Prjects will make reasnable effrts t limit the percentage f missing/null, dn t knw, refused, and data nt cllected entries t 10% r less. 3. Accuracy The purpse f accuracy is t ensure that the data hused in HMIS is the best pssible representatin f reality as it relates t peple wh are experiencing hmelessness and the prjects in which they participate Accuracy Standard All Prjects will ensure that data entered in HMIS accurately reflects the infrmatin prvided by the client. Prject staff will nt knwingly enter int HMIS inaccurate r false infrmatin. T the extent that clients and ther agencies supplying infrmatin have prvided accurate data, HMIS users are respnsible fr the accuracy f the data they enter int the HMIS. Immediately upn discvery, inaccurate r utdated data will be updated by the prject. In additin, respnses f Dn t Knw and Refused will be updated immediately nce the infrmatin is knwn. 4. Cnsistency The purpse f cnsistency is t ensure a cmmn interpretatin f questins, answers, and which fields need cmpletin in HMIS Cnsistency Standard All data required t be in HMIS will be cllected and entered in a cmmn and cnsistent manner acrss all Prjects. T that end, all HMIS users will cmplete an initial rientatin befre accessing the HMIS. As part f the rientatin, all new HMIS users will review Sectins 3 and 4 f the 2017 HMIS Data Standards, which utlines the Universal and Prgram Specific Data Elements, including their ratinale, cllectin pint(s), data cllectin instructins, and respnse categry descriptins. All existing HMIS users are encuraged t review this dcument n a quarterly basis. 5. Mnitring June 1, 2017 HMIS Data Quality Plan Page 5

6 The purpse f mnitring is t ensure that the HMIS Data Quality Standards are met t the greatest pssible extent and that data quality issues are quickly identified and reslved. When data quality benchmarks are met, reprting will be mre reliable and can be used t evaluate service delivery, prgram design and effectiveness, and efficiency f the system. All HMIS participating agencies are expected t meet the data quality benchmarks described in this dcument. T achieve this, HMIS data will be mnitred and reviewed in accrdance with the schedule utlined in this sectin. All mnitring will be cnducted by the OHS with the full supprt f the CC Mnitring Standard All Prjects are expected t meet the HMIS Data Quality Standards described in this dcument. Each Prject is respnsible fr mnitring its wn data and establishing internal data quality cntrl prcedures. Prjects are encuraged t utilize all applicable reprts that can be generated directly frm HMIS. In additin, the HMIS Lead Agency will mnitr HMIS data n the prject and system levels in accrdance with this Data Quality Plan. Prjects that fail t meet the data standards will be asked by the HMIS Lead Agency t submit a written plan that details hw they will take crrective actin and the timeline fr ding s. The plan will be submitted t and mnitred by, the CC Advisry Cmmittee. Data quality scring by each agency plays a significant rle during funding cnsideratin, agencies failing t meet minimum Data Quality Standard requirements may face funding lss r reductin Rles and Respnsibilities Data Timeliness: The OHS supprt staff will measure timeliness by running custm reprts designed by the HMIS staff in ClientTrack. Prgrams f different types will be reviewed separately. The agency will be required t imprve their data timeliness r prvide an explanatin befre the next mnth s reprt. Data Cmpleteness: The HMIS supprt staff will measure cmpleteness by running APRs, Universal Data Quality, r custm Data Explrer reprts, and cmpare any missing rates t the data cmpleteness benchmarks. The agency will be required t imprve their data cmpleteness rate r prvide an explanatin befre the next mnth s reprt. Data Accuracy: The HMIS supprt staff will review surce dcumentatin during the annual site visits. The agency staff is respnsible t make this dcumentatin available upn request. Outreach prgrams may be exempt frm the data accuracy review Mnitring Frequency Quarterly Review: Data Timeliness and Data Cmpleteness Annual Review site visits: Data Accuracy Other: Data quality mnitring may be perfrmed utside f the regularly scheduled reviews, as needed r if requested by prgram funders r ther interested parties (the agency itself, HMIS Lead Agency, CC, HUD, r ther Federal and lcal gvernment agencies) 5.4. Cmpliance Data Timeliness: The average timeliness rate in any given quarter shuld be within the allwed timeframe. June 1, 2017 HMIS Data Quality Plan Page 6

7 Data Cmpleteness: There shuld be n missing (null) data fr required data elements. Respnses that fall under unknwn (dn t knw r refused) shuld nt exceed the allwed percentages in any given quarter. Husing prviders shuld stay within the allwed utilizatin rates. Data Accuracy: The percentage f client files with inaccurate HMIS data shuld nt exceed 10%. (Fr example, if the sampling includes 10 client files, then 9 ut f 10 f these files must have the entire set f crrespnding data entered crrectly in HMIS.) 6. Incentives The purpse f incentives is t prvide psitive re-enfrcement t Philadelphia CC service prviders wh achieve and maintain the level f data quality utlined in this HMIS Data Quality Plan Incentives Standard Prjects with the best perfrmance with regards t the Data Quality Standards will be recgnized by the CC Advisry Cmmittee. Prjects that receive CC Prgram funding will submit data quality statistics in their annual renewal applicatin t the OHS. One f the criteria n which the prject s renewal applicatin will be scred will be the prject s achievement f the Data Quality Standards. Prjects are encuraged t develp their wn internal incentives. Data Cllectin Requirements The gal f the CC is t have 85% r mre f HMIS participatin rate. Meaning, we want t have mre than 85% f all hmeless service agencies within the CC, utilizing the single HMIS system that the CC cntracted. Each husing prject participating in HMIS is encuraged and expected t have an average f 90% r mre f daily bed utilizatin rate. The CC recgnizes that there may be instances when cmplete client data may nt be cllected, but every participating agencies are expected t have n mre than 10% errr rate. The errr rate includes, but nt limited t the number f invalid data, Dn t Knw, Refused etc. entries in HMIS. Universal Data Element (UDE) Cllectin Summary Applicable Prjects: All HMIS Participating Prjects, regardless f funding surce, including but nt limited t: Emergency, Transitinal, and Permanent Supprtive Husing Hmelessness Preventin Rapid Re-Husing OHS Centralized Intake Sites After Hurs Prcessing Sites Emergency Assistance and Respnse Unit June 1, 2017 HMIS Data Quality Plan Page 7

8 Cllected Fr Cllectin Pint Data Element All HH Adults Recrd Prject Prject Update Creatin Start Exit 3.1 Name X X 3.2 Scial Security Number X X 3.3 Date f Birth X X 3.4 Race X X 3.5 Ethnicity X X 3.6 Gender X X 3.7 Veteran Status X X 3.8 Disabling Cnditin X X 3.10 Prject Start Date X X 3.11 Prject Exit Date X X 3.12 Destinatin X X 3.15 Relatinship t Head f Husehld X X 3.16 Client Lcatin X X X 3.20 Husing Mve-in Date X X Living Situatin X X X These are the minimum data cllectin standards as established by federal partners. OHS-cntractual requirements supersede these baseline standards, if applicable. Prgram Specific Data Elements (PSDE) The fllwing cmmn PSDEs are required fr Hmeless Preventin, Emergency Husing (EH), Transitinal Husing (TH), Rapid Re-Husing (RRH), and Permanent Supprtive Husing (PSH) prjects receiving funding frm the fllwing surces: City f Philadelphia OHS HUD Cntinuum f Care Prgram (CC) HUD Emergency Slutins Grants Prgram (ESG) HUD-Veterans Affairs Supprtive Husing Prgram (HUD/VASH) June 1, 2017 HMIS Data Quality Plan Page 8

9 Cllected Fr Data Element All HH Adults Prject Start Occurrence Pint Cllectin Pint Update as Inf Changes Annual Assessment Prject Exit 4.2 Incme and Surces X X 4.3 Nn-Cash Benefits X X 4.4 Health Insurance X 4.5 Physical Disability 4.6 Develpmental Disability 4.7 Chrnic Health Cnditin 4.8 HIV/AIDS 4.9 Mental Health Prblem 4.10 Substance Abuse 4.11 Dmestic Vilence 4.12 Cntact X X 4.13 Date f Engagement X X X 4.14 Bed-Night Date X X Husing 4.18 Assessment Dispsitin X X These are the minimum data cllectin standards as established by federal partners. OHS-cntractual requirements supersede these baseline standards, if applicable. Please refer t the 2014 HMIS Data Standards (including succeeding revisins) fr infrmatin n required PSDEs fr prjects receiving funding frm the fllwing surces: HUD Husing Opprtunities fr Persns with AIDS Prgram (HOPWA) Duratin HHS Runaway and Hmeless Yuth Prgram (RHY) HHS Prjects fr Assistance in Transitin frm Hmelessness (PATH) VA Supprtive Services fr Veteran Families Prgram (SSVF) This plan must be reviewed annually and updated as needed by the Philadelphia Cntinuum f Care. June 1, 2017 HMIS Data Quality Plan Page 9

10 Update Lg Created: August 8, 2011 HMIS Data Quality Plan Reviewed and Reapprved: March 18, 2015 August 29, 2016 September 11, 2017 Elizabeth G. Hersh Directr, City f Philadelphia Office f Hmeless Services Date Jhn Ducff Chairpersn, Philadelphia Cntinuum f Care Bard Date June 1, 2017 HMIS Data Quality Plan Page 10