Improving Your AHAR Submission July 2009
Agenda 1. Introduction to the AHAR 2. Key AHAR Reporting Requirements 3. Data Collection and Submission Process 4. Data Quality Issues • Common data quality problems • Review of the bed utilization tool 5. Tips and Tools for AHAR Participation • Strategies for increasing bed coverage • Monitoring and improving data quality 6. Questions and Answers
AHAR Participation HUD emphasis on HMIS and AHAR participation: • Increasing emphasis on HMIS implementation and AHAR participation through Co. C competitive process • AHAR participation status is a question in HUD’s Co. C funding application • AHAR is the primary source of data on the extent and nature of homelessness nationwide • HPRP and HEARTH Act require HMIS participation
AHAR Schedule When are data reported to the AHAR? Reporting Period Data Collection Period 2008 AHAR October 2007 – September 2008 October – January 2009 AHAR October 2008 – September 2009 October – December 2009 2010 AHAR October 2009 – September 2010 October – December 2010
2009 AHAR Schedule Activity Schedule 2009 AHAR Reporting Period Ends September 30, 2009 AHAR Exchange: Webinar and Conference Call Training September 14 – September 25, 2009 Submit Complete Draft of AHAR Data November 15, 2009 Ongoing Review of AHAR Data by Research Team Within 2 days of receipt Submit Complete and Final AHAR Data December 15, 2009 HUD Publishes 2009 AHAR Report June 2010
Review: AHAR Reporting Requirements What data are reported to the AHAR? 1. HMIS data: – Based on HUD’s Universal Data Elements – Limited to emergency shelters and transitional housing programs only 2. Co. C Exhibit 1 data: – Housing Inventory data – Populations Chart – Subpopulations Chart
Review: AHAR Reporting Requirements (con’t. ) HMIS data: – An unduplicated count of persons within four primary reporting categories (ES-IND, ES-FAM, TH-IND, and THFAM) – Persons should be reported in multiple categories if they were served accordingly. (AHAR Exchange adjusts for cross-over. ) – Only HMIS participating programs provide data. (AHAR Exchange has built-in adjustment factors to account for non -participation. )
Review: AHAR Reporting Requirements (con’t) Co. C Exhibit 1 data: 1. Accurate bed inventory information is critical—used to calculate adjustment factor, bed utilization rates, and understand possible biases in program participation. 2. At present, Co. C Exhibit 1 is the only source of unsheltered counts, and the reliability of street counts can vary. 3. Until the program-specific data elements are incorporated, the subpopulation counts are an important source of information.
AHAR Reporting Requirements: New for 2009 AHAR Changes to the 2009 AHAR: • Supplemental report on veterans that relies on current reporting requirements (ES-IND, ES-FAM, TH-IND, and TH-FAM) but applied to veterans only – Excludes household members other than the veterans – AHAR Exchange will be modified accordingly to allow communities to report on veterans separately from all sheltered persons – Priority will be placed on completing the regular submission process before turning to the data on veterans
AHAR Processes and Roles The AHAR reporting period is a 12 -month timeframe: (Oct. 2008 – Sep. 2009). • What does this mean? Anyone who accesses an emergency shelter or transitional housing program during this time period should be included in your AHAR data.
Data Collection & Submission: HMIS Implementation and Monitoring • What should participating communities be doing? 1. Increase the number of providers participating in HMIS to increase bed coverage rates. 2. Confirm bed inventory. 3. Develop and start implementing data quality review procedures (e. g. , bed utilization rates). 4. Identify and fix data quality issues. 5. Develop and test queries for generating AHAR data.
Data Collection & Submission: Data Collection • Communities should continue to pursue the HMIS Implementation and Monitoring activities, but from October to December the priority shifts to data reporting. • What should communities be doing? 1. Obtain data from providers that participated in HMIS for the entire reporting period. 2. Run queries to obtain information for AHAR reporting categories. 3. Work with AHAR Team to fix any errors or inaccurate information. 4. Review data with other knowledgeable people in your community to confirm accuracy of information. 5. Document procedures for future AHARs.
Data Collection & Submission: AHAR Exchange • AHAR Exchange is a web-based data collection tool for communities to report their data • Features of the AHAR Exchange: • Embedded consistency checks and automated calculations • The ability to leave notes for AHAR data collection team about data • Data log that shows who made changes and when • Navigation tools • Reports for local/community use
Review: AHAR Exchange - My Data • The ‘My Data’ page is where the AHAR data should be entered. • There is a separate window for each of the reporting categories.
Review: Example of a reporting category Reporting Status: This will indicate whether you are submitting data for the reporting category. The options are ‘Reporting, ’ ‘Not Reporting, ’ or ‘Zero Provider. ’ Status: This will indicate the current state of your data. The options are ‘Not Started, ’ ‘In Progress, ’ ‘In Review, ’ or ‘Complete. ’ Used in Final AHAR: This will indicate if your data was used in the final AHAR. Validation: This will indicate if the data are valid. If the data are not valid, the errors in the report will appear. % Complete: This indicates the percentage of your data that are complete.
Other AHAR Exchange Features • XML Upload • Built-in data validation • Send messages to AHAR Data Collection Team • Additional reports for local/community use • Site Status page to quickly illustrate at what point in the reporting process the site is in
AHAR Exchange Reports • The reports option on AHAR Exchange allows you to access various reports on the data for your community. • Some reports can be used by communities for local purposes and cover a variety of topics. • Ability to generate report that compares data for multiple years.
Details about AHAR Exchange Reports (con’t. ) Primarily for use during AHAR Data Collection: • Notes Report: This report compiles all information entered in notes fields by community staff and AHAR data collection staff and compiles them into a single document. – Helpful for use during data review • Data Summary: This report will be generated by the Summary reporting category. – Data summary report provides an overview of your AHAR data and is used to finalize your data
AHAR Exchange Reports (con’t. ) • Extrapolated Counts: For jurisdictions with < 100% bed coverage, provides homeless counts that include estimates for providers not participating in HMIS. • Demographics Report: Provides the percentage of persons in each demographic category. • Prior Living Situation: Shows and categorizes the prior living situations of homeless people counted in the AHAR data. • Length of Stay: Breaks down the amount of time each person used shelter during the AHAR reporting period. • Long Term Stay: Presents demographic data on those who used ES for more than 180 days and compares to the entire homeless population.
AHAR Exchange: Local Reports • Automatically generated report that provides a description of sheltered homelessness in your community • Includes narrative introduction about the data • Report is formatted with color tables and charts that reflect the community’s AHAR data • Covers the reporting categories for which data was submitted to the 2008 AHAR, as well as 2007 AHAR data (if submitted)
The Sandbox Feature • A special feature of AHAR Exchange is the AHAR Exchange Sandbox • The Sandbox is a “dummy” AHAR site which was designed for public viewing and testing the AHAR data collection screens and for generating and testing upload files • To access the Sandbox site go to sandbox. hmis. info/ • Communities may use Sandbox year round to monitor AHAR data quality
AHAR Reporting Data Quality Three Key Data Quality Indicators: 1. Bed Utilization: The number of people served on a given night divided by the number of available beds the same night • HMIS participating agencies must be recording accurate entry and exit dates for all clients served during the reporting period • Important difference between bed and unit utilization rates discussed during the data collection process 2. Bed Coverage: The total number of beds in HMIS divided by the number of beds in the Co. C • Communities must have at least 50% HMIS bed coverage in 1 or more reporting category. 3. Data Completeness: A low rate of missing data across all questions • HMIS participating agencies must be collecting the HUD required Universal Data Elements
Bed Utilization Rates: Why are They Excessively High or Low? • Excessively High Utilization (typically above 105%) – Missing exit dates – Inaccurate, low bed counts – Inadequate de-duplication – Accounting for people who use overflow beds, but not the beds • Excessively Low Utilization (typically below 60%) – Not entering information into the HMIS on all clients served – Inaccurate, high bed counts – For family programs, not all beds in occupied unit may be filled
Bed Utilization Rates: Why are They Important? • Inaccurate bed utilization rates means your community may not know: – The number of days people are using shelters – The number of homeless people using shelters – The characteristics of sheltered homeless people served on a particular day or period of time – What types of providers need more capacity and what types have extra capacity • Monitor bed utilization rates in your community by using the Bed Utilization Tool – Located under “AHAR Tools” at ahar. hmis. info
Learn to Use the Bed Utilization Tool
Improving the Accuracy of Your Counts • Regularly review utilization rates by provider using Bed Utilization Tool. Ask providers to confirm unusual utilization rates. • Compare utilization rates across similar providers to identify possibly erroneous rates. • Compare the number of people served from HMIS to the number reported in the point-in-time count for the Co. C application (if from a different source).
More Suggestions for Improving the Accuracy of Your Counts • Match people listed in HMIS to bed logs if separate logs are kept • Automatically enter exit dates for overnight shelters • If long-term problem, exit everyone and have provider re-enter only those persons still being served • Design system so persons cannot be listed as staying at two residential providers at the same time • Provider regular training of front-line staff who enter the information
Other Strategies for Improving Data Quality • Self-monitoring reports – Open entry/exit report: List of all clients with no exit date – Total entry report: List of all clients that entered during a specific time frame – Data completion report: List of all clients entered with data element responses and flags for missing information
HMIS Self Assessment Process Tool • This tool helps Co. Cs to understand what types of challenges they may be experiencing with HMIS and identify the technical assistance resources that are available to address those challenges • It is typically a first step in obtaining technical assistance from HUD’s National HMIS Technical Assistance Team • Located at: http: //hmis. hudhre. info/etool • The interactive tool can be completed a single time or can be used on an ongoing basis
HMIS Self Assessment Process Tool (con’t. ) The purpose of the Self Assessment Process is to: 1. Highlight standard issues of importance for typical HMIS implementations 2. Identify specific issues or priority areas that may require attention 3. Direct communities to TA resources and materials that are available to address specific issues and barriers 4. Orient and prepare a community for an on-site TA visit, if appropriate
HMIS Self Assessment Process Tool (con’t. ) • Questions in the tool cover topics such as: – Organizational capacity and governance – Community/provider buy-in – Technological capacity – Project implementation and management plans – HMIS software and system design – Data sharing – Data quality and reporting – Funding and staffing
AHAR Mid-Year Data Check In • It is a good idea to review data mid-year (March/April) to check data quality • At this point, there may still be time to address or fix data quality problems that may affect AHAR participation • When performing this exercise, keep in mind any problems with data that surfaced during the previous year’s AHAR submission • Self-directed process, with possibility of support from the National HMIS Technical Assistance Team
Steps to Mid-Year Data Check In 1. Review bed coverage for all providers 2. Run point-in-time reports from HMIS to check bed utilization rates each month 3. Run a report from HMIS of all clients during the previous year that have a length of stay greater than 365 days – Consider whether these are legitimate length of stays or actually a problem with exit dates 4. Conduct a process check – Make sure there is an established process in place for collecting data, reviewing data, running reports, and providing feedback on the data
Resources – 2009 AHAR Schedule Activity Schedule 2009 AHAR Reporting Period Ends September 30, 2009 AHAR Exchange: Webinar and Conference Call Training September 14 – September 25, 2009 Submit Complete Draft of AHAR Data November 15, 2009 Ongoing Review of AHAR Data by Research Team Within 2 days of receipt Submit Complete and Final AHAR Data December 15, 2009 HUD Publishes 2009 AHAR Report June 2010
AHAR Resources (continued) • 2007 Annual Homeless Assessment Report – http: //www. hudhre. info/documents/3 rd. Homeless. Assessment. Rep ort. pdf • AHAR Data Quality: Tips and Strategies – http: //hmis. info/Resources/289/AHAR-Data-Quality-Training. aspx • AHAR Memo on Improving Missing Data Rates – http: //hmis. info/Resources/852/AHAR-Update-July-2007. aspx • HMIS Bed Utilization Tool – http: //www. hmis. info/Resources/1057/HMIS-Bed-Utilization-Tool 2008 -2009. aspx
AHAR Resources (continued) • Garbage In, Garbage Out: Strategies to Ensure Data Quality – http: //hmis. info/Resources/768/Garbage-In, -Garbage-Out. Strategies-to-Ensure-Data-Quality. aspx • Technical Guidelines for Unduplicating and De-Identifying HMIS Client Records – http: //hmis. info/Resources/305/Technical-Guidelines-for. Unduplicating-and-De-identifying-HMIS-Client. Records. aspx
Conclusion Questions or comments: • E-mail AHAR Team at: AHAR@abtassoc. com • Submit question through “Ask the Expert” on: www. hmis. info
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