Data Quality: A Proactive Approach

1. Data Quality: A Proactive Approach • Feb. 4, 2019 Joshua Gray HMIS Lead Team

2. Data Quality: A Proactive Approach “It is easier to build strong children, than to repair broken men” (Frederick Douglass, 1817-1895) ------------ “It is easier to enter good data, than to fix  bad data” (Jon Magee, 1984 - Present)

3. Overview • Data Quality before HMIS • Data Quality during Data Entry • Tips and Best Practices  

4. What is it? • Quality Data is 3 things • Accurate • Representative of reality • Complete • All Questions Answered • Timely • Near real time entry

5. Data Quality Before HMIS • First Impressions are important • Building trust • Realizing client is in current crisis • Remain calm • Use simple, easy to understand language (balance between compliance and client) • Be confident and comfortable asking questions • Be knowledgeable of all intake questions • Practice doing intakes on friends/family members

6. Data Quality Before HMIS • Privacy • Other people • Children • Use intake as reference to keep private • Paper Intake Forms • Verify all data is being captured • Good to keep on hand in case of system outages • Assure your services will not be refused by what answers are recorded • Be upfront with clients on what is shared/not shared (Barriers, case notes, DV) • Be willing to put off or pause an intake if better quality data can be captured later (as your agency/project allows)

7. Data Quality During Data Entry • Don't duplicate clients (makes it easier and quicker on you) • Search by SSN, Birthdate, and finally, Name, Partial Name • Use Legal Names (Might not be possible for SO) • Double check SSN and Birthdates w/ID if possible • Make Sure Head of Households is Correct • Read selection choices • Health Insurance, Barriers, Income

8. Don’t Create Duplicates

9. Data Quality During Data Entry • Living Situation Questions • Be willing to spend more time on this question, making it conversational • Use seasons, holidays to help clients estimate time periods • Use prior HMIS data to assist clients in remembering • Work backwards in time when needed • Write it out on paper if it helps

10. Universal Data Assessment

11. Data Quality During HMIS • Check for paused workflows • Be sure you're intake is capturing all required data (if not, project might be set-up incorrectly) • Data quality issues expected before engaged date on Street Outreach projects • Add additional data after building rapport • Enter HMIS data within 24 hours(if not in real time)

12. Tips and Tricks • Stay in the workflow • Current Enrollments • Sort by date • HUD Data quality report • Video of the Month • Entry assessment date and project start date must match

13. Accuracy • Compare Project Start Date and Move in Date • Rarely should they be the same • SSN • First 3 numbers 000, 666, or 999 • Middle 2 numbers cannot be 00 • Last four cannot be 0000 • Cannot be sequential • Client Location

14. Resources • HUD HMIS Data Standards and Data Dictionary • https://www.hudexchange.info/resource/3824/hmis-data-dictionary/ • HUD Reporting Glossary • https://www.hudexchange.info/resource/4489/hmis-standard-reporting-terminology-glossary/ • APR Data Quality • https://www.youtube.com/watch?v=zhA3nPiEHtI • Basic Data Editing • https://www.youtube.com/watch?v=td8uLmCB7Gs

15. QA