1. Data Quality Tools & Best Practices Matthew D. Simmonds, Simtech Solutions Inc.

2. The Different Levels of Data Cleansing Continuum 2 Org 2Org 1Org 3Org 4Org 5Org 6 Continuum 3Continuum 1 Program 1Program 2Program 3

3. State Level Data Quality Techniques Periodically run reports to compare counts to housing inventory. Periodically run reports to compare counts to housing inventory. Annually run reports to compare counts to point in time figures. Annually run reports to compare counts to point in time figures. Increase the focus on data quality and provide tools and training to assist agencies improve this quality. Increase the focus on data quality and provide tools and training to assist agencies improve this quality. Increase reporting requirements via data feeds and reduce the reliance on paper. Increase reporting requirements via data feeds and reduce the reliance on paper. Check data completion stats regularly and create performance benchmarks by program type. Check data completion stats regularly and create performance benchmarks by program type. Tie HMIS to billing. Tie HMIS to billing.

4. Sample M-5 Data Completion Stats Report

5. Capacity Analysis (HMIS Vs. Housing Inv)

6. Auditing and Cleansing at the CoC Level Create a subcommittee to address data quality within the CoC and dedicate time at CoC meetings to share updates. Create a subcommittee to address data quality within the CoC and dedicate time at CoC meetings to share updates. Implement interim reporting “dry runs” and use HMIS to track program performance. Implement interim reporting “dry runs” and use HMIS to track program performance. Develop customizable CoC wide common intake documents that match your HMIS software as well as your local reporting needs. Develop customizable CoC wide common intake documents that match your HMIS software as well as your local reporting needs. Introduce peer-to-peer training and assistance. Introduce peer-to-peer training and assistance. Consider HMIS implementation status when ranking projects. Consider HMIS implementation status when ranking projects. Self-audit by comparing 1 day APR reports against PIT count. Self-audit by comparing 1 day APR reports against PIT count.

7. Sample HMIS vs. Point in Time Analysis

8. Data Quality at the Agency Level Data Quality at the Agency Level Dedicate at least 1 staff person to the task of ensuring the data is being collected in a timely and accurate fashion. Dedicate at least 1 staff person to the task of ensuring the data is being collected in a timely and accurate fashion. Implement interim reporting “dry runs”. Implement interim reporting “dry runs”. Use HMIS as a management tool. Use HMIS as a management tool. Customize your CoC-wide common intake documents to match your agency’s unique needs. Customize your CoC-wide common intake documents to match your agency’s unique needs. Introduce peer-to-peer training and assistance. Introduce peer-to-peer training and assistance. Run a client served report on a daily basis and compare it to the counts from the bed register. Run a client served report on a daily basis and compare it to the counts from the bed register.

9. Data Quality at the Agency Level Data Quality at the Agency Level Check for invalid data conditions: Long Term Disability = No and any disabilities = Yes Note: mental health and substance abuse as duration should be long term. Long Term Disability = No and any disabilities = Yes Note: mental health and substance abuse as duration should be long term. Long Term Disabilty = No and Collecting SSDI = Yes. Long Term Disabilty = No and Collecting SSDI = Yes. Client = Inactive, any other data = Active. Client = Inactive, any other data = Active. Social Security # is not null and SSN Data Quality Code = blanks. Social Security # is not null and SSN Data Quality Code = blanks. Pregnancy = Yes and Gender = Male. Pregnancy = Yes and Gender = Male. Chronically Homeless = Yes and all disabilities = No. Chronically Homeless = Yes and all disabilities = No. Household ID not null and program type = individual shelter. Household ID not null and program type = individual shelter. SSN or Zip Code Data Quality code does not match value in SSN or zip code field. SSN or Zip Code Data Quality code does not match value in SSN or zip code field.

10. Ensuring an Accurate Chronic Count If the client has a disability (F=Yes), and they either had 4 or more homeless episodes (G>=4) OR were homeless for greater than 1 year (J>365), and are 18 years old or older (K>=18), then count them as chronically homeless. If the client has a disability (F=Yes), and they either had 4 or more homeless episodes (G>=4) OR were homeless for greater than 1 year (J>365), and are 18 years old or older (K>=18), then count them as chronically homeless.

11. Use ID Cards or Name Tags to Reduce Duplicates

12. Use an Offline Bed Register