HMIS Data Quality Monthly Audit

Monthly audit template for HMIS administrators to review completeness, accuracy, and timeliness of universal data elements and project-specific elements against HUD data quality benchmarks.

Audit Scope and Setup

• Agency / Organization Name
  Enter the full legal name of the agency whose HMIS data is being audited.
• Project(s) Under Review
  List all HMIS project names and project IDs included in this audit period.
• Audit Period (Month and Year)
  Select the first day of the month being audited.
• Project Type(s) Included
  Select all project types represented in this audit.
• HMIS Data Quality Report Pulled Prior to Audit
  Confirm that the current month's HMIS data quality report has been exported from the HMIS system before beginning this audit.
• Auditor Name and Role
  Enter the full name and title of the person conducting this audit (e.g., HMIS Administrator, Data Quality Manager).

Universal Data Elements (UDE) Completeness

• Name (3.01) — Missing/Unknown Rate
  Enter the percentage of client records with missing or 'Data Not Collected' for Name (Element 3.01). Acceptable: ≤5%.
• Social Security Number (3.02) — Missing/Unknown/Refused Rate
  Enter the percentage of records with SSN quality issues (missing, refused, or approximate). Acceptable: ≤20% for SSN due to population sensitivity; flag if >20%.
• Date of Birth (3.03) — Missing/Unknown Rate
  Enter the percentage of records with missing or approximate Date of Birth (Element 3.03). Acceptable: ≤5%.
• Race and Ethnicity (3.04) — Missing/Unknown Rate
  Enter the percentage of records with missing or 'Data Not Collected' for Race and Ethnicity (Element 3.04). Acceptable: ≤5%.
• Gender (3.06) — Missing/Unknown Rate
  Enter the percentage of records with missing or 'Data Not Collected' for Gender (Element 3.06). Acceptable: ≤5%.
• Veteran Status (3.07) — Missing/Unknown Rate
  Enter the percentage of adult records with missing or 'Data Not Collected' for Veteran Status (Element 3.07). Acceptable: ≤5%.
• Disabling Condition (3.08) — Missing/Unknown Rate
  Enter the percentage of records with missing or 'Data Not Collected' for Disabling Condition (Element 3.08). Acceptable: ≤5%.

Program Entry and Exit Data Timeliness

• Entries Recorded Within 3 Days of Program Entry — Compliance Rate
  Enter the percentage of enrollments entered into HMIS within 3 calendar days of the actual program entry date. Acceptable: ≥90%.
• Exits Recorded Within 3 Days of Program Exit — Compliance Rate
  Enter the percentage of exits entered into HMIS within 3 calendar days of the actual exit date. Acceptable: ≥90%.
• Number of Open Enrollments with No Exit (Stale Records) — Count
  Enter the count of enrollments open for more than 90 days with no recorded exit or service activity. Target: 0; flag any count >5 for immediate review.
• Destination at Exit (3.12) — Missing/Unknown Rate
  Enter the percentage of exit records with missing, unknown, or 'Data Not Collected' for Destination (Element 3.12). Acceptable: ≤5%.
• Reason for Leaving (3.12b) Populated for All Applicable Exits
  Confirm that Reason for Leaving is recorded for all applicable project types where required by HUD Data Standards.

Project-Specific and Program Data Elements

• Prior Living Situation (3.917) — Missing/Unknown Rate
  Enter the percentage of entry records with missing or 'Data Not Collected' for Prior Living Situation (Element 3.917). Acceptable: ≤5%.
• Income and Sources (4.02) at Entry — Missing/Unknown Rate
  Enter the percentage of applicable entry records missing Income and Sources data (Element 4.02). Acceptable: ≤5%.
• Income and Sources (4.02) at Annual Assessment / Exit — Missing Rate
  Enter the percentage of applicable annual assessment or exit records missing Income and Sources update (Element 4.02). Acceptable: ≤5%.
• Non-Cash Benefits (4.03) — Missing/Unknown Rate
  Enter the percentage of applicable records missing Non-Cash Benefits data (Element 4.03). Acceptable: ≤5%.
• Health Insurance (4.04) — Missing/Unknown Rate
  Enter the percentage of applicable records missing Health Insurance data (Element 4.04). Acceptable: ≤5%.
• Annual Assessments Completed Within Required Window
  Confirm that all clients enrolled for 12+ months have an annual assessment recorded within 30 days before or after their anniversary date, per HUD requirements.
• Chronic Homelessness Status Accurately Documented
  Confirm that Chronic Homelessness determination fields (Element 3.917 + disability + length of time) are complete and consistent for all PSH and applicable CoC-funded enrollments.

Data Accuracy and Logical Consistency

• Duplicate Client Records Identified — Count
  Enter the number of confirmed or probable duplicate client records identified in the HMIS system for this audit period. Target: 0.
• Overlapping Enrollment Errors (Same Client, Same Project Type, Same Period)
  Enter the count of clients with overlapping enrollments in the same project type during the audit period. These indicate data entry errors. Target: 0.
• Exit Date Before Entry Date — Error Count
  Enter the count of enrollment records where the recorded exit date precedes the entry date. This is a critical logical error. Target: 0.
• Head of Household Designation Present for All Households
  Confirm that every household enrollment has exactly one client designated as Head of Household. Missing or multiple HOH designations cause APR calculation errors.
• Age-Inconsistent Data Flags (e.g., Minor Recorded as Veteran)
  Confirm no records exist where a client's age is inconsistent with their recorded data (e.g., client under 18 flagged as Veteran, or DOB indicating age >120 years). Answer 'Yes' if no such errors exist.

Project Descriptor and Setup Data

• Project Type Correctly Configured in HMIS
  Confirm the project type (ES, TH, PSH, RRH, SO, etc.) is correctly set in the HMIS project setup and matches the grant agreement.
• Continuum of Care (CoC) Code Correctly Assigned
  Confirm the correct CoC code is assigned to each project in HMIS setup. Incorrect CoC codes cause misattribution in HUD reporting.
• Funding Sources Accurately Recorded in Project Setup
  Confirm all active funding sources (HUD CoC, ESG, SSVF, PATH, RHY, local, etc.) are accurately recorded in the HMIS project setup for the audit period.
• Bed and Unit Inventory (HIC) Data Current and Accurate
  Confirm that bed inventory, unit counts, and bed type designations in HMIS match the current Housing Inventory Count (HIC) submission for this project.

Corrective Actions and Follow-Up

• Overall Data Quality Assessment
  Select the overall data quality rating for this agency/project based on audit findings.
• Summary of Deficiencies Identified
  Provide a narrative summary of all data quality deficiencies identified during this audit, including element names, error counts, and affected projects.
• Corrective Action Plan Documented for All Critical Deficiencies
  Confirm that a written corrective action plan has been created for every critical deficiency identified in this audit, including responsible staff and target resolution date.
• Target Resolution Date for Open Deficiencies
  Select the target date by which all identified deficiencies will be resolved and re-verified.
• Agency Data Quality Contact Notified of Findings
  Confirm that the agency's designated HMIS data quality contact has been notified of audit findings and corrective action requirements.
• Supporting Documentation or Screenshots Attached
  Attach screenshots of HMIS data quality reports, error logs, or other supporting documentation for this audit.
• HMIS Administrator Signature
  HMIS Administrator signature certifying the accuracy of this audit.