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Run: HMIS Data Quality Monthly Audit

Monthly HMIS audit template for checking completeness, timeliness, and accuracy against HUD data quality benchmarks. Use it to catch missing fields, stale en...

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Audit Scope and Setup

Enter the full legal name of the agency whose HMIS data is being audited.
List all HMIS project names and project IDs included in this audit period.
Select the first day of the month being audited.
Select all project types represented in this audit.
Confirm that the current month's HMIS data quality report has been exported from the HMIS system before beginning this audit.
Enter the full name and title of the person conducting this audit (e.g., HMIS Administrator, Data Quality Manager).

Universal Data Elements (UDE) Completeness

Enter the percentage of client records with missing or 'Data Not Collected' for Name (Element 3.01). Acceptable: ≤5%.
Enter the percentage of records with SSN quality issues (missing, refused, or approximate). Acceptable: ≤20% for SSN due to population sensitivity; flag if >20%.
Enter the percentage of records with missing or approximate Date of Birth (Element 3.03). Acceptable: ≤5%.
Enter the percentage of records with missing or 'Data Not Collected' for Race and Ethnicity (Element 3.04). Acceptable: ≤5%.
Enter the percentage of records with missing or 'Data Not Collected' for Gender (Element 3.06). Acceptable: ≤5%.
Enter the percentage of adult records with missing or 'Data Not Collected' for Veteran Status (Element 3.07). Acceptable: ≤5%.
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

Enter the percentage of enrollments entered into HMIS within 3 calendar days of the actual program entry date. Acceptable: ≥90%.
Enter the percentage of exits entered into HMIS within 3 calendar days of the actual exit date. Acceptable: ≥90%.
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.
Enter the percentage of exit records with missing, unknown, or 'Data Not Collected' for Destination (Element 3.12). Acceptable: ≤5%.
Confirm that Reason for Leaving is recorded for all applicable project types where required by HUD Data Standards.

Project-Specific and Program Data Elements

Enter the percentage of entry records with missing or 'Data Not Collected' for Prior Living Situation (Element 3.917). Acceptable: ≤5%.
Enter the percentage of applicable entry records missing Income and Sources data (Element 4.02). Acceptable: ≤5%.
Enter the percentage of applicable annual assessment or exit records missing Income and Sources update (Element 4.02). Acceptable: ≤5%.
Enter the percentage of applicable records missing Non-Cash Benefits data (Element 4.03). Acceptable: ≤5%.
Enter the percentage of applicable records missing Health Insurance data (Element 4.04). Acceptable: ≤5%.
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.
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

Enter the number of confirmed or probable duplicate client records identified in the HMIS system for this audit period. Target: 0.
Enter the count of clients with overlapping enrollments in the same project type during the audit period. These indicate data entry errors. Target: 0.
Enter the count of enrollment records where the recorded exit date precedes the entry date. This is a critical logical error. Target: 0.
Confirm that every household enrollment has exactly one client designated as Head of Household. Missing or multiple HOH designations cause APR calculation errors.
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

Confirm the project type (ES, TH, PSH, RRH, SO, etc.) is correctly set in the HMIS project setup and matches the grant agreement.
Confirm the correct CoC code is assigned to each project in HMIS setup. Incorrect CoC codes cause misattribution in HUD reporting.
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.
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

Select the overall data quality rating for this agency/project based on audit findings.
Provide a narrative summary of all data quality deficiencies identified during this audit, including element names, error counts, and affected projects.
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.
Select the target date by which all identified deficiencies will be resolved and re-verified.
Confirm that the agency's designated HMIS data quality contact has been notified of audit findings and corrective action requirements.
Attach screenshots of HMIS data quality reports, error logs, or other supporting documentation for this audit.
HMIS Administrator signature certifying the accuracy of this audit.

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