Quarterly Data Quality

Minnesota’s QDQ has been redesigned.

Why is it important?

With high-quality data, a community can accurately tell the story of the individuals and families it serves. For the information in the system to be useful in measuring our progress or understanding our system, it must be accurate, complete, consistent, and timely.

Our system is big and complex, and it requires regular attention to ensure that the data in it meets our quality standards. Especially with the inclusion of Coordinated Entry in HMIS, good data helps agencies and programs make decisions that affect clients’ lives, so it’s more important now than ever.

What is the QDQ Process?

In recent years, ICA has focused on data quality in response to federally mandated efforts like System Performance Measures and the Longitudinal System Analysis (formerly known as the AHAR). These efforts look at data in the system in specific ways, and require ICA and users to respond to specific timelines.

While those efforts won’t go away, our new process has a more frequent examination of the HUD and MN Universal Data Elements, all of which are important in those efforts, as a way to reduce the effort spent looking at and attempting to correct data from years ago during crunched timelines.

In the Quarterly Data Quality (QDQ) monitoring process, four times per year, agencies will hear from their CoC coordinator.

This is the proposed quarterly data quality process flow. It demonstrates which parts of the process are owned by agencies, ICA, and state/CoC partners.

Agencies will run a special report that ‘scores’ their providers’ data quality based on the extent to which the HUD and MN universal data elements meet criteria for accuracy, completeness, consistency, and timeliness. Agencies will have time to correct issues and then re-run the report, with support from ICA in HMIS User Groups and via the HMIS MN Helpdesk during that time.

Agencies will then submit a form indicating they reviewed their report and documenting their scores. In return, agencies will receive charts that can help them track and celebrate their data quality progress. CoC leadership and state funding partners will be briefed on agencies’ participation and progress every quarter.

Here is the Scoring Rubric from which providers will be measured on quarterly data quality.

QDQ Timeline

Quarterly Data Quality timeline

QDQ Materials

QDQ Instructions for Users – A guide to help end users navigate the QDQ report, data corrections, and submission of provider scores to the QDQ Portal.

The QDQ Report Guide – A guide to orient users to the purpose, structure, and technical features of the QDQ report.

QDQ Data Portal Instructions – A step-by-step guide for submitting your agency’s QDQ provider scores into the QDQ Data Portal.

QDQ Data Portal – Where HMIS users will submit their agency’s provider scores every quarter.

MN HMIS Knowledge Base – The place to go for data corrections help with errors on your QDQ report.

QDQ Instruction Videos

Our QDQ video series includes four short videos that contain what you need to know about the Quarterly Data Quality process.

Who should watch these videos? Training is required for any HMIS users responsible for data corrections or submitting data quality scores via the portal.

Tips and Tricks for a Successful Submission

For some helpful tips on submitting through the QDQ Data Portal, check out this news post.

If you have any questions, please contact our ICA Helpdesk at mnhmis@icalliances.org.