We are currently reconstructing our DQ plan in light of the software transition. Be sure to read the monthly MN HMIS Newsletter for updates. In the meantime, check out the Ultimate HMIS Data Quality Guide Series.
What is Quarterly Data Quality (QDQ)?
QDQ is the data quality review process for agencies participating in Minnesota's HMIS.
Why is high-quality data important?
High-quality data helps a community truly understand and share the experiences of the people it supports. But for this information to actually help us track progress or evaluate our system, it needs to be accurate, complete, consistent, and up to date.
Because our system is large and complex, keeping data up to standard requires ongoing work. Clean data is critical, because programs rely on it to make decisions that directly impact clients' lives.
In the past, ICA focused heavily on data quality during mandatory federal reporting periods like System Performance Measures and the Longitudinal System Analysis (LSA). These reports examine data in specific ways and come with tight deadlines for both ICA and users.
Those federal requirements aren't changing, but we are shifting our approach. Going forward, we will review key HUD and Minnesota Universal Data Elements much more frequently. Checking data regularly will save everyone time and reduce the need for last-minute fixes on older records right before major deadlines.