How can researchers obtain ethnicity- or ancestry-specific mortality data from the Minnesota Department of Health?

1. Start with public dashboards and standard mortality files

MDH maintains interactive mortality dashboards and annual summary data tables that include mortality by race/ethnicity, crude and age‑adjusted death rates, and downloadable Excel files for calendar years (with standard files available from 2011 onward), so researchers should first search the Vital Statistics Interactive Query and the Mortality data table for the needed cross‑tabs before filing a request ^{[7] [1] [2]}.

2. Contact the Minnesota Center for Health Statistics for targeted analyses

When published tables do not provide the specific ethnicity or ancestry cross‑tabulation required, the Center for Health Statistics handles special requests and custom data — the site explicitly directs requests to healthstats@state.mn.us for health outcome data by social determinants (including race/ethnicity) at state, county or other geographic levels ^{[6] [8]}.

3. Use the Public Health Data Access portal for custom requests but expect prioritization

The Minnesota Public Health Data Access portal accepts specialized analyses and custom data requests; the portal notes that custom requests are answered in order and that MDH gives priority to internal users, the legislature and certain agencies, so outside researchers may face slower turnaround or triage of complex requests ^[3].

4. File a formal data practices request if necessary

If a researcher needs to make a formal demand under state law, the MDH Guide for Requesting Public Data explains that a written data practices request under the Minnesota Government Data Practices Act triggers a formal response obligation from MDH, and instructions for delivery (mail/address) are provided on the MDH data practices page ^[9].

5. Know what’s public and what limitations exist in categories

All Minnesota death records are public and noncertified informational death records can be obtained, but the statistical categories used by MDH may be limited to the fixed race/ethnicity response options in their systems — for example, a published analysis using MDH death records relied on fixed-response categories (Hispanic/non-Hispanic, and major racial groups) which may not capture detailed ancestry labels without custom coding or linkage ^{[10] [11]}.

6. Request specifications and methodological options (age adjustment, geography, timeframe)

When requesting data specify the exact variables needed (race, ethnicity, ancestry, age, cause of death), desired geography (state, county, zip), timeframe, and whether crude or age‑adjusted rates are required; MDH calculates rates using confirmed deaths by reported race/ethnicity and offers age-adjusted options to enable fair group comparisons — include requests for denominators or population estimates to compute rates ^{[12] [1] [5]}.

7. Anticipate review, cost, privacy and analytic constraints

Custom outputs and cross‑tabs may require suppression for small cell sizes, statistical review, resource time, and possibly fees or conditions; the county health tables transition and staffing limitations underscore that not all historic or highly disaggregated tables will be recreated without negotiation and justification ^{[4] [3]}.

8. Partnerships and data sharing examples

Academic and public‑health researchers have obtained MDH mortality data through partnerships (for example, a study that used Minnesota death records via a partnership with MDH), illustrating that formal collaborations or IRB arrangements can be an effective route to access deidentified individual‑level mortality data for research ^[11].