Advancing Health Equity With Tribal Perspectives On Data

Executive Summary

The National Indian Health Board (NIHB) held the Tribal Health Equity Data Symposium on Monday, September 25 and Tuesday, September 26 at American University in Washington, DC. Throughout the two days, we heard the following four themes detailed below. For each theme, NIHB provides several recommendations of actions the Centers for Medicare and Medicaid Services (CMS) can take to improve the situation.

The detailed report provides a summary of each presentation and session from the Symposium. Within the report, context and details are given as to how the recommendations may be successfully implemented. This executive summary provides a brief snapshot of the major themes and specific recommendations.

Honor Tribal Sovereignty and Reinforce Tribal Self Determination

Presenters and participants shared the importance of meaningful Tribal consultation when federal agencies are making any decisions regarding the collection and dissemination of Tribal data. To make progress on addressing all cross-cutting data issues for American Indians/Alaska Natives (AI/ANs), data collectors from any organization (local, state, federal, university) must recognize and respect Tribal data sovereignty. In addition, Tribal Advisory Committees, CMS Tribal Technical Advisory Group (TTAG), public listening sessions, and other methods of Tribal engagement all play a role in ensuring Tribal perspectives and Indigenous ways of knowing are included and listened to.

Recommendations
  • NIHB recommends CMS receive full Tribal review of the CMS Office of Minority Health (OMH) data white paper[1] before implementing actions.
  • CMS leadership, through robust training, must ensure that CMS staff understand what Tribal data sovereignty is, including how to uphold and honor data sovereignty to ensure Tribes take ownership of, access, and control their data.
  • CMS must make sure that ongoing Tribal consultation and the principles of data sovereignty guide all work that CMS undertakes involving data.

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