METHODS: State vital records data was prepared for tribal use by collecting tribal affiliation data and using geospatial analysis to geographically define these communities. We used the American Indian/ Alaskan Native/ Native Hawaiian Area and American Indian Tribal Subdivision boundary shapefiles provided by the United States Census to define tribal events using a geographic definition. By using these boundaries, US Census population estimates, and self-reported tribal affiliation, we are able to calculate tribe specific health statistics using vital records data. These data are in turn used by these communities for community health assessment and health promotion activities.
RESULTS: Through the resource of a full time dedicated Tribal Epidemiologist at the New Mexico Department of Health (NMDOH), these data have been shared with 13 tribal communities within the state of New Mexico since 2013. These data can currently be accessed through a secure portal on the NMDOH Indicator Based Information System, which is the NMDOH open data web application. Through the NMDOH Tribal Epidemiologist, these data and other health department data are routinely used for community health assessments, grant applications, and to inform health policy within NM tribal communities.
CONCLUSIONS: Local control of health data is critical for the advancement of American Indian and Alaskan Native health. Elimination of health disparities in AIAN communities cannot be accomplished by the State Health department alone. In order to prioritize health issues, geospatial analysis and the collection of tribal affiliation on state datasets are needed for accurate tribe specific epidemiological surveillance at the state health department level. Additionally, it is beneficial to have staff whose primary focus is to serve the data sharing and data analysis needs of these communities. Through these types of mechanisms, health departments in states with large AIAN populations can foster government to government relations by working with tribes to improve and share of data.