BACKGROUND: American Indian/Alaska Natives (AI/ANs) in the United States and the Bemidji Area (Michigan, Minnesota, Wisconsin, and Chicago) face numerous health, social, and economic disparities. In order to conduct planning activities and understand changes in health status over time, community-level data are needed. However, secondary sources of data are often not available or useful for AI/AN communities for reasons including small sample sizes or lack of relevant indicators. AI/AN communities require confidentiality regarding their community-level data because of past harms done by misuse of data; however, they would like to know how their community’s health status compares to that of similar communities.
METHODS: The Great Lakes Inter-Tribal Epidemiology Center (GLITEC) developed the Modular Survey for American Indian Communities (MoSAIC) health assessment framework to meet AI/AN communities’ competing needs for 1) flexibility and standardization, and 2) confidentiality and comparability. MoSIAC was designed with the goal of collecting data from enough communities over time to aggregate and share publically, with results for individual participating communities to be available in a timely manner only to the individual community.
RESULTS: A library of question modules was developed, with many modules based upon questions used in other surveys such as the Behavioral Risk Factor Surveillance System, the American Indian Adult Tobacco Survey, or the Pregnancy Risk Assessment Monitoring System. Although some modules have built in flexibility, the majority of modules must be used as-is. This provides adaptability to local contexts when necessary, while also ensuring that some degree of structure and consistency is maintained. Participating communities control the topics by selecting modules from the library by taking part in a guided process. GLITEC works with the communities to determine other aspects of the assessment, including defining the population of interest and selecting administration methods and promotion strategies. Data entry is completed via scanner technology, and basic analyses and standardized reports are generated, with options to explore data more deeply upon request. A preliminary version of MoSAIC was piloted with four communities and the framework is being evaluated.
CONCLUSIONS: MoSAIC is a potential solution to AI/AN communities’ desire for useful community health assessment data to meet their communities’ unique needs as well as to see how their community compares to the state, region, and nation.