Using Tribal Data Linkages to Improve the Quality of American Indian Cancer Data in Michigan

Misracialization of Indigenous people in population health and mortality studies: a scoping review to establish promising practices

Indigenous people are often misracialized as other racial or ethnic identities in population health research. This misclassification leads to underestimation of Indigenous-specific mortality and health metrics, and subsequently, inadequate resource allocation. In recognition of this problem, investigators around the world have devised analytic methods to address racial misclassification of Indigenous people. We carried out a scoping review based on searches in PubMed, Web of Science, and the Native Health Database for empirical studies published after 2000 that include Indigenous-specific estimates of health or mortality and that take analytic steps to rectify racial misclassification of Indigenous people. We then considered the weaknesses and strengths of implemented analytic approaches, with a focus on methods used in the US context. To do this, we extracted information from 97 articles and compared the analytic approaches used. The most common approach to address Indigenous misclassification is to use data linkage; other methods include geographic restriction to areas where misclassification is less common, exclusion of some subgroups, imputation, aggregation, and electronic health record abstraction. We identified 4 primary limitations of these approaches: (1) combining data sources that use inconsistent processes and/or sources of race and ethnicity information; (2) conflating race, ethnicity, and nationality; (3) applying insufficient algorithms to bridge, impute, or link race and ethnicity information; and (4) assuming the hyperlocality of Indigenous people. Although there is no perfect solution to the issue of Indigenous misclassification in population-based studies, a review of this literature provided information on promising practices to consider.

Challenges with misclassification of American Indian/Alaska Native race and Hispanic ethnicity on death records in North Carolina occupational fatalities surveillance

As frequently segregated and exploitative environments, workplaces are important sites in driving health and mortality disparities by race and ethnicity. Because many worksites are federally regulated, US workplaces also offer opportunities for effectively intervening to mitigate these disparities. Development of policies for worker safety and equity should be informed by evidence, including results from research studies that use death records and other sources of administrative data. North Carolina has a long history of Black/white disparities in work-related mortality and evidence of such disparities is emerging in Hispanic and American Indian/Alaska Native (AI/AN) worker populations. The size of Hispanic and AI/AN worker populations have increased in North Carolina over the last decade, and North Carolina has the largest AI/AN population in the eastern US. Previous research indicates that misidentification of Hispanic and AI/AN identities on death records can lead to underestimation of race/ethnicity-specific mortality rates. In this commentary, we describe problems and complexities involved in determining AI/AN and Hispanic identities from North Carolina death records. We provide specific examples of misidentification that are likely introducing bias to occupational mortality disparity documentation, and offer recommendations for improved data collection, analysis, and interpretation. Our primary recommendation is to build and maintain relationships with local community leadership, so that improvements in the ascertainment of race and ethnicity are grounded in the lived experience of workers from communities of color.

Urban American Indian and Alaska Native Data Sovereignty: Ethical Issues

This paper examines the ethical issues underlying research with urban American Indians and Alaska Natives (AI/ANs) through the lens of tribal sovereignty. There are 574 federally recognized tribes within the United States. Each of those tribes is recognized by the federal government as having sovereign status, an important political designation that ensures that decisions impacting tribal peoples must be made after consultation with those nations. Most AI/AN people live away from their designated tribal lands, yet their sovereign rights are frequently only recognized when living on tribal lands. These urban AI/ANs are still considered citizens of their sovereign nations, yet they lack the protections afforded to those who live on tribal lands, including protections surrounding research with their tribal communities. We explore the Belmont Report and related documents and demonstrate their inadequacy in considering the cultural and ethical concerns specific to protecting urban AI/ANs. We also provide several solutions to help guide future institutional policies regarding research with urban AI/ANs that honors Indigenous data sovereignty, including consultation, partnership with community advisory boards, employment of data use agreements, and ensuring informed consent.