Data quality for and about American Indian/Alaska Native (AI/AN) people is undermined by deeply entrenched, colonial practices that have become standard in US federal data systems. This article draws on cases of maternal mortality and COVID-19 to demonstrate the ethical and clinical need for inclusive, diverse, and accurate data when researching AI/AN health trends. This article further argues that epidemiologists specifically must challenge implicit bias, question methods and practices, and recognize colonial, racist reporting practices about AI/AN people that have long undermined data collection, analytical, and dissemination practices that are fundamental to epidemiological research.
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Data quality for and about American Indian/Alaska Native (AI/AN) people is undermined by deeply entrenched, colonial practices that have become standard in US federal data systems. This article draws on cases of maternal mortality and COVID-19 to demonstrate the ethical and clinical need for inclusive, diverse, and accurate data when researching AI/AN health trends. This article further argues that epidemiologists specifically must challenge implicit bias, question methods and practices, and recognize colonial, racist reporting practices about AI/AN people that have long undermined data collection, analytical, and dissemination practices that are fundamental to epidemiological research.
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