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Data invisibility in United States national healthcare datasets: implications for immigrant health equity
Tala Al-Rousan1, Matthew Banegas1,2, Ava Nariman1
1Herbert Wertheim School of Public Health and Human Longevity Science, University of California, La Jolla, San Diego, CA, USA.
Abstract:
Immigrants represent more than 47 million people in the United States yet remain systematically invisible in the national datasets that inform health policy. Data invisibility operates across three dimensions: the structural absence of immigration related variables from most major national datasets; the substitution of imprecise proxy indicators that introduce misclassification bias; and the deliberate withdrawal of immigrant populations from data systems in response to enforcement risk. While some federal health surveys collect basic nativity data, these measures do not capture the full complexity of immigration history; recent federal arrangements permitting the use of health and tax data for immigration enforcement have compounded both the practical and ethical barriers to expanded data collection. International examples from Denmark, Sweden, and Canada demonstrate that comprehensive, ethically governed migration data collection is operationally feasible. We argue that expanded data collection may be epidemiologically necessary but remains ethically contingent upon legal protections, community governance, and restoration of trust.
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