Data invisibility in United States national healthcare datasets: implications for immigrant health equity.
Where this comes from
- Record sourced from PubMed, PMID 42494652.
- Also identified by DOI 10.1016/j.lana.2026.101574 and PMC identifier 13393586.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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.