Evidence map›Paper›PMID 42494652›Full record

ReviewLancet regional health. Americas2026

Data invisibility in United States national healthcare datasets: implications for immigrant health equity.

Tala Al-Rousan, Matthew Banegas, Ava Nariman, Cheryl A M Anderson

Abstract readReview
In one paragraph

Review in Lancet regional health. Americas, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Tala Al-RousanHerbert Wertheim School of Public Health and Human Longevity Science, University of California, La Jolla, San Diego, CA, USA.
Matthew BanegasHerbert Wertheim School of Public Health and Human Longevity Science, University of California, La Jolla, San Diego, CA, USA.
Ava NarimanHerbert Wertheim School of Public Health and Human Longevity Science, University of California, La Jolla, San Diego, CA, USA.
Cheryl A M AndersonHerbert Wertheim School of Public Health and Human Longevity Science, University of California, La Jolla, San Diego, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Data invisibilityHealth equityHealth surveillanceImmigrant healthImmigration policy

Identifiers

PMID42494652
PMCPMC13393586

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.