Evidence map›Paper›PMID 41734612›Full record

ArticlePublic health2026

Disparities in testing for latent tuberculosis infection in a large US integrated healthcare system.

Jennifer H Ku, Parag Mahale, Lei Qian, Zhoxin Li, Heidi Fischer, Katia J Bruxvoort, Jacek Skarbinski, Bruno J Lewin, Sally F Shaw, Brigitte C Spence and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

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

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0citing papers in PubMed
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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

11 authors.

Jennifer H KuCenter for Integrated Health Care Research, Kaiser Permanente Hawaii, Honolulu, HI, USA. Electronic address: jen.h.ku@kp.org.
Parag MahaleDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Lei QianDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Zhoxin LiDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Heidi FischerDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Katia J BruxvoortDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Jacek SkarbinskiDivision of Research, Kaiser Permanente Northern California, Oakland, CA, USA; Department of Infectious Diseases, Oakland Medical Center, Kaiser Permanente Northern California, Oakland, CA, USA.
Bruno J LewinDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA; Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, USA.
Sally F ShawDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Brigitte C SpenceDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Sara Y TartofDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA; Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, USA.

Funding

A New Approach to an Old Problem: Redesigning Latent Tuberculosis Screening and TreatmentR01AI151072 · NIAID · KAISER FOUNDATION RESEARCH INSTITUTE · PI TARTOF, SARA · 2020 to 2024
$3.9M
Antimicrobial resistant E. coli before and after California Senate bill 27 (ARES): a natural experimentR01AI130066 · NIAID · KAISER FOUNDATION RESEARCH INSTITUTE · PI TARTOF, SARA · 2017 to 2021
$3.8M
NIAID NIH HHS R01 AI130066NIAID NIH HHS R01 AI151072
6 · The paper itself

Abstract

objectivesDisparities in latent tuberculosis infection (LTBI) testing by birth country and socioeconomic status (SES) are not well understood. We used electronic health records from Kaiser Permanente Southern California (2010-2019) to examine disparities in LTBI testing across SES among those born in high-vs. low-tuberculosis (TB) incidence countries. STUDY

designRetrospective cohort study.

methodsWe examined LTBI testing rates and measures of disparities (absolute/relative concentration index, between-group variance, and mean log deviation) across area-level SES and racial/ethnic groups, by birth in a high-vs. low-TB incidence country, with imputed data for missing birth country.

resultsWe included 1,740,428 individuals, with a median age of 37.0 years (interquartile range 27.0, 51.0), who were 50.3% female (n = 875,879), and 39.2% Hispanic (n = 682,870); 1,205,853 (69.3%) were born in a country with low TB incidence. Among adults born in low-TB incidence countries (n = 1,205,853; 315.3 tests/10,000 person-years), testing rates remained stable (annual percent change [APC] = -0.69% [95% CI: -1.55, 0.41]). Among adults born in high-TB incidence countries (n = 534,575; 246.7 tests/10,000 person-years), testing rates increased over time (APC = 1.90% [1.14, 2.90]) with a higher rate of increase for those with higher SES. Among individuals born in a high-TB incidence country, disparities by SES and racial/ethnic groups increased over time.

conclusionsDisparities in LTBI testing in individuals born in high-vs. low-TB incidence countries decreased overall, but increased disproportionally in those with higher SES among those born in high-TB incidence countries. Continued research is needed to understand the causes of disparities, and to inform interventions to reduce disparities.

Indexed as

Delivery of Health Care, IntegratedHealthcare DisparitiesLatent TuberculosisMass ScreeningAdultCaliforniaFemaleHumansIncidenceMaleMiddle AgedRetrospective StudiesSocioeconomic Disparities in HealthCountry of birthDisparitiesLatent tuberculosis infection testingSocioeconomic statusTuberculosis

Identifiers

PMID41734612
PMCPMC13455725

What OpenQuestion holds

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Registered trials

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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.