Evidence map›Paper›PMID 33770534›Full record

Observational studyThe Lancet. Infectious diseases2021

Measuring health-care delays among privately insured patients with tuberculosis in the USA: an observational cohort study.

Jessica El Halabi, Nathan Palmer, Michael McDuffie, Jonathan J Golub, Kathe Fox, Isaac Kohane, Maha R Farhat

Open access · greenAbstract readObservational Study
In one paragraph

Observational study in The Lancet. Infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.2field-weighted citation impact, top 18% of its field
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

20 citing papers in PubMed, 24 citations in OpenAlex.

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  20. Tuberculosis Pathways to Care and Transmission of Multidrug Resistance in India.American journal of respiratory and critical care medicine · 2022
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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

7 authors at 3 institutions in 1 country.

Jessica El HalabiDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Nathan PalmerDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Michael McDuffieDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Jonathan J GolubCenter for Tuberculosis Research, Johns Hopkins University, Baltimore, MD, USA.
Kathe FoxDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Isaac KohaneDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Maha R FarhatDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA. Electronic address: maha_farhat@hms.harvard.edu.
Harvard University · USJohns Hopkins University · USMassachusetts General Hospital · US

Funding

RESEARCH TRAINING-MEDICAL INFORMATICS 90T15LM007092 · NLM · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Nils Gehlenborg · 1992 to 2026
$32.8M
New Tools for the interpretation of Pathogen Genomic Data with a focus on Mycobacterium tuberculosisK01ES026835 · NIEHS · MASSACHUSETTS GENERAL HOSPITAL · PI FARHAT, MAHA · 2015 to 2019
$1.1M
NIEHS NIH HHS K01 ES026835NLM NIH HHS T15 LM007092
6 · The paper itself

Abstract

backgroundA high index of suspicion is needed to initiate appropriate testing for tuberculosis due to its protean symptoms, yet health-care providers in low-incidence settings are becoming less familiar with the disease as rates decline. We aimed to estimate delays in tuberculosis diagnosis and treatment at the US national level between 2008 and 2016.

methodsIn this retrospective observational cohort study, we repurposed private insurance claims data provided by Aetna (Connecticut, USA), to measure health-care delays in tuberculosis diagnosis in the USA in 2008-16. Active tuberculosis was determined by diagnosis codes and the filling of anti-tuberculosis treatment prescriptions. Health-care delays were defined as the duration between the first health-care visit for a tuberculosis symptom and the initiation of anti-tuberculosis treatment. We assessed if delays varied over time, and by patient and system variables, using multivariable regression. We estimated household tuberculosis transmission and respiratory complications after treatment initiation.

findingsWe confirmed 738 active tuberculosis cases (incidence 1·45 per 100 000 person-years) with a median health-care delay of 24 days (IQR 10-45). Multivariable regression analysis showed that longer delays were associated with older age (8·4% per 10 year increase [95% CI 4·0 to 13·1]; p<0·0086) and non-HIV immunosuppression (19·2% [15·1 to 60·0]; p=0·0432). Presenting with three or more symptoms was associated with a shorter delay (-22·5% [-39·1 to -2·0]; p=0·0415), relative to presenting with one symptom, as did use of chest imaging (-24·9% [-37·9 to -8·9]; p<0·0098), tuberculosis nucleic acid amplification tests (-19·2% [-32·7 to -3·1]; p=0·0241), and care by a tuberculosis specialist provider (-17·2% [-33·1 to -22·3]; p<0·0087). Longer delays were associated with an increased rate of respiratory complications even after controlling for patient characteristics, and an increased rate of secondary tuberculosis among dependents.

interpretationIn the USA, the median health-care delay for privately insured patients with tuberculosis exceeds WHO-recommended levels of 21 days (3 weeks). The results suggest the need for health-care provider education on best practices in tuberculosis diagnosis, including the use of molecular tests and the maintenance of a high index of suspicion for the disease.

fundingUS National Institutes of Health.

Indexed as

AdolescentAdultAntitubercular AgentsChildChild, PreschoolDelayed DiagnosisFemaleHumansIncidenceInsurance Claim ReviewMaleMiddle AgedMultivariate AnalysisPrivate SectorRegression AnalysisRetrospective StudiesAntitubercular Agents

Identifiers

PMID33770534
PMCPMC12687599
OpenAlexW3137342705

What OpenQuestion holds

Textmetadata
LicenceTDM
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.