Evidence map›Paper›PMID 29345997›Full record

ArticleAmerican journal of public health2018

Trends in Health Insurance and Type Among Military Veterans: United States, 2000-2016.

Carla E Zelaya, Colleen N Nugent

Abstract read
In one paragraph

Article in American journal of public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Preventive Care Delivery After the Veterans Choice Program.American journal of preventive medicine · 2021
    Article
  9. Article
  10. Article
  11. Article
  12. Article
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  14. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Carla E ZelayaBoth authors are with the Division of Health Interview Statistics, National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD.
Colleen N NugentBoth authors are with the Division of Health Interview Statistics, National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

objectivesTo describe long-term national trends in health insurance coverage among US veterans from 2000 to 2016 in the context of recent health care reform.

methodsWe used 2000 to 2016 National Health Interview Survey data on veterans aged 18 to 64 years to examine trends in insurance coverage and uninsurance by year, income, and state Medicaid expansion status. We also explored the current proportions of veterans with each type of insurance by age group.

resultsThe percentage of veterans with private insurance decreased from 70.8% in 2000 to 56.9% in 2011, whereas between 2000 and 2016 Department of Veterans Affairs (VA) health care coverage (only) almost tripled, Medicaid (without concurrent TRICARE or private coverage) doubled, and TRICARE coverage of any type tripled. After 2011, the percentage of veterans who were uninsured decreased. In 2016, low-income veterans in Medicaid expansion states had double the Medicaid coverage (41.1%) of low-income veterans in nonexpansion states (20.1%).

conclusionsOur estimates, which are nationally representative of noninstitutionalized veterans, show marked increases in military-related coverage through TRICARE and VA health care. In 2016, only 7.2% of veterans aged 18 to 64 years and 3.7% of all veterans (aged 18 years or older) remained uninsured.

Indexed as

AdultHealth Care ReformHealth SurveysHumansInsurance CoverageInsurance, HealthMedicaidMedically UninsuredMiddle AgedUnited StatesUnited States Department of Veterans AffairsVeterans

Identifiers

PMID29345997
PMCPMC5803799

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.