Evidence map›Paper›PMID 32242312›Full record

ArticleJournal of general internal medicine2020

Comparing VA and Community-Based Care: Trends in Sleep Studies Following the Veterans Choice Act.

Frances M Weaver, Alex Hickok, Bharati Prasad, Elizabeth Tarlov, Qiuying Zhang, Amanda Taylor, Brian Bartle, Howard Gordon, Rebecca Young, Kathleen Sarmiento and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in Journal of general internal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

  1. Mortality in US veterans with insomnia, sleep apnea, and comorbid insomnia and sleep apnea (COMISA); an exploratory, hypothesis-generating cohort study.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2026
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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

11 authors at 5 institutions in 1 country.

Frances M WeaverCenter of Innovation for Complex Chronic Health Care (CINCCH), Hines VA Hospital, Hines, IL, USA. Frances.Weaver@va.gov.
Alex HickokCenter to Improve Veteran Involvement in Care, Portland VA Healthcare System, Portland, OR, USA.
Bharati PrasadJesse Brown Veterans Affairs Medical Center, Chicago, IL, USA.
Elizabeth TarlovCenter of Innovation for Complex Chronic Health Care (CINCCH), Hines VA Hospital, Hines, IL, USA.
Qiuying ZhangVA Information Resource Center, Department of Veterans Affairs, Hines VA Hospital, Hines, IL, USA.
Amanda TaylorVA Information Resource Center, Department of Veterans Affairs, Hines VA Hospital, Hines, IL, USA.
Brian BartleCenter of Innovation for Complex Chronic Health Care (CINCCH), Hines VA Hospital, Hines, IL, USA.
Howard GordonCenter of Innovation for Complex Chronic Health Care (CINCCH), Hines VA Hospital, Hines, IL, USA.
Rebecca YoungCenter to Improve Veteran Involvement in Care, Portland VA Healthcare System, Portland, OR, USA.
Kathleen SarmientoDepartment of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Denise M HynesCenter to Improve Veteran Involvement in Care, Portland VA Healthcare System, Portland, OR, USA.
Edward Hines, Jr. VA Hospital · USUniversity of Illinois Chicago · USPortland VA Medical Center · USSan Francisco VA Health Care System · USVA Portland Health Care System · US

Funding

HSRD VA I01 HX002655HSRD VA IK6 HX003395VA SDR 17-255 and SDR 18-321
6 · The paper itself

Abstract

backgroundTo address concerns about access to care, the Veterans Access, Choice, and Accountability Act of 2014 was enacted to make care available in the community when Veterans Health Administration (VA) care was unavailable or not timely. This paper examined VA referrals for diagnostic sleep studies from federal fiscal year (FY) 2015-2018.

designSleep studies completed between FY2015 and 2018 for Veterans tested within VA facilities (VAF) or referred to VA community care (VACC) providers were identified using VA administrative data files. Sleep studies were divided into laboratory and home studies. KEY

resultsThe number of sleep studies conducted increased over time; the proportion of home studies increased in VAF (32 to 47%). Veterans were more likely to be referred for a sleep study to VACC if they lived in a rural or highly rural area (ORs = 1.47 and 1.55, respectively), and had public or public and private insurance (ORs = 2.01 and 1.35), and were less likely to be referred to VACC if they were age 65+ (OR = 0.72) and were in the highest utilization risk based on Nosos score (OR = 0.78). Regression analysis of sleep study type revealed that lab studies were much more likely for VACC referrals (OR = 3.16), for persons living in rural areas (OR = 1.21), with higher comorbidity scores (OR = 1.28) and for ages 44-54, 55 to 64, and 65+ (ORs = 1.12, 1.28, 1.45, respectively) compared to younger Veterans. Veterans with some or full VA copayments (ORs = 0.91 and 0.86, respectively), and overweight Veterans (OR = 0.94) were less likely to have lab studies.

conclusionsThe number of sleep studies performed on Veterans increased from 2015 to 2018. Access to sleep studies improved through a combination of providing care through the Veteran Choice Program, predominantly used by rural Veterans, and increased use of home sleep studies by VA.

Indexed as

VeteransAdultAgedHealth Services AccessibilityHumansMiddle AgedReferral and ConsultationRural PopulationSleepUnited StatesUnited States Department of Veterans Affairsaccesscommunity caresleep studiesVA Choice ActVeterans

Identifiers

PMID32242312
PMCPMC7459009
OpenAlexW3014831981

What OpenQuestion holds

Textmetadata
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.