Evidence map›Paper›PMID 35404460›Full record

ArticleJAMA network open2022

Demographic Differences Among US Department of Veterans Affairs Patients Referred for Genetic Consultation to a Centralized VA Telehealth Program, VA Medical Centers, or the Community.

Maren T Scheuner, Alexis K Huynh, Catherine Chanfreau-Coffinier, Barbara Lerner, Alicia R Gable, Martin Lee, Alissa Simon, Randall Coeshott, Alison B Hamilton, Olga V Patterson and 2 more

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 3 pooled it
1.5field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 3 syntheses or guidelines pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. A Model for Clinician and Staff Education in the Engagement of American Indians in Genomic Research.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026
    Article
  5. Article
  6. Observational
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

12 authors at 5 institutions in 1 country.

Maren T ScheunerSan Francisco Veterans Affairs Health Care System, San Francisco, California.
Alexis K HuynhCenter for the Study of Healthcare Innovation, Implementation, and Policy, Veterans Affairs Greater Los Angeles Health Care System, Los Angeles, California.
Catherine Chanfreau-CoffinierVeterans Affairs Informatics and Computing Infrastructure, Salt Lake City, Utah.
Barbara LernerVeterans Affairs Boston Health Care System, Boston, Massachusetts.
Alicia R GableCenter for the Study of Healthcare Innovation, Implementation, and Policy, Veterans Affairs Greater Los Angeles Health Care System, Los Angeles, California.
Martin LeeCenter for the Study of Healthcare Innovation, Implementation, and Policy, Veterans Affairs Greater Los Angeles Health Care System, Los Angeles, California.
Alissa SimonCenter for the Study of Healthcare Innovation, Implementation, and Policy, Veterans Affairs Greater Los Angeles Health Care System, Los Angeles, California.
Randall CoeshottSan Francisco Veterans Affairs Health Care System, San Francisco, California.
Alison B HamiltonCenter for the Study of Healthcare Innovation, Implementation, and Policy, Veterans Affairs Greater Los Angeles Health Care System, Los Angeles, California.
Olga V PattersonVeterans Affairs Informatics and Computing Infrastructure, Salt Lake City, Utah.
Scott DuVallVeterans Affairs Informatics and Computing Infrastructure, Salt Lake City, Utah.
Marcia M RussellCenter for the Study of Healthcare Innovation, Implementation, and Policy, Veterans Affairs Greater Los Angeles Health Care System, Los Angeles, California.
Center for the Study of Healthcare Provider Behavior · USSan Francisco VA Health Care System · USUniversity of Utah · USVA Boston Healthcare System · USVA Salt Lake City Healthcare System · US

Funding

Precision Medicine Care Coordination in the Veterans Health AdministrationI01HX002278 · VA · VETERANS AFFAIRS MED CTR SAN FRANCISCO · PI RUSSELL, MARCIA MCGORY, SCHEUNER, MAREN THERESA · 2018 to 2021
–
HSRD VA I01 HX002278
6 · The paper itself

Abstract

Importance: Telehealth enables access to genetics clinicians, but impact on care coordination is unknown. Objective: To assess care coordination and equity of genetic care delivered by centralized telehealth and traditional genetic care models. Design, Setting, and Participants: This cross-sectional study included patients referred for genetic consultation from 2010 to 2017 with 2 years of follow-up in the US Department of Veterans Affairs (VA) health care system. Patients were excluded if they were referred for research, cytogenetic, or infectious disease testing, or if their care model could not be determined. Exposures: Genetic care models, which included VA-telehealth (ie, a centralized team of genetic counselors serving VA facilities nationwide), VA-traditional (ie, a regional service by clinical geneticists and genetic counselors), and non-VA care (ie, community care purchased by the VA). Main Outcomes and Measures: Multivariate regression models were used to assess associations between patient and consultation characteristics and the type of genetic care model referral; consultation completion; and having 0, 1, or 2 or more cancer surveillance (eg, colonoscopy) and risk-reducing procedures (eg, bilateral mastectomy) within 2 years following referral. Results: In this study, 24 778 patients with genetics referrals were identified, including 12 671 women (51.1%), 13 193 patients aged 50 years or older (53.2%), 15 639 White patients (63.1%), and 15 438 patients with cancer-related referrals (62.3%). The VA-telehealth model received 14 580 of the 24 778 consultations (58.8%). Asian patients, American Indian or Alaskan Native patients, and Hawaiian or Pacific Islander patients were less likely to be referred to VA-telehealth than White patients (OR, 0.54; 95% CI, 0.35-0.84) compared with the VA-traditional model. Completing consultations was less likely with non-VA care than the VA-traditional model (OR, 0.45; 95% CI, 0.35-0.57); there were no differences in completing consultations between the VA models. Black patients were less likely to complete consultations than White patients (OR, 0.84; 95% CI, 0.76-0.93), but only if referred to the VA-telehealth model. Patients were more likely to have multiple cancer preventive procedures if they completed their consultations (OR, 1.55; 95% CI, 1.40-1.72) but only if their consultations were completed with the VA-traditional model. Conclusions and Relevance: In this cross-sectional study, the VA-telehealth model was associated with improved access to genetics clinicians but also with exacerbated health care disparities and hindered care coordination. Addressing structural barriers and the needs and preferences of vulnerable subpopulations may complement the centralized telehealth approach, improve care coordination, and help mitigate health care disparities.

Indexed as

Breast NeoplasmsTelemedicineVeteransCross-Sectional StudiesDemographyFemaleHealthcare DisparitiesHumansMastectomyReferral and ConsultationRetrospective StudiesUnited StatesUnited States Department of Veterans Affairs

Identifiers

PMID35404460
PMCPMC9002339
OpenAlexW4223463413

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.