Evidence map›Paper›PMID 36346628›Full record

ArticleJAMA network open2022

Association of Patient and Site-of-Care Characteristics With Reproductive Carrier Screening Timing in a Large Integrated Health System.

Leland E Hull, David Cheng, Mie H Hallman, M L Rieu-Werden, Jennifer S Haas

Abstract 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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Multilevel barriers and facilitators to widespread use of preconception carrier screening in the United States.Genetics in medicine : official journal of the American College of Medical Genetics · 2023
    Article
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

5 authors.

Leland E HullDivision of General Internal Medicine, Massachusetts General Hospital, Boston.
David ChengHarvard Medical School, Boston, Massachusetts.
Mie H HallmanDivision of General Internal Medicine, Massachusetts General Hospital, Boston.
M L Rieu-WerdenDivision of General Internal Medicine, Massachusetts General Hospital, Boston.
Jennifer S HaasDivision of General Internal Medicine, Massachusetts General Hospital, Boston.

Funding

Elucidating the barriers and facilitators to widespread implementation of preconception genetic carrier screeningK08HG012221 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI HULL, LELAND · 2022 to 2025
$883k
NHGRI NIH HHS K08 HG012221
6 · The paper itself

Abstract

Importance: Reproductive genetic carrier screening can be performed prior to or during pregnancy to assess a reproductive couple's risk of having a child with a recessively inherited disorder. Although professional societies endorse preconception screening as preferable to prenatal screening to allow for greater reproductive choice, implementation of preconception screening is challenging. Objective: To determine how carrier screening timing varies by multilevel factors associated with health care delivery including patient, clinician, and location across a large integrated health care system. Design, Setting, and Participants: This cross-sectional study used a mixed-methods approach including (1) quantitative analysis of multilevel factors associated with the timing of reproductive carrier screening and (2) qualitative analyses of data from interviews conducted with clinicians ordering carrier screenings. The setting was the Mass General Brigham, a large integrated health care system in the greater Boston, Massachusetts area. Participants included adult female patients who completed reproductive carrier screening performed by Myriad Women's Health between October 1, 2018, to September 30, 2019. Exposures: Site of care (ordering clinical location and hospital affiliate), ordering clinician specialty, and patient characteristics, including age at date of test collection, self-reported race and ethnicity, primary insurance payor, and number of comorbidities. Main Outcomes and Measures: The primary outcome was the timing of carrier screening (preconception vs prenatal). A series of 4 multilevel logistic regression models were fitted to measure the relative contribution of site, clinician, and patient-level factors on the timing of screening. Interviews with ordering clinicians (N = 9) were analyzed using a framework approach to explore barriers to preconception screening. Results: Among 6509 adult female patients who completed carrier screenings, 770 (12%) were Asian, 352 (5%) were Hispanic, 640 (10%) were non-Hispanic Black, 3844 (59%) were non-Hispanic White, 858 (13%) were other or multiple races and ethnicities, and 2611 (40%) were aged 31 to 35 years; 4701 (63%) had prenatal screening and 2438 (37%) had preconception screening; screenings were ordered by 161 distinct clinicians across 32 clinical locations affiliated with 4 hospitals. In model 1, adjusted for hospital (fixed effect), clinic and clinician (random effects), 49% of the variability in timing was associated with clinician-level effects (intraclass correlation coefficient [ICC], 0.49) and 28% was associated with clinic-level effects (ICC, 0.28). Clinician specialty explained the greatest amount of variation in screening timing. Interviewed clinicians (N = 9) supported preconception screening but cited several barriers to offering population-based preconception screening. Conclusions and Relevance: In this cross-sectional study, multilevel factors were associated with carrier screening timing. These findings suggest that increasing access to preconception screening may involve engaging specific medical specialties.

Indexed as

Delivery of Health Care, IntegratedPrenatal DiagnosisAdultChildCross-Sectional StudiesEthnicityFemaleHumansPregnancyWomen's Health

Identifiers

PMID36346628
PMCPMC9644263

What OpenQuestion holds

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LicenceCC BY
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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.