Evidence map›Paper›PMID 30815139›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2018

An Applied Framework in Support of Shared Decision Making about

Thomas B Silverman, Gilad J Kuperman, Alejandro Vanegas, Margaret Sin, Jill Dimond, Katherine D Crew, Rita Kukafka

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
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.

Thomas B SilvermanDepartment of Biomedical Informatics, Columbia University, New York, NY.
Gilad J KupermanDepartment of Biomedical Informatics, Columbia University, New York, NY.
Alejandro VanegasDepartment of Biomedical Informatics, Columbia University, New York, NY.
Margaret SinDepartment of Biomedical Informatics, Columbia University, New York, NY.
Jill DimondSassafras Tech Collective, Ann Arbor, MI.
Katherine D CrewDepartment of Medicine, Columbia University, New York, NY.
Rita KukafkaDepartment of Biomedical Informatics, Columbia University, New York, NY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The United States Preventive Services Taskforce recommends that primary care providers screen patients for an increased risk of carrying a BRCA1 or BRCA2 mutation and refer those who meet family history criteria to genetic counseling. Such screening requires detailed and accurate family history data, which often goes uncollected during a primary care visit due to time constraints, competing priorities, and lack of awareness on behalf of both patients and providers. In order to address these barriers and promote appropriate genetic counseling referral, we developed a user-centered framework that collects and communicates relevant data in order to prepare patients and their primary care providers for an informed discussion on genetic counseling referral. This paper describes this framework and the underlining data schema that makes it possible.

Indexed as

Decision MakingDecision Support TechniquesGenes, BRCA1Genes, BRCA2Genetic CounselingGenetic TestingMutationAdultFemaleHereditary Breast and Ovarian Cancer SyndromeHumansPreventive Health ServicesReferral and ConsultationRisk AssessmentUnited States

Identifiers

PMID30815139
PMCPMC6371283

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.