Evidence map›Paper›PMID 38222332›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2023

HerediGene Population Study IT infrastructure: A model to support genomic research recruitment and precision public health.

David P Taylor, Bret S E Heale, Benjamin Chisum, G Bryce Christensen, Darin F Wilcox, Kevin M Banks, Jacob S Tripp, Teresa Liu, James B Ruesch, Travis J Sheffield and 9 more

Open access · greenAbstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 72% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. 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

19 authors at 2 institutions in 1 country.

David P TaylorIntermountain Health, Salt Lake City, UT.
Bret S E HealeHumanized Health Consulting, Salt Lake City, UT.
Benjamin ChisumIntermountain Health, Salt Lake City, UT.
G Bryce ChristensenIntermountain Health, Salt Lake City, UT.
Darin F WilcoxIntermountain Health, Salt Lake City, UT.
Kevin M BanksIntermountain Health, Salt Lake City, UT.
Jacob S TrippIntermountain Health, Salt Lake City, UT.
Teresa LiuIntermountain Health, Salt Lake City, UT.
James B RueschIntermountain Health, Salt Lake City, UT.
Travis J SheffieldIntermountain Health, Salt Lake City, UT.
Jesse W BreinholtIntermountain Health, Salt Lake City, UT.
J Clay HarwardIntermountain Health, Salt Lake City, UT.
Erin C HakodaIntermountain Health, Salt Lake City, UT.
Ted MayIntermountain Health, Salt Lake City, UT.
Joshua L BonkowskyDivision of Pediatric Neurology, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT.
Nephi A WaltonIntermountain Health, Salt Lake City, UT.
Howard L McLeodIntermountain Health, Salt Lake City, UT.
Lincoln D NadauldIntermountain Health, Salt Lake City, UT.
Pallavi Ranade-KharkarIntermountain Health, Salt Lake City, UT.
Intermountain Healthcare · USUniversity of Utah · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The HerediGene Population Study is a large research study focused on identifying new genetic biomarkers for disease prevention, diagnosis, prognosis, and development of new therapeutics. A substantial IT infrastructure evolved to reach enrollment targets and return results to participants. More than 170,000 participants have been enrolled in the study to date, with 5.87% of those whole genome sequenced and 0.46% of those genotyped harboring pathogenic variants. Among other purposes, this infrastructure supports: (1) identifying candidates from clinical criteria, (2) monitoring for qualifying clinical events (e.g., blood draw), (3) contacting candidates, (4) obtaining consent electronically, (5) initiating lab orders, (6) integrating consent and lab orders into clinical workflow, (7) de-identifying samples and clinical data, (8) shipping/transmitting samples and clinical data, (9) genotyping/sequencing samples, (10) and re-identifying and returning results for participants where applicable. This study may serve as a model for similar genomic research and precision public health initiatives.

Indexed as

GenomicsPublic HealthGenome, HumanGenotypeHumansResearch Design

Identifiers

PMID38222332
PMCPMC10785925
OpenAlexW4390889650

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.