Evidence map›Paper›PMID 37241093›Full record

ReviewMedicina (Kaunas, Lithuania)2023

Race: How the Post-Genomic Era Has Unmasked a Misconception Promoted by Healthcare.

Donna Schaare, Ludovico Abenavoli, Luigi Boccuto

Abstract readReview
In one paragraph

Review in Medicina (Kaunas, Lithuania), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Donna SchaarePh.D. Program in Healthcare Genetics and Genomics, School of Nursing, College of Behavioral, Social and Health Sciences, Clemson University, Clemson, SC 29634, USA.ORCID 0000-0002-1132-3097
Ludovico AbenavoliDepartment of Health Sciences, University "Magna Graecia", 88100 Catanzaro, Italy.ORCID 0000-0002-5922-1524
Luigi BoccutoPh.D. Program in Healthcare Genetics and Genomics, School of Nursing, College of Behavioral, Social and Health Sciences, Clemson University, Clemson, SC 29634, USA.ORCID 0000-0003-2017-4270

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The term "race" has been employed to categorize human beings into distinct groups based on some perceived biological distinctions. This concept was debunked with the completion of the Human Genome Project and its revolutionary findings that all humans are >99% genetically identical, subsequently making the term "race" obsolete. Unfortunately, the previous misconception is being propagated by the continued use of the term to capture demographic information in healthcare in an attempt to improve equity. This paper seeks to review the history of the term "race", analyze the current policy, and discuss its limitations. It is important to note that our analysis was exclusively focused on the United States healthcare system and the Affordable Care Act; as such, it may not reflect other regions' policies, including those in Africa, Asia, and the Middle East. However, we feel that this policy analysis may serve as a model to recommend alterations that mirror the post-genomic era. The need for this policy change was recently highlighted in the 2022 ASHG presidential address, One Human Race: Billions of Genomes, and will reflect the knowledge gleaned by the scientific community through the conclusions of the Human Genome Project.

Indexed as

Delivery of Health CarePatient Protection and Affordable Care ActAfricaGenomicsHumansMiddle EastUnited Stateshealthcarehuman genome projectpolicypost-genomic erarace

Identifiers

PMID37241093
PMCPMC10223560

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.