Evidence map›Paper›PMID 37782875›Full record

ArticleHealth affairs (Project Hope)2023

Promoting Equity In Clinical Decision Making: Dismantling Race-Based Medicine.

Tina Hernandez-Boussard, Shazia Mehmood Siddique, Arlene S Bierman, Maia Hightower, Helen Burstin

Abstract read
In one paragraph

Article in Health affairs (Project Hope), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Genes, culture, and scientific racism.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  13. 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.

Tina Hernandez-BoussardTina Hernandez-Boussard (boussard@stanford.edu), Stanford University, Stanford, California.
Shazia Mehmood SiddiqueShazia Mehmood Siddique, University of Pennsylvania, Philadelphia, Pennsylvania.
Arlene S BiermanArlene S. Bierman, Agency for Healthcare Research and Quality, Rockville, Maryland.
Maia HightowerMaia Hightower, University of Chicago, Chicago, Illinois.
Helen BurstinHelen Burstin, Council of Medical Specialty Societies, Washington, D.C.

Funding

Advancing Knowledge Discovery for Postoperative Pain ManagementR01LM013362 · NLM · STANFORD UNIVERSITY · PI HERNANDEZ-BOUSSARD, TINA · 2019 to 2023
$3.2M
NLM NIH HHS R01 LM013362
6 · The paper itself

Abstract

As the use of artificial intelligence has spread rapidly throughout the US health care system, concerns have been raised about racial and ethnic biases built into the algorithms that often guide clinical decision making. Race-based medicine, which relies on algorithms that use race as a proxy for biological differences, has led to treatment patterns that are inappropriate, unjust, and harmful to minoritized racial and ethnic groups. These patterns have contributed to persistent disparities in health and health care. To reduce these disparities, we recommend a race-aware approach to clinical decision support that considers social and environmental factors such as structural racism and social determinants of health. Recent policy changes in medical specialty societies and innovations in algorithm development represent progress on the path to dismantling race-based medicine. Success will require continued commitment and sustained efforts among stakeholders in the health care, research, and technology sectors. Increasing the diversity of clinical trial populations, broadening the focus of precision medicine, improving education about the complex factors shaping health outcomes, and developing new guidelines and policies to enable culturally responsive care are important next steps.

Indexed as

Health EquityRacismArtificial IntelligenceClinical Decision-MakingDelivery of Health CareEthnicityHumans

Identifiers

PMID37782875
PMCPMC10849087

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.