Evidence map›Paper›PMID 36869772›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2023

Racism and Electronic Health Records (EHRs): Perspectives for research and practice.

Srinivas Emani, Jorge A Rodriguez, David W Bates

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Srinivas EmaniDivision of General Internal Medicine and Primary Care, Department of Medicine, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0002-6217-5792
Jorge A RodriguezDivision of General Internal Medicine and Primary Care, Department of Medicine, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
David W BatesDivision of General Internal Medicine and Primary Care, Department of Medicine, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Informatics researchers and practitioners have started exploring racism related to the implementation and use of electronic health records (EHRs). While this work has begun to expose structural racism which is a fundamental driver of racial and ethnic disparities, there is a lack of inclusion of concepts of racism in this work. This perspective provides a classification of racism at 3 levels-individual, organizational, and structural-and offers recommendations for future research, practice, and policy. Our recommendations include the need to capture and use structural measures of social determinants of health to address structural racism, intersectionality as a theoretical framework for research, structural competency training, research on the role of prejudice and stereotyping in stigmatizing documentation in EHRs, and actions to increase the diversity of private sector informatics workforce and participation of minority scholars in specialty groups. Informaticians have an ethical and moral obligation to address racism, and private and public sector organizations have a transformative role in addressing equity and racism associated with EHR implementation and use.

Indexed as

RacismElectronic Health RecordsHumansMinority GroupsRacial GroupsStereotypingequityintersectionalityorganizationsstructural racismtraining

Identifiers

PMID36869772
PMCPMC10114075

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.