ArticleHealth (London, England : 1997)2023
Racial biases in healthcare: Examining the contributions of Point of Care tools and unintended practitioner bias to patient treatment and diagnosis.
Article in Health (London, England : 1997), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Academic librarian support for patient-centred and inclusive medical education curricula: a case report.Journal of the Medical Library Association : JMLA · 2025Article
- Digitalised primary care in the UK: a qualitative study of the experiences of minoritised ethnic communities.The British journal of general practice : the journal of the Royal College of General Practitioners · 2024Article
- Inherent Bias in Electronic Health Records: A Scoping Review of Sources of Bias.medRxiv : the preprint server for health sciences · 2024Article
- Health Equity in Clinical Research Informatics.Yearbook of medical informatics · 2023Review
- Race-based medicine in the point-of-care clinical resource UpToDate: A systematic content analysis.EClinicalMedicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sophisticated algorithms are used daily to search through hundreds of medical journals in order to package updated medical insights into commercial databases. Healthcare practitioners can access these searchable databases-called Point of Care (PoC) tools-as downloadable apps on their smartphones or tablets to comprehensively and efficiently inform patient diagnosis and treatment. Because racist biases are unintentionally incorporated into the search reports that the companies generate and that practitioners regularly access, the aim of this article is to examine how healthcare practitioners' "pre-existing" racial stereotypes interact with pithy conclusions about race and ethnicity in PoC tools. I use qualitative research methods (content analysis, discourse analysis, open-ended semi-structured interviews, and role play) to frame the analysis within the Public Health Critical Race Praxis (PHCRP). This approach facilitates an understanding of how biological racism-the use of scientific evidence to support inherent differences between races-that is embedded in PoC algorithms informs a practitioner's assessment of a patient, and converges with persistent racial bias in medical training, medical research and healthcare. I contextualize the study with one semi-structured interview with an Editor of a leading PoC tool, MedScope (pseudonomized), and 10 semi-structured interviews with healthcare practitioners in S.E. Ontario, Canada. The article concludes that PoC tools and practitioners' personal biases contribute to racial prejudices in healthcare provision. This warrants further research on racial bias in medical literature and curriculum design in medical school.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.