Reassessing the Use of Race in Clinical Algorithms: An Interactive, Case-Based Session for Medical Students Using eGFR

Vijayvardhan Kamalumpundi; Carolina Gonzalez Bravo; Ariele Andalon; Amy L. Conrad; Joyce Goins-Fernandez

doi:10.15766/mep_2374-8265.11412

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Reassessing the Use of Race in Clinical Algorithms: An Interactive, Case-Based Session for Medical Students Using eGFR

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Reassessing the Use of Race in Clinical Algorithms: An Interactive, Case-Based Session for Medical Students Using eGFR

Vijayvardhan Kamalumpundi, Carolina Gonzalez Bravo, Ariele Andalon, Amy L. Conrad and Joyce Goins-Fernandez

MedEdPORTAL, Vol.20, 11412

06/21/2024

DOI: 10.15766/mep_2374-8265.11412

PMCID: PMC11219082

PMID: 38957523

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Abstract

Introduction: Medical curricula implicitly teach that race has a biological basis. Clinical rotations reinforce this misconception as race-based algorithms are used to guide clinical decision-making. This module aims to expose the fallacy of race in clinical algorithms, using the estimated glomerular filtration rate (eGFR) equation as an example. Methods: We created a 60-minute module in consultation with nephrologists. The format was an interactive, case-based presentation with a didactic section. A third-year medical student facilitated the workshops to medical students. Evaluation included pre/post surveys using 5-point Likert scales to assess awareness regarding use of race as a biological construct. Higher scores indicated increased awareness. Results: Fifty-five students participated in the module. Pre/post results indicated that students significantly improved in self-perceived knowledge of the history of racism in medicine (2.6 vs. 3.2, p < .001), awareness of race in clinical algorithms (2.7 vs. 3.7, p < .001), impact of race-based eGFR on quality of life/treatment outcomes (4.5 vs. 4.8, p = .01), differences between race and ancestry (3.7 vs. 4.3, p < .001), and implications of not removing race from the eGFR equation (2.7 vs. 4.2, p < .001). Students rated the workshops highly for quality and clarity. Discussion: Our module expands on others’ work to expose the fallacy of race-based algorithms and define its impact on health equity. Limitations include a lack of objective assessment of knowledge acquisition. We recommend integrating this module into preclinical and clinical curricula to discuss the use of race in medical literature and clinical practice. *************************** Educational Objectives By the end of this session, learners will be able to: 1. Discuss how race is used in clinical algorithms, with an emphasis on the estimated glomerular filtration rate (eGFR) equation. 2. Explain how race-based clinical algorithms can magnify existing inequalities in health care. 3. Identify differences between race, ancestry, and genetics. 4. Describe the implications of removing the race-correction factor from the eGFR equation.

Details

Title: Subtitle: Reassessing the Use of Race in Clinical Algorithms: An Interactive, Case-Based Session for Medical Students Using eGFR
Creators: Vijayvardhan Kamalumpundi - Mayo Clinic
Carolina Gonzalez Bravo - University of Iowa
Ariele Andalon - University of Iowa
Amy L. Conrad - University of Iowa
Joyce Goins-Fernandez - University of Iowa
Resource Type: Assignment/exercise
Publication Details: MedEdPORTAL, Vol.20, 11412
DOI: 10.15766/mep_2374-8265.11412
PMID: 38957523
PMCID: PMC11219082
NLM abbreviation: MedEdPORTAL
ISSN: 2374-8265
eISSN: 2374-8265
Language: English
Date published: 06/21/2024
Academic Unit: Pediatric Psychology; Stead Family Department of Pediatrics; Iowa Neuroscience Institute; Craniofacial Anomalies Research Center; Medicine Administration; Internal Medicine
Record Identifier: 9984648356802771

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