Effects of using race and ethnicity in clinical algorithms in health care systems

NewsGuard 100/100 Score

A Special Issue of the peer-reviewed journal Health Equity focuses attention on the incorrect use of race and ethnicity in clinical algorithms in health care systems across the U.S. and internationally. The Special Issue is titled "Race Adjustment in Clinical Algorithms and Other Clinical Decision-making Tools."

The Guest Editors of the special issue are Michelle Morse, MD, MPH, Chief Medical Officer, Deputy Commissioner, New York City Department of Health and Mental Hygiene; Nichola Davis, MD, MS, Vice President, Chief Population Health Officer, NYC Health + Hospitals; Chandra Ford, PhD, MPH, Professor and Founding Director, Center for the Study of Racism, Social Justice & Health, UCLA Fielding School of Public Health; and Ruqaiijah Yearby, JD, MPH, Kara J. Trott Professor of Law, Moritz College of Law, The Ohio State University.

Included in the issue is the article titled "Challenging Race-Based Medicine Through Historical Education About the Social Construction of Race," by Allison Skinner-Dorkenoo, from the University of Georgia, and coauthors. The investigators tested an intervention that educates college students about the historical construction of racial categories in the U.S. They found that the interactive intervention had the potential to shape the way health care providers in-training understand race, their internalization of biologically essentialist explanations of disease, and willingness to adopt race-based treatment plans.

Leah Savage and Aaron Panofsky, in the article titled "The Self-Fulfilling Process of Clinical Race Correction: The Case of Eighth Joint National Committee Recommendations," develop a case study of the JNC 8's 2014 Evidence-Based Guideline for the Management of Blood Pressure in Adults, which recommends a different initial antihypertensive treatment for black versus non-black patients. "We illustrate that this case study exemplifies a self-fulfilling prophecy of racial reasoning, in which assumptions about racial difference inform the design and interpretation of research which then serve to reinforce ideas about racial differences leading to differential medical treatment," stated the investigators.

In "Effects of Race and Gender Classifications on Atherosclerotic Cardiovascular Disease Risk Estimates for Clinical Decision-Making in a Cohort of Black Transgender Women," Tonia Poteat, from the University of North Carolina School of Medicine, and coauthors, evaluated the effect of manipulating six different race-fender categories on atherosclerotic cardiovascular disease (ASCVD) risk scores among Black transgender women. "Race and gender categories are multidimensional, dynamic, and socially constructed structural factors that drive racialized and gender health inequities," stated the investigators. "Clinical reliance on current calculator's risks over or under-prescribing and perpetuating clinical biases that affect ASCVD treatment - ultimately reinforcing and perpetuating existing population-level inequities."

The. Issues features the article titled "Racial Disparities Among Predicted Bronchopulmonary Dysplasia Risk Outcomes in Premature Infants Born <30 Weeks Gestation" by Priyanka Patel, from Nemours Children's Health, and coauthors. The primary outcome of this study, which included a retrospective cohort of infants born <30 weeks gestation, was the difference in predictive risk of bronchopulmonary dysplasia (BPD) for non-Hispanic Black compared to non-Hispanic White infants. The secondary outcome was the disparity in theoretical administration of post-natal corticosteroids when the calculator was applied to the cohort. "When applied to our study cohort, the calculator resulted in a reduction in the predicted risk of BPD in non-Hispanic Black infants," concluded the investigators. "If utilized to guide treatment, the calculator can potentially lead to disparities in care for non-Hispanic Black infants."

"These articles represent the most cutting edge science that advance our understanding the limitations and the harms of race adjustment in clinical algorithms and affords us the opportunity to use rigorous evidence to design more equitable ways to treat patients," says Health Equity Editor-in-Chief Monica R. McLemore, RN, MPH PhD, Professor, Child, Family and Population Health Department and Interim Director, Manning Price Spratlen Center for Anti-Racism and Equity in Nursing, University of Washington, School of Nursing.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Benefits and challenges of integrating nursing home residents into clinical trials