Dalla Lana School of Public Health

Links

• https://tinyurl.com/cucerch7

Presented by: Canada-US Coalition to End Race Correction in Health Care in partnership with William Osler Health System, University Health Network, Unity Health Toronto and Knowledge Translation at the MAP Centre for Urban Health Solutions.

Date and Time (virtual event): June 13, 2024 from 12 pm – 1:30 pm EST

Register: https://tinyurl.com/cucerch7

About this talk:

This talk will explore what the reality of race correction means for the integrity of systematic reviews that:
– Concern or include data based on diagnostic tools that are race corrected;
– Do not explicitly take race correction into account.

Speakers will also discuss the implications for AI/machine learning, as systematic reviews and other peer-reviewed literature is often used for training data and modelling.

What is “race correction”?
Health care providers often use tests to assess a patient’s health. In many cases, health care providers calculate test results differently for Black patients than they do for everyone else. Overall, “race correction” means that Black people are diagnosed late, or never diagnosed at all, for serious conditions from heart, kidney and lung diseases to cognitive impairment. It also means that Black people are systematically excluded from timely access to life-saving treatments like organ transplants and other surgeries. “Race correction” has no scientific basis because “race” is not biological. It is a harmful social construct that is applied differently in different times and in different places.

Speakers:
LLana James (she/her) is the Chair of the Canada-US Coalition to End Race Correction in Health Care.

Amy Katz (she/her) is a Senior Knowledge Translation Specialist at MAP, Unity Health Toronto and a PhD student in the Faculty of Information at the University of Toronto.

Patricia O’Campo, PhD (she/her) is Canada Research Chair in Population Health Intervention Research and a Professor at the Dalla Lana School of Public Health at the University of Toronto.

Nav Persaud, MD, MSc (he/him) is the Canada Research Chair in Health Justice, Staff Physician in the Department of Family and Community Medicine at St. Michael’s Hospital in Unity Health Toronto, and Associate Professor in the Department of Family and Community Medicine at the University of Toronto.

Note: Sign language interpreters (ASL) will be signing during the event.

For any questions please contact ERC2022@pm.me

Below please find important background materials:
– Boston University School of Public Health (2022). Replacing the Term ‘Race’ in Risk Predictions for Heart Attacks among Black Patients. https://www.bu.edu/sph/news/articles/2022/replacing-the-term-race-in-risk-predictions-for-heart-attacks-among-black-patients/
– Canada-US Coalition to End Race Correction in Health Care. Race correction in health care: a primer. (2022). www.endracecorrection.com.
– Cerdeña, J.P., Plaisime, M.V., Tsai, J. (2020). From Race-Based to Race-Conscious Medicine: How Anti-Racist Uprisings Call Us to Act. The Lancet, 396(10257), P1125-1128. https://doi.org/10.1016/S0140-6736(20)32076-6.
– Deyrup, A., & Graves, J. L., Jr (2022). Racial Biology and Medical Misconceptions. New England Journal of Medicine, 386(6), 501–503. https://doi.org/10.1056/NEJMp2116224.
– Global News (2023). Whistleblowers allege University of Toronto data project collected 600K patient records without consent. https://globalnews.ca/video/9431153/whistleblowers-allege-university-of-toronto-data-project-collected-600k-patient-records-without-consent
– Graves, J.L. (2015). Great Is Their Sin: Biological Determinism in the Age of Genomics. The Annals of the American Academy of Political and Social Science, 661(1), 24-50. https://doi.org/10.1177/0002716215586558.
– Graves, J.L. (2015). Why the Nonexistence of Biological Races Does Not Mean the Nonexistence of Racism. American Behavioral Scientist, 59(11), 1474-1495. https://doi.org/10.1177/0002764215588810.
– Grubbs, V. (2020). Precision in GFR Reporting: Let’s Stop Playing the Race Card. Clinical Journal of the American Society of Nephrology, 15(8), 1201–1202. https://doi.org/10.2215/CJN.00690120.
– Moffett, A.T., Eneanya, N.D., Halpern, S.D., & Weissman, G.E. (2021, Abstract). The Impact of Race Correction on the Interpretation of Pulmonary Function Testing Among Black Patients. American Journal of Respiratory and Critical Care Medicine, 203:A1030. https://doi.org/10.1164/ajrccm-conference.2021.203.1_MeetingAbstracts.A1030.
– Opara, I.N., Riddle-Jones, L. & Allen, N. (2022). Modern Day Drapetomania: Calling Out Scientific Racism. Journal of General Internal Medicine, 37, 225–226. https://doi.org/10.1007/s11606-021-07163-z.
– Roberts, D.E. (2021). Abolish race correction. Lancet, 397(10268), 17–18. https://doi.org/10.1016/S0140-6736(20)32716-1.
– Parekh, R. S., Perl, J., Auguste, B., & Sood, M. M. (2022). Elimination of race in estimates of kidney function to provide unbiased clinical management in Canada. CMAJ : Canadian Medical Association journal = journal de l’Association medicale canadienne, 194(11), E421–E423. https://www.cmaj.ca/content/194/11/E421.
– Schillace, Brandy. (2021). Predicting Death Could Change the Value of a Life. Wired. https://www.wired.com/story/predicting-death-value-life/.
– Sjoding, M. W., Dickson, R. P., Iwashyna, T. J., Gay, S. E., & Valley, T. S. (2020). Racial Bias in Pulse Oximetry Measurement. New England Journal of Medicine, 383(25), 2477–2478. https://doi.org/10.1056/NEJMc2029240.
– Tsai, J. W., Cerdeña, J. P., Goedel, W. C., Asch, W. S., Grubbs, V., Mendu, M. L., & Kaufman, J. S. (2021). Evaluating the Impact and Rationale of Race-Specific Estimations of Kidney Function: Estimations from U.S. NHANES, 2015-2018. EClinicalMedicine, 42, 101197. https://doi.org/10.1016/j.eclinm.2021.101197.
– Tsai, J.W. (2021). Jordan Crowley would be in line for a kidney—if he were deemed white enough. Slate. https://slate.com/technology/2021/06/kidney-transplant-dialysis-race-adjustment.html.
– Vasan, R.S., Heuvel, E. (2022).Differences in estimates for 10-year risk of cardiovascular disease in Black versus White individuals with identical risk factor profiles using pooled cohort equations: an in silico cohort study. The Lancet. 4(1), E55-E-63. https://doi.org/10.1016/S2589-7500(21)00236-3
– Vyas, D. A., Eisenstein, L. G., & Jones, D. S. (2020). Hidden in Plain Sight – Reconsidering the Use of Race Correction in Clinical Algorithms. New England Journal of Medicine. 383(9), 874–882. https://doi.org/10.1056/NEJMms2004740.