Thread by @andreaprinzi

1/Listening to an amazing plenary talk by @DrCHWilkins on racism, disparities, and the role of race/ethnicity in medicine and research. AMAZING talk!
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2/Our focus always seems to be on race alone, and not on other social scenarios. We focus so much on personal choices and access to care-- but we focus less on disparities the way we should (and race as a fully sociopolitical concept).
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3/*Racism in medicine is =responsible for minorities having the worst healthcare & outcomes in the US
*Many famous physicians & scientists were involved in creating and perpetuating inferiority stereotypes
*Many continue to conflate race with biology & physiology
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4/Race is a sociopolitical construct, it is NOT biological!
*It is fluid, and changes over time
*There is NO biological or scientific basis for race
*Race is one of the most imprecise variables we use in human research
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5/One of my favorite things Dr. Wilkin's said during this talk:

*We have created this black vs white dichotomy that pushes people as far away from each other as possible*
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6/We should probably be checking up on many of our "idols." For example, Dr. Marion Sims (who is considered the "father of modern gynecology") did most of his research on enslaved black women without anesthesia.
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7/What should we be doing as clinicians & researchers to address these inequities?
1. De-biologize race
2. Reverse/reject unjust practices
3. Design scientifically just research
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8/De-biologize race:
*Racism, not race, causes health disparities
*It is important for us to understand that genetics is never going to replace a social construct

9/De-biologize race (cont)
*Change how we ask about race!
-A single combined question for race/ethnicity
-Which of these best DESCRIBES YOU?
-Select all that apply
-An example may look like: Asian (for example: Asian Indian, Chinese, Japanese, Korean, Pakistani, Vietnamese, etc.)

10/We need to stop using diagnostic algorithms that are based on flawed science, and that continue to perpetuate racism in medicine. There are some good examples of this here: livescience.com/racial-bis-hea…
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11/Consider:
Machine learning & AI is often built/based on samples/datasets that don't represent the population broadly. Socioeconomic data needed to understand these populations is missing. Often, these researchers are not from groups that have been marginalized or minoritized.

12/When researching, ask ourselves:
1. Who is the population that is most affected by the disease?
2. Has race been defined?
3. Is it clear how race will be used?
4. Are social determinants of health collected?
5. If white people are the control, why? Is this justified?

13/"Despite good intentions, we propagate and maintain a system where non-white populations bear the burden of disease but do not reap the benefits of research advances."
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14/Proposed actions the scientific community should adopt:
1. Strengthen compliance, transparency and accountability in clinical research enrollment
2. Address exclusionary research practices
3. Invest in sustained, reciprocal relationships with marginalized communities

15/Proposed actions the scientific community should adopt (continued)
4. Ensure enrollment goals are scientifically valid and reflect the burden of disease
5. Develop evidence-based guidance to inform inclusive research participation
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