IB 110 Chap.10 Should Medicine Stop Using Race?
Should Medicine Stop Using Race?
The question the course keeps asking
If race is a social construct, why not remove it from medicine altogether? The second lecture ends by asking what we would lose if we stopped acknowledging race now, and the third lecture opens with the answer that doing so would erase important aspects of people's experience and culture.
The fourth lecture lays out the reasoning.
Why removal is not simple
Centuries of socialization and unfair policies cannot be erased by deleting a label, and the labels still carry meaning because of what they did to different groups. Cultural experience is still partly defined by the social category. And colorblindness can uphold racism, because it ignores the structural problems that keep producing inequities.
Removing race also does not remove racism or change how race is perceived.
When ethnicity and ancestry help
Ethnicity matters when it describes important parts of identity. Linked ancestry can matter for health, and linked culture can reveal specific risks, such as dietary exposures.
The lecture cites a 2023 Northwestern University report arguing that if race has predictive power for a disease, clinicians should use all relevant information to make better predictions and care for the patient.
Disaggregation
Lumping groups together can hide risk.
A 2020 news report in the lecture describes a study in which Asian Americans as a whole looked healthier than non-Hispanic White adults, but separated by nationality the picture changed.
Vietnamese respondents were more than twice as likely to report fair or poor health, Japanese respondents were more often obese or overweight, Japanese and Korean respondents reported more diabetes, and Filipinos appeared least healthy of all the subgroups.
Race versus racism in how findings are written
The lecture collects headlines on colorectal cancer deaths among Black Americans linked to lower access to life-saving treatment, poorer health among Latino children in states with more anti-immigrant laws, and median PFAS levels 88% higher in Asian Americans than in non-Hispanic White adults.
It warns against blaming minoritized groups for their own health and offers an alternative framing: counting excess deaths, as in a report of 14,000 excess deaths among Connecticut's Black population.
Using race well in a written answer
Treat race as a record of how people have been treated and where they have been able to live, not as a description of their bodies.
Name the subgroup when the data allow it, name the mechanism or policy that produces the gap, and describe the gap as something preventable. That is the position the course builds across its first four lectures.
What this chapter covers
- 01
What is lost by ignoring race
- 02
Why history cannot be deleted
- 03
Colorblindness and structural racism
- 04
When ethnicity and ancestry help
- 05
The case for using predictive information
- 06
Disaggregating Asian American data
- 07
Headlines and blame
- 08
Excess deaths as a framing
Worked example · free
Rewrite a finding so it points at causes
- 2Rewrite the finding.
- 2Explain the change in emphasis.
Key terms
- Colorblindness
- Ignoring race in policy or practice, which the lecture argues can uphold racism by hiding structural problems.
- Disaggregated Data
- Data separated into subgroups, such as nationality, instead of reported for one broad group.
- Excess Deaths
- The number of deaths above what would be expected if a group had the rate of a comparison group.
Should Medicine Stop Using Race? FAQ
Should doctors stop using race in medicine?
The lecture argues against simply removing it. Race records experiences of racism and culture that affect health, and dropping the label would not remove racism. It should never be treated as a biological cause, and it should be broken into subgroups where they differ.
Why does disaggregating data matter?
Broad groups can hide risk. Pooled Asian American data looked healthier than White adults, but separated data showed worse health among Vietnamese and Filipino respondents and more diabetes among Japanese and Korean respondents.
What is wrong with blaming a group for its health outcomes?
It points attention away from the causes that can be changed, such as access to care and environmental exposure, and can deepen inequity. Framing a gap as excess deaths keeps the focus on what was preventable.
Exam move
Prepare a short argued answer to the lecture question on what is lost if race is no longer acknowledged. Use one example from disaggregated data and one from the history chapters, and end with the limit of your position.
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