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Record W2012949327 · doi:10.1542/peds.113.5.1394

The Misuse of Race in Medical Diagnosis

2004· article· en· W2012949327 on OpenAlexaboutno aff
Richard Garcia

Bibliographic record

VenuePEDIATRICS · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWhite (mutation)SisterRace (biology)Family medicineGerontologyPediatricsGender studiesLaw

Abstract

fetched live from OpenAlex

I am a 39-year-old Hispanic male born in Stockton, Calif, to a mother who—after many years of unwise eating—has recently been diagnosed with diabetes and to a father I didn’t know who floated away at the end of a needle in his sister’s garage. I prefer being called Mexican to Hispanic, though I’ve never been to Mexico. I eat a fat American’s diet. Speak American English. Although I don’t smoke, I have been living in a big city with polluted air. An American city where I recently was an assistant professor of pediatrics, working in a profession that tries to define my indefinable race without asking for my input.I helped train medical students and residents who are all taught, as I was when I was a medical student, to assess each patient first in terms of age, race, and gender. Always in that order. A 52-year-old white female, a 3-month-old Asian male, a 39-year-old Hispanic male. The actual identity of patients remains ignored: A 47-year-old African American female—who’s never been to Africa and prefers to call herself black if ever asked by a white doctor, though none ever asks—two-pack-a-day smoker, still living with her mother in South Central Los Angeles, presents with fatigue.The doctor asks the patient—or the parent of the patient, if you’re a pediatrician—for his or her age. The gender is determined during the physical examination. But the doctor usually just assumes the patient’s race by looking at the person. My professors told me, and current textbooks still say, that knowing the patient’s race helps the doctor make an accurate diagnosis. So the doctor looks at the patient’s skin, nose, hair, lips—the silent mouth—and defines ancestry in a single word: Asian, Hispanic, white, African American. I smiled when one doctor described the Nigerian father of a patient as an African American. The Nigerian father didn’t smile.The textbooks say that a patient’s race can, and should, influence the doctor’s thinking about possible diagnoses. An Ashkenazic Jewish infant might have Tay-Sachs disease. A black boy might have sickle cell anemia. A Southeast Asian girl might have thalassemia. Of course, I know that Ashkenazic Jews get Tay-Sachs, but the only infant I ever saw with Tay-Sachs was a Mexican child. I didn’t misdiagnose the disease because he was Mexican instead of Jewish.Do all Hispanics have the same genetic risk for asthma? Do Mexicans and Puerto Ricans eat the same diet? What about a patient from Spain—is he Hispanic in the same way that I am?My childhood friend Lela wasn’t diagnosed with cystic fibrosis until she was 8 years old. Over the years, her doctors had described her as a “2-year-old black female with fever and cough…4-year-old black girl with another pneumonia. Lela is back.” Had she been a white child, or had no visible “race” at all, she would probably have gotten the correct diagnosis and treatment much earlier. Only when she was 8 did a radiologist, who had never seen her face to face, notice her chest radiograph and ask, “Who’s the kid with CF?”An emergency room physician referred a patient to me with this history: “A 14-year-old black male from South Central Los Angeles with a positive tox screen presents with headache. He’s probably in a gang.” I ordered a computed tomography scan of the patient’s head and discovered a large cyst that had blocked the normal flow of cerebral spinal fluid until the fluid had backed up and squashed his brain against his skull. Yes, he had a headache, and he had smoked a joint before going to the hospital.Those are just two examples of incorrect diagnoses caused by doctors who use racial assumptions to arrive at incorrect medical conclusions. As a physician, such misdiagnoses disturb me. I am also concerned as a father. I am Mexican from California, and my wife is black from Los Angeles. Our daughter is blonde with green eyes and pale skin. I have no known white ancestors, and that kind of heritage—even if it is just a legend—would not be left out of my family’s stories. In my wife’s case, her mother is now tracing their family’s roots back through American history; as of 1843, she has not found a single white ancestor. But my wife’s relatives generally have fair skin, and I suspect that my mother-in-law will eventually find a slave owner or overseer or some other white man who is responsible for that, and for my daughter’s appearance.What concerns me is that many years from now, when she is old enough to see a doctor with neither me nor my wife present, the doctor will use what he assumes is her race to misdiagnose her: “A 19-year-old white female presents with irritability.”Here is the crux of the problem: My daughter’s race can never be known. Her genetic risk for this or that disease is necessarily imprecise because she is a person, not a race.Americans used to define anyone who had “one drop of Negro blood” as a Negro, but we now know that definition makes no sense. We learn nothing if we group together as Asian Americans a man in Seattle who was born in the far-eastern portion of the former Soviet Union, a Korean woman living in Toronto, and a child in California with maternal grandparents who immigrated from China and a father whose ancestors came to New Jersey from Europe. There are almost as many definitions of Hispanic as there are Hispanics. Do I have the same genetic risk for sickle cell anemia as a Puerto Rican, a Spaniard, or a Mayan? What about my daughter, and the millions like her in this country, whose racial and ethnic ancestry defies geography and time?If by using a patient’s ancestry in medical discourse we can narrow the range of possible diagnoses, then at least we must be careful to describe accurately the genetic, ethnic, cultural, or geographical variables involved; guessing what category a person fits in is not acceptable. And when “race” cannot possibly matter, let us omit it. What difference does it make if it is an African American or an Asian who has an earache or ingrown toenail?Medical school professors must teach students that a Hispanic is not real. That an Asian American doesn’t exist. That whites exist only in America: They are Irish in Ireland, Italian in Italy, Spaniards in Spain. That harm—real, physical harm—can come from calling a child with cystic fibrosis an African American.Race does exist in America, alas. It’s why my daughter’s history here starts in slavery. It’s why my Mexican face identifies me to strangers before they know I’m an educated member of the middle class. It’s why nobody dares to ask for details about anybody else’s identity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.403
Teacher spread0.365 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations27
Published2004
Admission routes1
Has abstractyes

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Same venuePEDIATRICSSame topicRacial and Ethnic Identity ResearchFrench-language works237,207