COVID-19 has wreaked havoc on Black and Indigenous communities and other people of color, and U.S. medical institutions should be doing everything they can to root out and eliminate entrenched racial inequities. Yet many of the screening assessments used in health care are exacerbating racism in medicine, automatically and erroneously changing the scores given to people of color in ways that can deny them needed treatment.
新冠肺炎已經對黑人和土著社區以及其他有色人種造成了嚴重破壞，美國醫療機構應該盡其所能根除和消除根深蒂固的種族不平等。然而，醫療保健中使用的許多篩查評估都在加劇醫學上的種族主義，自動錯誤地改變了對有色人種的評分，使他們無法接受必要的治療。
These race-based scoring adjustments to evaluations are all too common in modern medicine, particularly in the U.S. To determine the chances of death for a patient with heart failure, for example, a physician following the American Heart Association’s guidelines would use factors such as age, heart rate and systolic blood pressure to calculate a risk score, which helps to determine treatment.
這些基於種族的評分調整在現代醫學中非常常見，尤其是在美國。例如，為了確定心力衰竭患者的死亡機率，遵循美國心臟協會(American Heart Association)指南的醫生會使用年齡、心率和收縮壓等因素來計算風險評分，這有助於確定治療方案。
But for reasons the AHA does not explain, the algorithm automatically adds three points to non-Black patients』 scores, making it seem as if Black people are at lower risk of dying from heart problems simply by virtue of their race. This is not true.
但由於美國心臟協會沒有解釋的原因，該算法會自動將非黑人患者的得分增加3分，這使得黑人似乎僅僅因為他們的種族而死於心臟問題的風險更低。這不是真的。
A recent paper in the New England Journal of Medicine presented 13 examples of such algorithms that use race as a factor. In every case, the race adjustment results in potential harm to patients who identify as nonwhite, with Black, Latinx, Asian and Native American people affected to various degrees by different calculations.
最近發表在《新英格蘭醫學雜誌》(the New England Journal of Medicine)上的一篇論文展示了13個使用種族作為因素的此類算法示例。在每一種情況下，種族調整都會對那些被認定為非白人的病人造成潛在的傷害，根據不同的計算結果，黑人、拉丁人、亞洲人和印第安人受到不同程度的影響。
These 「corrections」 are presumably based on the long-debunked premise that there are innate biological differences among races. This idea persists despite ample evidence that race—a social construct—is not a reliable proxy for genetics: Every racial group contains a lot of diversity in its genes. It is true that some populations are genetically predisposed to certain medical conditions—the BRCA mutations associated with breast cancer, for instance, occur more frequently among people of Ashkenazi Jewish heritage.
這些「糾正」大概是基於一個長期被揭穿的前提，即種族之間存在先天的生物差異。儘管有大量證據表明種族(一種社會結構)並不是遺傳學的可靠代表:每個種族群體的基因都有很多多樣性，但這種觀點依然存在。的確，一些人群的基因傾向於某些疾病——例如，與乳腺癌相關的BRCA基因突變，在德系猶太人後裔中更為頻繁地發生。
But such examples are rare and do not apply to broad racial categories such as 「Black」 or 「white.」
但這樣的例子很少見，也不適用於「黑人」或「白人」等寬泛的種族類別。
The mistaken conflation of race and genetics is often compounded by outdated ideas that medical authorities (mostly white) have perpetuated about people of color. For example, one kidney test includes an adjustment for Black patients that can hinder accurate diagnosis. It gauges the estimated glomerular fltration rate (eGFR), which is calculated by measuring creatinine, a protein associated with muscle breakdown that is normally cleared by the kidneys.
將種族和基因錯誤地混為一談，常常因為醫療當局(主要是白人)對有色人種的過時觀念而變得更加複雜。例如，一項腎臟檢查包括一項針對黑人患者的調整，這可能會妨礙準確診斷。它測量估算的腎小球濾過率(eGFR)，這是通過測量肌酸酐計算出來的，肌酸酐是一種與肌肉分解有關的蛋白質，通常由腎臟清除。
Black patients』 scores are automatically adjusted because of a now discredited theory that greater muscle mass 「inherent」 to Black people produces higher levels of the protein. This inflates the overall eGFR value, potentially disguising real kidney problems. The results can keep them from getting essential treatment, including transplants. Citing these issues earlier this year, medical student Naomi Nkinsi successfully pushed the University of Washington School of Medicine to abandon the eGFR race adjustment. But it remains widely used elsewhere.
黑人患者的評分被自動調整，這是因為一個現在已經不可信的理論，即黑人「天生的」更大的肌肉質量可以產生更高水平的蛋白質。這抬高了總體eGFR值，潛在地掩蓋了真正的腎臟問題。這一結果可能會使他們無法得到包括移植在內的基本治療。今年早些時候，醫科學生納奧米·恩金西(Naomi Nkinsi)引用這些問題成功地推動華盛頓大學醫學院放棄eGFR種族調整。但它在其他地方仍被廣泛使用。
A recent study in Science examined an algorithm used throughout the U.S. health system to predict broad-based health risks. The researchers looked at one large hospital that used this algorithm and found that, based on individual medical records, white patients were actually healthier than Black patients with the same risk score.
最近發表在《科學》雜誌上的一項研究檢驗了一種在整個美國衛生系統中使用的算法，該算法用於預測廣泛的健康風險。研究人員觀察了一家使用這種算法的大型醫院，發現根據個人醫療記錄，白人患者實際上比風險得分相同的黑人患者更健康。
This is because the algorithm used health costs as a proxy for health needs—but systemic racial inequality means that health care expenditures are higher for white people overall, so the needs of Black people were underestimated. In an analysis of these findings, sociologist Ruha Benjamin, who studies race, technology and medicine, observes that 「today coded inequity is perpetuated precisely because those who design and adopt such tools are not thinking carefully about systemic racism.」
這是因為該算法使用醫療成本作為健康需求的指標--但系統性的種族不平等意味著白人整體的醫療支出更高，因此黑人的需求被低估了。在對這些發現的分析中，研究種族、技術和醫學的社會學家魯哈·班傑明(Ruha Benjamin)指出，「如今，編碼不平等得以延續，正是因為那些設計和採用此類工具的人沒有仔細考慮系統性種族主義。」
The algorithms that are harming people of color could easily be made more equitable, either by correcting the racially biased assumptions that inform them or by removing race as a factor altogether, when it does not help with diagnosis or care.
對有色人種造成傷害的算法可以很容易地變得更加公平，要麼通過糾正那些告知他們存在種族偏見的假設，要麼在對診斷或護理沒有幫助的情況下，將種族作為一個因素完全剔除。
The same is true for devices such as the pulse oximeter, which is calibrated to white skin—a particularly dangerous situation in the COVID pandemic, where nonwhite patients are at higher risk of dangerous lung infections. Leaders in medicine must prioritize these issues now, to give fair and often lifesaving care to people left most vulnerable by an inherently racist system.
脈搏血氧儀等設備也是如此，它是根據白皮膚進行校準的——在新冠疫情中這是一個特別危險的情況，非白人患者患危險肺部感染的風險更高。醫學界的領袖們現在必須把這些問題放在首位，為那些因固有的種族主義制度而處於弱勢的人們提供公平的、往往能挽救生命的護理。