How AI Can Remedy Racial Disparities In Healthcare

The story of American medicine is one of incredible scientific advancements, from the use of penicillin to treat syphilis and other bacterial infections to the countless biomedical breakthroughs made possible by cell-line research. 

Too often, however, these stories ignore an uncomfortable truth: Some of our nation’s most significant medical discoveries were made possible through the mistreatment of Black patients—from the exploitation of African American farmers during the Tuskegee Syphilis Experiments to the tragic case of Henrietta Lacks, a black patient whose cells were stolen by doctors and used for decades of cell-line research.

Racism is woven into our nation’s medical past but is also part of our present, as evidenced by the Covid-19 crisis. From testing to treatment, Black and Latino patients have received a lower quality and quantity of care compared white Americans.

As a country, we now have the opportunity to reverse course. Rather than advancing medicine through racist actions, we can combat racism in medicine with the use of science and technology. Artificial intelligence and data-based algorithms can help address health disparities and break down the barriers to healthcare equity, like these:

At some point during medical school, all future doctors are instructed to treat everyone equally, regardless of a person’s race, ethnicity, gender, religion or sexual orientation. Studies have shown just how difficult this edict proves in practice.

Even when physicians have the best of intents, their actions are beset by unconscious prejudices. Researchers have found that two out of three clinicians harbor what is called an “implicit bias” against African Americans and Latinos. These are biases that exist outside the doctor’s awareness but are nonetheless harmful to minority patients. 

In one example, epidemiological data demonstrate that Black individuals have experienced a two to three times higher likelihood of dying from Covid-19 than white patients.

Physicians attribute this discrepancy to the “social determinants of health,” a phrase that encapsulates the many aspects of life that influence our health, including where we live, work, play and socialize. But before we accept this explanation and let healthcare professionals off the hook, consider what we learned early in the pandemic: According to national studies, white patients who came to the emergency room with symptoms likely to be Covid-19 were tested far more often than Black patients with identical symptoms.

Or consider this: Studies show Black women are less likely to be offered breast reconstruction after mastectomy than white women. Or this: Research shows that Black patients are 40 percent less likely than white patients to receive pain medication after surgery.

In a medical culture that falsely believes all patients are treated equally, white physicians fail to recognize how often Black and Latino patients are treated as other.

Technology can mitigate this threat. Early experiments using artificial intelligence have shown some success in replacing or supplementing the physician’s judgment (and implicit biases) when diagnosing a patient’s pain or medical needs. 

And by using information pulled from each doctor’s electronic health record, AI applications can compare treatments provided to patients of different racial or ethnic backgrounds within the individual physician’s practice. That data can be used to program alerts, notifying doctors when they are providing unequal treatment to a patient of different race. 

A little over a year before the coronavirus pandemic reached our shores, the racism problem in U.S. healthcare was making big headlines. 

But it wasn’t doctors or nurses being accused of bias. Rather, a study published in Science concluded that a predictive healthcare algorithm had, itself, discriminated against Black patients.