Chapter 13: Race, Racial Bias, and Health Care

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Welcome back to the Deep Dive.

Today we are opening up, well, a really critical discussion from bioethics.

Yeah, it's a tough one.

We're diving into a topic that I think should make all us rethink the supposed neutrality of modern healthcare.

Race,

racial bias, and healthcare.

We tend to rely on science and medicine to be objective, rational.

That expectation is absolutely essential, right?

But the sources we're looking at today, Louis Vaughn's work on this, it shows that these deep -seated racial biases and systemic inequities are just completely embedded within our health institutions, and this leads to tragic and measurable differences in who lives and who dies.

It's stark.

It really is the ultimate contradiction, isn't it?

Science aiming for universal human betterment, yet somehow we have systems that seem designed to perpetuate differential harm.

So our mission today is to, well, try and cut through some of the noise.

We're taking this deep dive to first establish some foundational definitions.

What is race?

What is racism?

Then we need to understand the ethical principles they violate and then, then look at the shocking real data.

Things like infant mortality rates, right up to discriminatory medical algorithms.

Absolutely.

And to do that properly, we really have to start at the very beginning.

We need to clarify what we even mean when we use the word race.

Okay.

So when people think of race traditionally, they usually think of biology, right?

Inheritable essential features that define separate groups.

Is that premise?

Is it even scientifically sound?

No.

Simply put, it's not.

The traditional idea of race, it centers on this concept of inherency.

Inherency meaning?

Meaning the belief that there are these discrete groups sharing permanent biological traits and that these traits somehow explain psychological or cultural differences.

But the scientific consensus is really firm on this and pretty much unanimous.

Race has no physical scientific basis.

It's a social construct entirely.

So if you were to, say, sequence the entire human genome, you wouldn't find a gene that someone is black or white or anything like that.

Precisely.

And what's fascinating actually is the genetics behind it.

The variations we do see, you know, the visual differences between someone from Southeast Asia and someone from Western Europe, they're there visually, but genetically.

The variation within any group we might label as a race is often much greater than the average variation between different groups.

Wow.

So that core assumption of traditional racism that we're fundamentally biologically different, it just collapses.

It completely collapses.

And if that foundation goes, then the whole basis for race -based discrimination really goes with it too.

Okay.

So if the biology isn't real in that sense, then what actually is racism?

How do we define it?

Right.

Well, racism starts with that false presupposition that distinct races do exist, but then it adds two crucial elements.

First, the belief that some of these supposed races are inherently inferior.

Scholars often call this inferiorization.

Inferiorization.

Okay.

And second, the belief that these inferior groups deserve dislike or hostility.

That's antipathy.

So it's both assigning a lower status and having that negative feeling or hostility towards it.

Exactly.

It's that dual action,

assigning a permanent lower station and then acting on, or at least feeling, that hostility.

That's what really defines it according to the sources.

That brings us to a really complex ethical point then.

If biological race is just a social fiction, why don't we just stop using the term?

Why not aim for color blindness?

Seems simpler.

It seems simpler, but it's a profoundly important question.

And actually, many observers argue pretty strongly that aiming for immediate color blindness is, well, morally problematic, maybe even wrong.

Why?

How so?

Because while biological race isn't real, racialized groups absolutely are.

These are the groups that society and policy have treated as distinct races for centuries.

Ah, okay.

So the treatment based on perceived race is the reality, even if the biological basis isn't.

Precisely.

And if we just stop using the concept of race altogether,

we immediately lose our ability to name, to quantify, and critically to address the historical wrongs.

We can't track ongoing discrimination or the unearned advantages that groups like white groups have historically held and often still hold.

We have to keep the terminology to keep track of the harm and the inequality.

That makes the ethical argument much, much clearer.

It's not about seeing biological differences that aren't there.

It's about recognizing how society treats people based on those perceived differences.

Okay, let's pivot now to those foundational ethical arguments.

We all kind of inherently know racism is wrong.

What specific bioethical principles, according to the text, does it violate?

Right.

If we look at the core principles we always come back to in bioethics, racism just fails spectacularly on three main counts.

First, it violates the principle of respect for persons.

This is fundamental.

It demands that we acknowledge every single individual's ultimate inherent worth and their basic human rights.

And racism obviously denies that inherent worth.

It leads directly to discrimination.

Directly.

It treats people as means or as less than persons based on their group identity.

Okay, so respect for persons is number one.

What's next?

The principle of justice.

This one's pretty straightforward, too.

Justice requires that equals be treated equally.

Any differential treatment needs to be justified by a morally relevant difference.

And race, as we've just established, is not a morally relevant difference.

Exactly.

So when racial categories are used to distribute resources, access to care, quality of treatment, that's a direct violation of justice.

Simple as that.

And the third principle you mentioned,

utility.

Yes, the principle of utility.

This principle is about maximizing overall benefit and minimizing harm.

Racism, pretty clearly, produces immense demonstrable harm and suffering.

And this is an abstract harm, right?

We're talking measurable things.

Absolutely measurable.

Higher disease rates, shorter life spans, the psychological burden of chronic stress.

The list goes on.

It creates a massive net harm.

That failure to maximize good over bad, benefit over harm, is the violation of utility.

That ethical breakdown is really helpful.

It shows the moral cost, clearly.

But we need to distinguish, I think, between individual acts of prejudice, like someone shouting a slur, and this deeper, more systemic problem.

What's the difference between individual and structural racism?

That's a crucial distinction.

Individual racism is, like you said, easier to spot.

It's person to person discrimination,

overt intolerance, maybe explicit bias.

Structural or institutional racism, on the other hand, is far more pervasive.

And often it's kind of unseen, or at least less obvious.

How does it work then?

It's the unequal treatment that results from the way organizations, institutions, social systems operate.

It happens through policies, practices, procedures that might even look neutral on the surface.

And here's the kicker.

It can persist, even if the individuals within that system aren't personally prejudiced or explicitly trying to discriminate.

The system itself becomes the bias machine.

The system itself is the bias machine.

That's a powerful way to put it.

And we can actually see the output of this machine in the huge socioeconomic inequalities that scholars like Eduardo Bonilla Silva point out.

Let's talk about that wealth gap for a second.

Yeah, the wealth gap statistics are just stunning.

They're a really direct measure of this kind of structural failure over time.

The sources we looked at show that back in 2016, the typical black household had wealth around what was at $13 ,000, compared to nearly $150 ,000 for a typical white household.

That's more than a tenfold difference.

That's staggering.

It is.

And the crucial thing to understand is that this massive difference isn't an accident.

It didn't just happen.

It was manufactured, deliberately or not, over decades by racist policies.

And a key historical mechanism for this, this sort of multi -generational theft was redlining.

Can you walk us through how that specific policy worked?

It's such a clear example.

Redlining is, yeah, probably the perfect illustration of structural racism in action.

So back in the 1930s, you have the Federal Housing Administration, the FHA.

This is the government body essentially insuring home loans, making homeownership accessible.

Right.

A huge engine for wealth building after the war, especially.

But the FHA created these underwriting manuals and they explicitly stated that for neighborhoods to be considered stable and worthy of insured loans, the properties had to be occupied by the same social and racial classes.

They actually wrote that down.

They wrote it down.

And they went further.

They created maps for cities across the country and literally drew red lines around areas they deemed hazardous for lending.

These were overwhelmingly black communities, but also other minority groups and immigrant neighborhoods.

So by refusing to back loans in these redlined areas,

the FHA effectively choked off investment.

Completely.

It suppressed home values within those red lines.

It prevented black families and others in those areas from building generational wealth through home equity, which, as you said, is arguably the single largest source of wealth for most American families.

While at the same time, they were actively subsidizing wealth accumulation for white families moving into newly developed, non -redlined, often suburban areas.

It was government sanctioned, institutionalized segregation and wealth stripping.

It used the power of the federal government to define who could and couldn't participate in the massive post -war housing boom.

And that connects racist policies from, you know, 80, 90 years ago directly to the enormous wealth disparities we still see today.

It's a long shatter.

It really is.

Okay, so easy to talk about abstract systems and historical policies, but where we really see the human cost is in the cold hard data on health outcomes.

What are some of the most alarming statistics the chapter highlights regarding health disparities?

Well, I think the most tragic and maybe the most telling disparity mentioned is infant mortality.

The numbers are just heartbreaking.

What do the data show?

In 2013, the infant mortality rate among African Americans was 11 .1 deaths per 1000 live births.

For white infants, it was 5 .06.

More than double.

More than double.

And the text puts this in a global perspective that's really shocking.

If black America were treated as a separate nation, its infant mortality rate would rank it 95th in the world behind many, many developing nations.

That number.

Yeah.

Yeah.

That's the kind of statistic that just stops you cold.

It really underscores the scale of this systemic failure, doesn't it?

It does.

And beyond infant mortality, we see significant gaps in life expectancy too.

You know, African American males living on average several years less than white males.

And higher death rates from major diseases.

Yes, higher age -adjusted death rates for black individuals from heart disease, from cancer, from diabetes.

The list goes on.

So what causes these disparities?

Is it just poverty,

lower socioeconomic status?

Well, socioeconomic status, SES, definitely plays a role, no question.

Lower income limits, access to good care, healthy food, safe environments, et cetera.

But the research presented is pretty clear.

Structural racism itself is a major independent cause of these poor health outcomes.

It's not just reducible to poverty.

Okay.

So how does structural racism directly impact health separate from just income level?

What are the mechanisms?

The text points to two main mechanisms.

First, there's the impact of chronic stress.

From experiencing racism day Exactly.

Constant exposure to what's sometimes called everyday racism or racial microaggressions.

Things like being treated with less courtesy or respect, being viewed with suspicion, being followed in stores, getting subtle insults.

Living with that constant vigilance and stress generates a physiological response.

It's linked to chronic inflammation, hypertension, cardiovascular problems, and it demonstrably leads to poor birth outcomes like low birth weight and premature birth, independent of other factors.

So the stress itself makes people sick.

What's the second mechanism?

The second is residential segregation, which is often a direct result of policies like redlining we just talked about.

How does where you live impact health so directly?

Well, segregated neighborhoods often have fewer high quality health care providers.

They might be food deserts with limited access to fresh, healthy food options.

They can have higher levels of environmental hazards, pollution,

lead paint, lack of green spaces, all of these directly impact health outcomes for the people living there.

Right.

So we've established that history, policy, and ongoing systemic issues create these broad disparities.

Now let's zoom right into the clinic.

What happens when a patient actually interacts with the health care system today?

The Institute of Medicine finding is pretty damning, isn't it?

That minority patients consistently receive fewer procedures and poor quality medical care than white patients, even when you control for things like insurance status, income, or how severe their disease is.

It is damning, and it points to something happening within the clinical encounter itself.

How can that happen?

Especially when most health care providers genuinely believe in equity and want to help all their patients equally.

It seems contradictory.

It does seem contradictory, and the answer, according to the research Vaughn presents, largely lies in implicit bias.

Implicit bias.

Define that for us again.

Implicit bias is basically a negative attitude or stereotype about a particular group that operates outside of our conscious awareness and control.

It's unintentional.

Decades of psychological research confirm that these biases are pervasive.

We all have them, to some extent, shaped by the culture and messages around us, and crucially, they can have a more powerful impact on our actual behavior than our explicitly held beliefs, our conscious intentions.

So it's not necessarily conscious prejudice or malice from the doctor, but more like the brain taking a flawed shortcut based on ingrained stereotypes.

That's a really crucial distinction.

It is.

The text uses this kind of visualization.

Imagine a white physician meeting an elderly African -American patient for the first time.

The physician might hold absolutely no conscious ill will.

They might genuinely believe in treating everyone the same.

But their brain might subconsciously recrieve what the text calls social group knowledge.

These are stereotypes absorbed from media, society, maybe even past experiences, perhaps associating black patients with poverty, lower education, non -compliance, maybe even things like incarceration rates.

And those subconscious associations, even if the doctor rejects them consciously, can influence their decisions.

Yes.

They can subtly shape the doctor's perception of the patient, their assessment of the patient's credibility, their assumptions about the patient's lifestyle or ability to adhere to treatment.

And this might lead unintentionally to harmful treatment choices, maybe withholding a complex or expensive treatment option or spending less time explaining things or dismissing the patient's complaints more readily.

So this unintentional discrimination ends up directly contradicting the physician's stated values and intentions to practice equitably.

That's exactly the problem.

It creates a gap between intention and impact.

But there is a critical piece of good news embedded in all this research on implicit bias.

These biases are alterable.

Oh, that's important.

They're not fixed.

No, they're not fixed personality traits.

They are learned associations.

And because they're learned, they can be unlearned or overridden.

They can be influenced and controlled by conscious individual choice, by motivation, and importantly, by external factors like training, exposure to counter stereotypes, and creating systems that check Okay, that's essential to remember if we're thinking about solutions.

That leads us to the final and maybe most ethically complex area discussed, race -based medicine.

This is the idea or the practice of actually using race as a factor when deciding on medical treatment.

Is this a useful shortcut, maybe a proxy for genetic differences, or is it just another form of racial profiling in a clinical setting?

It is intensely controversial and the debate is

On one side, some physicians argue that observed statistical correlations justify using race as a kind of rough guide in treatment.

The classic example often cited is prescribing certain heart failure medications like ACE inhibitors, where some early studies suggested different average response rates between black and white patient groups.

So using race as a quick predictor of who might benefit most.

Kind of.

But critics, including the philosopher Michael Root, whose arguments are discussed in the text, raise some really serious objections to treating race as a valid biological proxy in medicine.

He makes three main points against it.

Okay, what's the first objection?

First, it ignores intra -racial differences.

This is huge.

Let's say a study shows, hypothetically, that 70 % of black patients respond poorly to drug X.

That still means 30 % respond well.

If you create a policy or practice of not giving drug X to any black patients based on group average, you are actively denying potentially effective treatment to that 30 % of individuals who would have benefited.

You're treating the group statistic as if it applies identically to every person within the group.

Right, you're sacrificing individual benefit for group categorization.

What's the second objection?

The second is that the observed correlation might not even be biological at all.

Many of those differential drug response studies, especially older ones, failed to adequately control for crucial environmental and social factors.

Like what?

Like socioeconomic status, diet, access to care, exposure to chronic stress, environmental toxins, all the things we just discussed that disproportionately affect certain racialized groups due to structural factors.

So the difference in drug response might be caused by these environmental factors, not by some underlying genetic difference linked to race.

And Root's third point.

The third point brings us back the beginning.

Since biological race is a social construct, there are no race genes in the way people often imagine.

The genes that actually influence things like drug metabolism vary within and across populations, but they don't map neatly onto these broad socially defined racial categories.

So treating race as an independent variable that causes genetic differences in drug response is fundamentally flawed from a scientific standpoint.

This whole debate is now getting even more complicated, isn't it?

Because it's literally being baked into the technology we use through diagnostic algorithms.

The text mentions race correction.

That sounds problematic.

It sounds problematic because it often is problematic.

It's essentially taking these contested race -based assumptions and embedding them into software that doctors use to make decisions.

It's like automating structural racism.

Can you give an example from the text?

Yeah, there's a really concerning example of a widely used algorithm in the U .S.

that was designed to predict which patients needed extra health care resources like care management programs.

It turned out this algorithm systematically discriminated against black patients.

It was significantly less likely to refer black patients for this extra help compared to white patients, even when the black patients were equally sick or even sicker based on objective health measures.

Why would it do that?

How did the bias get in?

The algorithm used health care cost as a proxy for health care need.

But because of systemic barriers and biases, black patients, on average, generated lower health care costs than white patients at the same level of sickness.

So the algorithm incorrectly concluded they were less sick or needed less help.

Wow.

So it wasn't explicitly programmed to be racist, but it used a bias proxy that led to discriminatory outcomes.

Exactly.

It propagated race -based disparities without anyone intending it to.

And the surgical risk calculator example is

Right.

Tell us about that one.

There are risk calculators used, for instance, before major thoracic surgery, lung surgery, heart surgery.

And some of these calculators automatically increase the estimated risk of death for African -American patients compared to white patients, sometimes by nearly 20%.

Based on what evidence?

That's the problem.

The adjustment is often made based on older observational data showing a correlation.

But the actual mechanism for that supposed difference in risk is unknown.

It might be due to underlying health conditions related to systemic disadvantage or differences in hospital quality, or even bias in how risk was measured in the first place.

But the algorithm just applies the penalty anyway.

It applies the penalty.

And the potential result.

It could wrongly steer black patients or their doctors away from necessary, potentially life -saving surgery because their calculated risk looks artificially inflated.

So when we embed these unexamined race -based assumptions into our technology, into our algorithms, we risk, as the tech says, baking inequity right into the system for years to come.

That's the profound danger, yes.

Okay, so let's try to pull this all together.

What does this deep dive really tell us?

We've seen pretty clearly that race, biologically speaking, is a social construct.

It's not rooted in genetics in the way people traditionally thought.

Right.

But despite that, the social reality of race, and specifically structural racism and implicit bias, has devastating real -world consequences.

Consequences we can measure in massive persistent health disparities.

Things like infant mortality, life expectancy, rates of chronic disease.

And these biases aren't just historical artifacts.

They're operating right now, consciously or unconsciously, in individual interactions within institutional structures, and now even within the medical algorithms designed to help us.

So the challenge moving forward is immense.

It involves confronting these biases at every level, the structural, the unconscious personal biases, and these new algorithmic biases.

It really does.

And maybe we can leave you, the listener, with one final provocative thought that comes out of Michael Root's critique in this whole discussion.

It highlights a real tension.

If individual doctors might sometimes be able to use race -conscious clinical judgments based on imperfect population statistics in a way they believe benefits their specific them,

should the medical community as a whole, as a matter of policy, adopt a stance of strictly ignoring race in all treatment decisions?

What would be the effect of that?

Well, such a policy might mean that some specific individuals are potentially worse off in the short term if a useful statistical correlation is ignored.

But, the argument goes, maybe that policy is necessary to protect entire racialized groups from the much larger systemic harm caused by widespread racial profiling and algorithmic discrimination in medicine.

A tension between individual optimization and preventing group harm.

Exactly.

Where should the balance lie?

It's not an easy question.

What stands out to you as you think through all this?

That is definitely a powerful tension to consider.

It gets to the heart of justice in healthcare, doesn't it?

Thank you for joining us on this deep dive into the incredibly complex and vitally important intersection of bioethics and racial equity.