How Stereotypes Impact Treatment Decisions in Healthcare

Bias in Medicine: The Blind Spots We Don’t Like to Admit

The “Good Patient” Bias

It’s the end of a long shift. You’ve seen a dozen cases, but this one patient greets you with a smile, follows every instruction, is polite, doesn’t question anything, and even thanks you on the way out. Subconsciously, you breathe easier. That’s a “good patient,” right? The kind we all wish for.

But here's the danger: we’re often more thorough, more empathetic, and more invested in these “good patients.” Meanwhile, the patient who is upset, mistrustful, anxious, or repeatedly non-compliant? They may get labeled as “difficult,” and the bias sets in. Their concerns might be dismissed as exaggerations. Their pain may be under-treated. Their diagnoses may be delayed.

This “halo effect” can skew clinical decision-making. It can lead us to under-investigate real issues just because someone isn’t likable—or over-investigate just because they are.

The Weight Bias: “Everything Isn’t Obesity”

Let’s be honest: how many of us have been guilty of seeing an overweight patient and jumping straight to lifestyle advice before fully listening to their symptoms? Studies show obese patients are less likely to be referred for advanced imaging and more likely to be told to “lose weight” regardless of the complaint—be it back pain or a migraine.

What’s worse? Patients pick up on it. They may avoid follow-ups or switch doctors because they feel judged rather than treated.

This bias also leads to diagnostic overshadowing. chest pain becomes reflux, fatigue becomes poor fitness, joint pain becomes too much weight bearing. Meanwhile, real pathologies get missed.

The Age Bias: “Too Young” or “Too Old” to Worry

“You’re too young for a heart attack.”

“This must just be stress.”

“She’s 87—we probably don’t need to screen further.”

Sound familiar? Age-based assumptions cut both ways. Younger patients often have their symptoms minimized (“it’s anxiety”), while older adults may have their symptoms dismissed as “normal aging.”

This bias leads to over-reliance on age as a diagnostic shortcut. Yes, probabilities matter, but anchoring on age can blind us to outliers—those zebras in the herd of horses.

The Socioeconomic Bias: “They Won’t Adhere Anyway”

Many physicians unconsciously adjust their care recommendations based on a patient’s perceived financial status, education level, or job.

We think: “He probably can’t afford that drug.”
“She won’t follow up.”
“They won’t understand the risks.”

And so, we offer substandard plans. Fewer diagnostics. Less aggressive therapy. Fewer referrals. Patients from lower socioeconomic backgrounds receive less preventive care, longer diagnostic delays, and less empathy—even in controlled studies with simulated patients.

It becomes a self-fulfilling prophecy.

The Gender Bias: “Women Exaggerate; Men Underreport”

Gender bias has deep roots in medicine. Women’s pain is often under-treated, chalked up to “hormones,” “anxiety,” or “overreacting.” Conversely, men may be over-investigated for the same symptoms, perceived as “stoic” or “serious.”

Take myocardial infarctions. Women are more likely to be misdiagnosed and discharged. Conditions like endometriosis or autoimmune diseases often take years to diagnose because their symptoms—fatigue, diffuse pain, GI issues—are often dismissed.

Meanwhile, men may delay care out of fear of stigma, and when they do show up, we might assume it's something more serious than it is.

The Racial and Ethnic Bias: “They Have a Higher Threshold”

Black patients, especially in the U.S. and Europe, have consistently been found to receive less pain medication for similar complaints compared to white patients. This isn't a theory—it’s a measurable reality.

There’s a disturbing myth that Black individuals feel less pain or have “tougher” skin—ideas with historical roots in pseudoscience that still echo in clinical care today.

Similar biases affect Indigenous, Hispanic, and Middle Eastern patients. Language barriers, cultural assumptions, and provider discomfort often lead to miscommunication, misdiagnosis, and mistrust.

The Mental Health Bias: “It’s Just in Their Head”

Patients with a psychiatric diagnosis—whether it’s depression, anxiety, bipolar disorder, or schizophrenia—often experience what's known as diagnostic overshadowing.

If they present with chest pain, it’s panic.
If they’re vomiting, it’s anxiety.
If they’re confused, it’s their baseline.

Actual medical pathology is easily missed. Worse, these patients often sense the bias and hesitate to seek help—even when they know something is wrong. This bias is particularly dangerous in emergency settings where time and assumptions both run high.

The “Frequent Flyer” Bias

Ah, the repeat visitor. The chronic pain patient. The one who knows the triage nurse by name. We roll our eyes, assume attention-seeking, and sometimes quietly think, “Here we go again.”

But buried in those repeat visits could be missed diagnoses: autoimmune diseases, rare cancers, evolving neurologic conditions.

Assuming someone is exaggerating because they’ve been here before blinds us to the possibility that something new—or something still missed—is happening.

The Confirmation Bias: “I’ve Already Made My Diagnosis”

Let’s not forget the mother of all cognitive traps. Once we latch onto a working diagnosis, our brains go on autopilot. We seek confirming signs and ignore contradictory ones.

You think it's cellulitis? You ignore the fact that there’s no warmth or swelling.
You think it's anxiety? You downplay the tachycardia and shortness of breath.

Even the most seasoned clinician is susceptible to this bias. It’s why second opinions, checklists, and differential diagnosis reviews exist—to save us from our own brain’s shortcuts.

The Compliance Bias: “They Didn’t Follow Instructions, So It’s Their Fault”

Sometimes we let frustration cloud clinical empathy.

“She didn’t take her meds. What did she expect?”
“He didn’t quit smoking. Why is he even here?”
“They didn’t show up to the follow-up.”

While non-adherence is indeed a challenge, we need to stop assuming it's rooted in laziness or disinterest. Patients may be facing financial constraints, side effects, cultural beliefs, or simple fear.

Punishing them with less effort, judgment, or “tough love” isn’t evidence-based medicine—it’s bias.

The Bias of Familiarity: “This Is My Long-Time Patient—They’re Fine”

You’ve seen Mr. K for 8 years. You know his diabetes numbers, his wife’s name, his last vacation. When he comes in with a vague complaint, you might assume it’s nothing serious. You’ve always been right before.

This is dangerous.

Familiarity can breed complacency. We skip systems reviews, defer labs, assume things without asking. Long-term relationships can blind us to subtle shifts in clinical status.

How to Spot Your Own Biases

We’re not bad people. We’re busy humans with busy brains. But being aware isn’t enough—we need systems to catch us when we fall:

• Pause before dismissing a concern. Ask: “Would I respond the same way if this were a different patient?”
  
  
• Practice “diagnostic humility.” Keep differentials broad, especially for vague symptoms.
  
  
• Use clinical decision support tools. They don’t have bias, even when we do.
  
  
• Audit your own patterns. Who gets referred for MRIs? Who gets admitted? Who gets pain meds?
  
  
• Get feedback. Colleagues, nurses, and even patients can spot our blind spots before we do.
  

Bias in Medicine Isn’t Always Overt—But It’s Always Harmful

It’s easy to think of bias as racism or sexism in its most extreme forms. But the biases that cause the most harm in clinical medicine are often subtle, silent, and systemic. They hide behind good intentions and rushed days.

By acknowledging them, naming them, and calling them out—even in ourselves—we do more than protect our patients. We become better doctors.

Better not just in skill, but in heart.