The Impact of Demographic Inequalities & Provider Biases on Healthcare Access & Quality

Breaking It Down: How Biases Manifest in Healthcare

In our modern healthcare landscape, full of groundbreaking scientific and technologic advances, one would expect that equitable healthcare quality and access would be guaranteed for all patients. However, despite the progress we've made in care delivery, implicit biases associated with demographic inequalities continue to significantly impact health outcomes. As one of my wise graduate school professors said "Anything involving humans will be a messy endeavor", and that could not be more true in healthcare.

As we've explored through the Social Determinants of health, there are many factors that profoundly affect health outcomes, such as socioeconomic status, physical environment, social context and patient literacy. However, addressing and overcoming unconscious biases is one of the most challenging aspects to manage and regulate. Disparities caused by biases are not merely statistics; they translate into real-world consequences affecting millions of lives. Though there are many ways to slice and dice a population, this article delves into how biases relating to gender and race shape health outcomes and perpetuate inequalities in healthcare delivery.

How the Clinical Environment Fuels Biased Decision-Making

The clinical environment is fast-paced and complex, requiring clinicians to manage numerous patients, stay on top of charting and administrative duties and fulfill other responsibilities within a tight schedule. Clinical decision-making often involves a high degree of uncertainty based on what the patient reports and unknowns in how the patient's environment, genetic makeup or lifestyle is contributing to their issue. At times, a patient's symptoms or lab results do not clearly indicate a diagnosis, compelling providers to rely on their prior experiences to make informed decisions.

This challenging environment, combined with demanding workloads, long hours, and occasionally uncooperative patients, adds significant emotional stress to healthcare professionals. These conditions create a perfect storm for biases to emerge, as the environment often forces clinicians to rely on automatic mental shortcuts (System 1 thinking), using less cognitive effort to simplify decision-making.

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Gender

Gender disparities in healthcare manifest in many ways, more often impacting women more than men. Even at a foundational level, women often struggle to have their pain and symptoms taken seriously. For example, providers more commonly associate heart attacks with men and often attribute chest pain in women to be anxiety. So much so, that women are 50% more likely to receive an incorrect diagnosis  following a heart attack. Women are also 30% more likely to have their stroke symptoms misdiagnosed, if seen at an emergency department  . Endometriosis, a chronic condition where uterine lining tissue grows outside the uterus, affects 10-15% of women and causes severe pain and bleeding, significantly impacting their quality of life. Despite the severity, it can take 4-11 years for women to receive a correct diagnosis, and up to 60% of endometriosis cases may go undiagnosed  .

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Misdiagnosis can be attributed to many factors such as implicit biases, inadequate training and confusing symptoms for other ailments. However, one key factor that keeps clinician biases alive and ongoing stands out: the lack of representation of females (biological sex) in clinical studies. Historically, medical research has predominantly focused on white male subjects, leading to significant gaps in understanding how various conditions manifest differently in women and people of color. The primary reason is that females are considered more "complicated" to test on than males. The physiological changes associated with menstrual cycles and menopause add significant complexity in understanding how the body responds to a specific external stimuli  . Because of this underrepresentation, clinical guidelines and diagnostic criteria are often based on male criteria, perpetuating the issue of women being incorrectly and under diagnosed.  

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As complicated as it is to include women in clinical studies, it is imperative to do so. The components that make it difficult to study females is also the exact reasons why it is so important to include them: to understand how the differences in physiology affect outcomes. Authors from The Conversation have compiled an extremely useful infographic on how to include women in clinical studies.