As I sat in my clinic, ready to see the next patient, my nurse walked-in and handed me the chart with the “heads-up” that the next patient is an attorney. Now, being married to an attorney, I guess I’m not that phased by carrying on normal conversations with them as I’m confident they live, breathe, and sleep the same, but it did underscore a bigger problem in healthcare: bias.
What about the next patient who perhaps doesn’t speak English, or took the bus to the office? Bias is real. Bias is present. Admitting it doesn’t make you a bad person, a racist, or any other label. What it means is that you acknowledge we subconsciously (or even consciously) alter our interactions based on what WE perceive to be the reality, and that can have profound downstream impact on the care and outcomes for our patients.
Data has now consistently shown that racial bias in the healthcare system affects the care and treatment of minorities. Indeed, the AMA just announced that racism is a threat to public health. This bias extends beyond our interactions with patients and also includes the technology advancements, data analytic tools, and therapeutics. In an article published by the New England Journal of Medicine, it is discussed that by “embedding race into the basic data and decisions of health care, these algorithms propagate race-based medicine.” The article goes on to say that “many of these race-adjusted algorithms guide decisions in ways that may direct more attention or resources to white patients than to members of racial and ethnic minorities.” Oftentimes in hospitals there are certain criteria that clinicians have to follow when administering care to patients. One of the troublesome issues this presents is where these systems and criteria are catered towards giving better care towards white patients.
The AHA for instance has a Heart Failure Risk Score that predicts the risk of death in patients admitted to the hospital, upon being examined a patient will be given a certain score. These criteria assign an additional 3 points to any patient who identifies as ‘nonblack’, thus, registering them at a higher risk and subsequently directing care and resources away from a potentially equal risk patient because they are black. This does not just extend to a specific instance with a certain kind of care, these algorithms run rampant in the treatment plans and patient care across the board. When investigated further, “some algorithm developers offer no explanation of why racial or ethnic differences might exist. Others offer rationales, but when these are traced to their origins, they lead to outdated, suspect racial science, or to biased data.” One of the chief concerns with following these guidelines and algorithms is that even when abiding by the rules to the letter, still minority groups are being disenfranchised.
Though scientific fields such as medicine often pride themselves on following the data, the interpretation of it can be fraught with error. For example, controlling for a confounder such as black race, treats it as a dichotomous variable, not as a variable impacted by numerous variables itself (ie being black in America). This is not to say that in certain clinical scenarios race does not impact the treatment recommendation, but as clinicians we must ensure that every patient receives the same quality of care irrespective of race, and critically examine our established norms based on data.
Informed consent is another area susceptible to bias. The information is delivered by the clinician, who may not be conscious of internal biases formed from years of practicing in a less than ideal system. The clinician is tasked with communicating the nature of the procedure, the risks, benefits, reasonable alternatives, and assessment of the patient’s understanding. However, the level at which this is done, can unfortunately be influenced by the doctors preconceived notions (implicit or subliminal). This issue can extend past race to socioeconomic status, age, and gender to name a few. This can even extend to language barriers, and communicating in one’s native language.
The standard of care and the process of communicating informed consent should not be affected by any of the aforementioned, however often it is. It is important that we seek out ways to bring this to the forefront and hold ourselves accountable. There are many ways to improve the patient care experience and make it more standardized for every individual no matter your race, age, gender, ethnicity, or native language. For us here at Confirmed Consent, this was a motivating factor in developing our informed consent platform. What have we done to address this?
- By providing closed-captioning on our consent material for those that need it.
- By providing the platform in non-English languages when necessary to ensure that each patient receives the information via certified and documented translation, and not impactedby the interpreters understanding of the spoken word at the visit.
- By providing the same information each and every time, irrespective of their race, ethnicity, profession, gender, or other factor leading to bias.
- By ensuring each patient understands the value of informed refusal.
- By confirming each patient had the right state of mind to give consent, and wasn’t coerced or rushed
As always, feel free to email us with questions at and check out our website to request a demo at confirmedconsent.com. Stay tuned for our next blog post!