Overcoming Implicit Bias in Medical Product Development

The science and the practice of medicine are supposed to rise above the fray, to be immune to the taint of culture and society. They are supposed to be driven by empiricism, objectivity, and, above all, the ethos of doing no harm.
 
Unfortunately, however, the reality is often far different. A culture’s most nefarious and reprehensible attributes are as likely to leach into the practice of medicine as they are into other social and professional domains. And what is true of clinical practice is also true of the activities that make clinical practice possible.
 
Medical product development, for example, has long suffered the contamination of implicit bias in both its processes and its products. The good news, though, is that it does not have to be this way. It is possible to overcome implicit bias in medical product development for a successful outcome.

What Is Implicit Bias?

Very few of us want to believe or acknowledge that we harbor bias against specific communities based on race, ethnicity, gender, or other identity categories. The reality, though, is that bias is ubiquitous in our culture, regardless of who you are, what your background is, or what your ideological worldview may be.
 
But as pernicious as bias is, what makes it even more damaging is that such prejudices are often unconscious. It is this failure to recognize implicit bias that makes it so pernicious and prolific. It is also this lack of acknowledgment of the existence, and the impacts, of implicit bias that makes it prevalent in both clinical practice and medical product development.
 
For this reason, the first and perhaps more important step in eradicating implicit bias in medical product development is simply to understand what it is, to recognize how and why it occurs, and to take proactive measures to address it both within yourself and within your product team.

Diversifying Target Patient Models

The most significant manifestation of implicit bias in medical product development lies in the use of homogenous target patient models as the basis of product design strategies. Traditionally, most medical products have been created with the image of the middle-aged, caucasian male patient in mind.
 
And this means that devices have been tailored to the average anatomy and physiological functioning of the healthy, white, adult male. The result has been products that present skewed data or poor functionality for other demographic groups — from women to people of color. For instance, many pulse oximeter technologies have been found to be significantly less reliable in detecting hypoxia in patients with darker skin tones due to the computational biases informing the development process.
 
These systems, more specifically, were not designed to account for variations in detector functioning based on the wearer’s skin tone, which can affect the scanner’s capacity to penetrate the layers of the skin for a more reliable oxygen reading.
 
In light of realities such as these, the practice of medicine is increasing, if somewhat controversially, incorporating race-based research to enhance medical care for patients of color.
 
For medical product development teams, expanding and diversifying product trial study populations may be one way to begin to overcome the computational biases that can lead to a decline in functionality for diverse patients.

Diversifying Data as Risk Management Tool

The more heterogeneous the population of research subjects and trial samples, the more certain product development teams can be of the utility, efficacy, and reliability of the product for all patient groups. Adopting an adaptive productive trial model provides opportunities for modifying product designs in response to the unique and particular needs of specific demographic groups.
 
This, in turn, can not only make the products more effective but also safer for vulnerable patient populations. To return to the example discussed above, inaccuracies in pulse oximeters can contribute to potentially life-threatening outcomes, as severe or prolonged oxygen deprivation is strongly associated with tissue damage and, over time, organ failure.
 
Impacted patients may experience serious wounds that do not heal due to systemic oxygen deprivation. They may have episodes of syncope which can result in catastrophic accidents and falls. They may even experience respiratory failure and cardiac arrest if the oximeter fails to detect a life-threatening decline in oxygen saturation.
 
For product development teams, the sometimes grave consequences of failing to account for significant and predictable variations in system functionality carry enormous moral as well as financial risk. These hazards may, indeed, put the entire business at risk, particularly if there is evidence that development teams did not pursue or effectively utilize the data needed to detect and mitigate potential risks to diverse product users.

The Takeaway

The concept of implicit bias is not an easy one to acknowledge or address. The reality, however, is that bias is far more prolific than many of us would care to imagine. Such implicit biases have even made their way into the development of medical products whose core purpose is to help and heal. Fortunately, though, it is possible to address and overcome implicit bias in medical product development. The key is recognition, acknowledgment, and proactive action.
 

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Amanda Winstead is a writer from the Portland area with a background in communications and a passion for telling stories. Along with writing she enjoys traveling, reading, working out, and going to concerts. If you want to follow her writing journey, or even just say hi you can find her on Twitter.