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What Is Bias, and How Can It Affect Patient Care?

Bias – particularly cognitive bias – can be perceived as an algorithm of the mind. It’s a systematic pattern of deviation from norm or rationality in judgment and implies an unreasoned and unfair distortion in favor of or against a person or thing. This essay provides an overview of bias, elucidates the different types of bias, and discusses the potential consequences – and opportunities – bias creates the medical field. 

One can distinguish two categories of bias: Conscious bias, where people hold explicit beliefs about other groups, manifesting in e.g. racism, sexism, Islamophobia – and unconscious bias.

As a cognitive skill, based on a simplified information processing strategy called heuristics, unconscious bias is supposed to help us evaluate information according to how we perceive these through the lens of our values and beliefs, and enable swift judgments and decisions. It however can lead to perceptual distortion, inaccurate judgment, illogical interpretation, and irrationality.

Cognitive biases, such as the availability and affective bias also often cause misdiagnoses, as they cause clinicians to focus on the patient’s initial impressions. 

There are numerous variations of cognitive bias – consequently – no individual is immune to the effects of it. In the realm of healthcare, this can lead to medical personnel unwittingly fueling healthcare disparities, which often leads to patient discomfort or even wrong treatment decisions.

Dr. Lucille Perez, an alumna at the NYMC, was an attending physician at Gouverneur Hospital in Manhattan. She had to treat people with lots of dissimilar cultures and backgrounds. Through this, over time she noticed how she unconsciously practiced racism towards African American people. Dr. Perez worked on changing her behavior, as she felt that this way, she can become a better doctor. 

A report from the National Academy of Medicine (NAM) demonstrates that “racial and ethnic minorities receive lower-quality health care than white people – even when insurance status, income, age, and severity of conditions are comparable “. Another study of 400 hospitals in the US indicates, how certain patient groups acquire cheaper and more conservative treatments than others do.

A good example for social bias is the fact that gendered norms are also often consolidated by hegemonic masculinity and andronormativity which results in men ending up getting more feeble pain treatments than they require, which basically manifests in the clichés humans create. 

With each generation they get passed on and extended, resulting in traditional and unfair treatment in our present time. Furthermore, utilization of artificial intelligence and “big data”, that cannot create its own opinion, has the potential to become a powerful tool for medical staff. To mitigate the risk of using generative AI as the data that is being processed in their learning models might already be biased, these models would however have to be closely monitored and continuously enhanced. 

To summarize, bias in patient care is an avoidable obstacle and there are various ways to circumvent it through a multifaceted approach, dedicated resources, and objective data, supported by training employees, recruiting from diverse backgrounds as well as application of AI. All this enables and fosters unbiased, individually optimized – however objective – and by that the best possible treatment and care.

References

Anurag Gupta „What Is Bias, and What Can Medical Professionals Do to Address It?“ IHI (Institute for Healthcare Improvement) 06/30/2017 #

Merriam-Webster Dictionary „Bias“ August 13, 2023 3 Vincent Berthet „The Impact of Cognitive Biases on Professionals’ Decision-Making: A Review of Four Occupational Areas“ frontiers January 4, 2021 

Kahneman D, Tversky A (1972). “Subjective probability: A judgment of representativeness”(PDF). Cognitive Psychology. 3 (3): 430– 454. doi:10.1016/0010-0285(72)90016-3. Archived from the original (PDF) on 2019-12-14. Retrieved 2017-04-01.

Rebecca Featherston, Laura E. Downie, Adam P. Vogel, Karyn L. Galvin “Decision making biases in the allied health professions: A systematic scoping review” 2020 Oct 20.

Chapman, E. N., Kaatz, A., & Carnes, M. Physicians and implicit bias: how doctors may unwittingly perpetuate health care disparities. *Journal of General Internal Medicine*, 28(11), 1504-1510. (2013)

Institute of Medicine; Board on Health Sciences Policy; Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care; Brian D. Smedley, Adrienne Y. Stith, and Alan R. Nelson, Editors „Unequal Treatment“ 2003 

Zheng, Nan Tracy Ph.D.*; Mukamel, Dana B. Ph.D.; Caprio, Thomas MD‡; Cai, Shubing Ph.D.;Helena Temkin-Greener, Ph.D. „Racial Disparities in In-Hospital Death and Hospice Use Among Nursing Home Residents at the End-of-life“ November 2011

 Anke Samulowitz et al. Pain Res Manag. “Brave Men” and “Emotional Women”: A Theory-Guided Literature Review on Gender Bias in Health Care and Gendered Norms Towards Patients with Chronic Pain 2018

Genevieve Smith and Ishita Rustagi, Berkeley Haas Center for Equity, Gender, and Leadership „Mitigating Bias in Artificial Intelligence: An Equity Fluent Leadership Playbook“ July 2020 

11Elizabeth C. Tippett Harvard Business Review „10 Ways to Mitigate Bias in Your Company’s Decision Making“ October 21, 2019

Anke Samulowitz et al. Pain Res Manag. “Brave Men” and “Emotional Women”: A Theory Guided Literature Review on Gender Bias in Health Care and Gendered Norms towards Patients with Chronic Pain 2018 https://pubmed.ncbi.nlm.nih.gov/29682130/ 

Anurag Gupta „What Is Bias, and What Can Medical Professionals Do to Address It?“ IHI (Institute for Healthcare Improvement) 06/30/2017 https://www.ihi.org/education/IHIOpenSchool/resources/Pages/AudioandVideo/AnuragGupta-What-Is-Bias,-and-What-Can-Medical-Professionals-Do-to-Address-It.aspx 

Elizabeth N. Chapman, MD, Anna Kaatz, MA, MPH, PhD, and Molly Carnes, MD, MS. Physicians and Implicit Bias: How Doctors May Unwittingly Perpetuate Health Care Disparities. *Journal of General Internal Medicine*, 28(11), 1504-1510. (2013) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3797360/ 

Elizabeth C. Tippett Harvard Business Review „10 Ways to Mitigate Bias in Your Company’s Decision Making“ October 21, 2019 https://hbr.org/2019/10/10-ways-to-mitigatebias-in-your-companys-decision-making 

Genevieve Smith and Ishita Rustagi, Berkeley Haas Center for Equity, Gender and Leadership „Mitigating Bias in Artificial Intelligence: An Equity Fluent Leadership Playbook“ July 2020 https://haas.berkeley.edu/wpcontent/uploads/UCB_Playbook_R10_V2_spreads2.pdf 

Institute of Medicine; Board on Health Sciences Policy; Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care; Brian D. Smedley, Adrienne Y. Stith, and Alan R. Nelson, Editors „Unequal Treatment“ 2003 https://pubmed.ncbi.nlm.nih.gov/25032386/ 

Rebecca Featherston, Laura E. Downie, Adam P. Vogel, Karyn L. Galvin “Decision making biases in the allied health professions: A systematic scoping review” 2020 Oct 20. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575084/ 

Kahneman D, Tversky A (1972). “Subjective probability: A judgment of representativeness”(PDF). Cognitive Psychology. 3 (3): 430–454. doi:10.1016/0010- 0285(72)90016-3. Archived from the original (PDF) on 2019-12-14. Retrieved 2017-04-01. https://en.wikipedia.org/wiki/Cognitive_bias 

Merriam-Webster Dictionary „Bias“ August 13, 2023 https://www.merriamwebster.com/dictionary/bias 

Vincent Berthet „The Impact of Cognitive Biases on Professionals` Decision-Making: A Review of Four Occupational Areas“ frontiers January 4, 2021 https://pubmed.ncbi.nlm.nih.gov/35058862/

Zheng, Nan Tracy PhD* ; Mukamel, Dana B. PhD† ; Caprio, Thomas MD‡ ; Cai, Shubing PhD§; Helena Temkin-Greener, PhD „Racial Disparities in In-Hospital Death and Hospice Use Among Nursing Home Residents at the End-of-life“ November 2011 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3215761/

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