Structural racism – a root cause of health inequities?

Photo by Markus Spiske on Unsplash

We have all heard how cancer outcomes are poorer for people in low socioeconomic groups and those from ethnic minority backgrounds. Although I knew that the reasons behind this were multifaceted, I had bought into the idea that delayed help seeking behaviour was the main cause. Until that is, I became familiar with structural racism. To mark Black History month in this post I discuss how implicit biases feed into health inequalities.

What is structural racism?

It refers to the ways in which historical and contemporary racial inequities in outcomes are perpetuated by social, economic, and political systems, including mutually reinforcing systems of health care, education, housing, employment, the media, and criminal justice. It results in systemic variation in opportunity according to race or ethnic background — for example, ethnic variation in access to health care.

Health research is concerned with concepts that can be measured (e.g. screening uptake, cancer diagnoses). Structural racism challenges these established concepts by opening up health inequality beyond the individual patients behavioural and biological determinants of health.

Are implicit biases ingrained within health systems?

The greatest ethnic inequalities exist for treatable cancers because there is greater discretion both for the health professionals and for the patient to choose which therapeutic option(s) to endorse. This leads to more opportunity for explicit preferences and implicit bias (an instant, unconscious and reflexive reaction) to play a role in medical decisions For example, a physician may decide not to promote a treatment that requires multiple visits because she/he feels patients are less likely to attend for follow-up. Such a decision may well be influenced by the ethnicity of the patient, even if this is at an implicit level. There is also evidence that patients from minority backgrounds are less likely to be invited to participate in clinical trials limiting their access to cutting edge treatments.

I found the following example taken from the American health system to be particularly illustrative:

A 60-year-old, African American woman in Chicago with no health insurance attends a community hospital with a painful breast lump. Her previous mammograms were normal, so the attending physician suspects an infection and prescribes antibiotics. When the lump remains, a screening mammogram suggested breast cancer, a general surgeon removed the lump (with an excisional biopsy) and suggests a mastectomy. The patient was not referred to an oncologist nor told the stage or type of her breast cancer.

Not only did the procedures she received deviate from standard – the mammogram should have been diagnostic, then a needle biopsy and most shockingly there was no indication for a mastectomy – but the patient was not given the opportunity to fully consider her treatment options.

Because of the way the NHS is structured such a situation may not so evidently occur, but there is evidence from a UK setting that general practitioner are less likely to initiate lung cancer investigations for black than white patients.

Further, research by Laura Marlow, behavioural scientist and expert in inequalities in screening, shows that some women from ethnic minority backgrounds (2.5-12% depending on ethnicity) felt they had been unfairly treated by a health professional as a result of their ethnicity. Her research also provides evidence that women from ethnic minority backgrounds are more likely to prefer a recommendation to be screened (rather than weighing up the pros and cons themselves). In her view, it’s important to acknowledge and educate physicians to be aware of implicit bias, but also to empower patients from ethnic minority backgrounds, especially if they come from countries where there are more authoritative models of medical practice.

We can all start by acknowledging it exists

Health professionals should be aware of implicit bias (and not only when recruiting staff!). A good first step to addressing these issues is to change the accepted narrative by educating the wider community to understand that implicit bias may be contributing to ethnic inequalities, leading to variations in care delivery. Structural racism and implicit biases may explain some of the differences in survival outcomes by ethnicity, but probably not all of it.

Implicit bias can’t be limited to cancer, it must affect every single interaction with health workers and systems. The first step is to pull back the curtain and acknowledge what’s there.

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