Unconscious bias leads to health disparities for patients, and has a negative effect on healthcare workers as well. Unconscious bias can cause both patients and staff to be treated differently based on gender, race, language spoken, lifestyle choices, and more. This results in higher staff attrition and and lower patient satisfaction—and in turn, it negatively effects healthcare organizations' bottom line.
This past week marked the 50th anniversary of Dr. Martin Luther King Jr.'s death. Dr. King famously said, "Of all the forms of inequality, injustice in health is the most shocking and inhumane." He said that in 1966. In 2018, the US still struggles with pervasive health inequality that weakens our overall healthcare system, and reduces our standing compared to other developed nations. The city of Atlanta, where Dr. King grew up and went to college, is a national healthcare hub, boasting world-class healthcare facilities. It is home to the Centers for Disease Control (CDC), the American Cancer Society, the Arthritis Foundation, and several schools of medicine and public health. But Atlanta also has some of the widest gaps in black and white health outcomes in the country. Among these disparities are:
Implicit bias, and especially the Implicit Association Test (IAT), has been the subject of recent debate in both scientific and popular press. Is the IAT accurate? Are its findings useful? Does the concept of implicit bias impede efforts to address explicit bias? A new piece in Scientific American argues that the controversy around implicit bias and the IAT is based on fundamental misunderstandings. For example, the IAT isn't designed to predict individual behavior, like how a particular physician will interact with a particular patient. Rather, the aggregate data can help predict (and correct) big-picture functions.
Trust in the healthcare system is at an all-time low—only 34% of Americans have “great confidence” in medical leaders, as compared to 73% in 1966. So if you are a health professional, you're wise to assume patient mistrust, rather than the other way around. Depending on your role and the setting, mistrust can present itself in very different ways. But I've learned that you can respond effectively to patient mistrust in any scenario using three simple communication techniques.
As reported in previous News Roundups, a lack of diversity in clinical trials results in disparities in care among under-served populations. Recruiting different racial and ethnic groups, especially African-Americans, remains a challenge. A focus-group study conducted by Louisiana State University Health Sciences Center sought to learn what it would take to address this problem. Results show that trust and communication are key to increasing minority participation in clinical trials.
The Tsimane people are an isolated tribe in Bolivia with a life-expectancy of only 50 years. Researchers from the Integrated Anthropological Sciences Unit at UC Santa Barbara published a paper analyzing why the Tsimane often refuse medical care, even when it's free and offered by people they trust. Their findings provide insights into why so many people around the world, regardless of background and education, resist going to the doctor even when they know they should.
Every moment, your brain processes incredible amounts of information. This processing allows you function: to make decisions and take actions. The majority of this goes on behind the scenes, a necessary efficiency that means you don’t have to “think” about most of your activity. For example, the minute calculations your brain makes to accomplish simple things, like walking across the room to open a door. Or more complicated things, like assessing a fellow human being.
In the United States, the recommended age for women to begin routine mammograms for cancer screening was recently increased to 50 years of age. This was based on a study of 747,763 mostly white women showing that breast cancer diagnoses peaked in their 60s. But researchers from Massachusetts General Hospital (MGH) have published a new study in JAMA Surgery that shows black, Hispanic, and Asian women tend to get breast cancer earlier than white women. A lack of data from racially diverse populations could put nonwhite women at risk for delayed diagnosis. According to David Chang, PhD, MBA, MPH, of the MGH department of surgery and an associate professor of surgery at Harvard Medical School, "The situation with breast cancer is one of the best examples of how science done without regard to racial differences can produce guidelines that would be ultimately harmful to minority patients."
Unconscious bias can lead to negative outcomes for disadvantage patient populations, even when that bias occurs behind-the-scenes in research settings. A new report from Data & Society identifies several ways that datasets can become biased, including historical bias, analytical bias, and access to different types of genetic data. “Bias through invisibility—such as lack of data on certain factors—can trigger discriminatory outcomes just as easily as explicitly problematic data,” note the authors.
The transgender population is underserved by the healthcare system, and one reason may be provider hesitancy. To meet the medical needs of transgender people, healthcare organizations, together with medical schools and residency programs, must incorporate training and content on how to care for transgender patients.
