We speak often about the need to combine human and artificial intelligence (AI) to improve patient care. Equally important is the marriage of compassion and data analytics ― a powerful duo that is proving invaluable in the battle to eradicate the systemic racism that still permeates health care.
Unfortunately, numerous examples demonstrate that systemic racism continues to affect the patient experience and leads to mistrust of health care institutions among people of color.
Some of us are familiar with the unethical Tuskegee syphilis study, in which the U.S. Public Health Service observed a large population of African American men with untreated syphilis between 1932 and 1972. As part of that study, participants with syphilis were not informed of their diagnosis, nor treated for it. They were told they were receiving free health care from the federal government.
As another example of systemic racism in health care, a recent journal article in the Proceedings of the National Academy of Sciences of the United States of America revealed that among 1.8 million U.S. births, the Black newborn mortality rate was three times higher when white doctors delivered the child, compared to Black doctors.
Awareness of such prejudices causes fear of interacting with the health care system, as evidenced by a December 2020 survey by the Kaiser Family Foundation in which 35% of Black respondents said they definitely or probably would not get a COVID-19 vaccine.
The list of inequities associated with racism includes numerous other problems. Blacks have a lower average life expectancy and they are less likely to have been vaccinated, according to a 2015 review by the Department of Health and Human Services. A 2015 review by Paradies et al also found that racism was "associated with poorer mental health, including depression, anxiety, psychological stress and various other outcomes … and with poorer general health.
Since the Black Lives Matter movement came to prominence in the U.S., many health care leaders have spoken out to address these disparities. Mayo Clinic has likewise taken a strong position on the subject and has put skin in the game by investing in a 10-year, $100 million effort to eradicate racism in all its forms.
That effort will include initiatives to:
- Increase recruitment of researchers and clinical trial patients from underrepresented racial and ethnic groups.
- Find ways to recruit and retain physicians, nurses and supervisors from underrepresented groups.
- Build out its digital and telehealth technology to make patient care more equitable around the nation.
Mayo also is working on programs to increase its own patient population's diversity, with special attention paid to Black patients.
At the local level, Mayo recently awarded several grants to communities to advance racial equity. Specifically, its EverybodyIN Fund for Change has given grants to 36 organizations in Mayo Clinic communities, including 17 organizations in the regions Mayo Clinic Health system serves.
Mayo Clinic's core values are the springboard for these initiatives and programs. These values include respect for everyone in our diverse community, providing compassionate care with an emphasis on sensitivity and empathy, and integrity to the highest principles of professionalism.
Of course, Mayo realizes that values have to be accompanied by specific actions to have any lasting impact. In addition to the concrete actions mentioned above, we are completing the most extensive analysis of care disparities in the U.S. to guide our steps.
In conjunction with Change Healthcare's data scientists, Mayo is creating a novel national disparities road map using Change Healthcare's enormous amount of linked data containing social determinants of health and health care use. The data will enable us to identify geographic areas and patient populations to first target as we work to eliminate health care inequities. We aim to develop a series of specific health care delivery interventions, leveraging many of the digital tools that are now part of the Mayo Clinic Platform that can address patient-level factors and structural factors that have contributed to, and continue to contribute to, racism in medicine.
We also have created an AI playbook that provides the tools and techniques needed to select unbiased data sets. This playbook can be used to develop algorithms to measure the biases in machine learning-based algorithms being used to deliver health care.
As we have mentioned in previous articles and books, several of the digital tools being recommended as diagnostic and therapeutic aids do not represent the populations they attempt to serve, leaving out adequate numbers of persons of color and other minorities.
In our book, "The Transformative Power of Mobile Medicine," we speak at length about the power of words, pointing out that they can persuade skeptics, overcome bigotry, wound colleagues, disrupt the status quo, ruin reputations, shatter misconceptions, deceive the uninformed, endear us to loved ones, and comfort the grief stricken.
Compassion is one of those powerful words, especially when it's backed by the actions of clinicians, executives and technologists who put patients first, regardless of the color of their skin.