CLN Article
ADLM celebrates the contributions that scientists from underrepresented and minoritized communities have made and continue to make to the field, and the organization has established in its strategic plan a commitment to equity in access to high quality healthcare.
We spoke with Octavia Peck Palmer, PhD, FADLM, the immediate past president of ADLM and division director of clinical chemistry at the University of Pittsburgh School of Medicine. Peck Palmer is ADLM’s first Black woman president. She shared insights into the challenges clinical laboratorians are facing today and why ADLM members remain committed to serving the entire community.
She explained how this is especially critical at a time when machine learning and artificial intelligence (AI) are advancing discovery and treatment. And she warned that if these models fail to encompass the full spectrum of patient diversity, they risk leaving some behind.
The ADLM Board of Directors and our membership have been courageous in acknowledging that the communities we serve, both professionally and clinically, are experiencing a range of inequities that prevent our mission of “Better health for all” from being a reality.
ADLM’s posture has been to “unlearn what we have learned to be the standard even if it makes us uncomfortable” and seek to innovate, create, and cultivate a culture and field that is focused on delivering educational tools, mentorship, and opportunities to its members and collaborators that are truly inclusive.
The organization also has not shied away from understanding and learning how the concepts and principles of health equity, diversity, equity, and inclusion are correlated with success. According to a McKinsey & Company report, high levels of these principles at work are strongly correlated with higher earnings, more innovation, and a sense of value among employees.
I hope that my leadership inspires our field to continue valuing and caring for each human, without stereotypes, biases, or societal pressures. When we seek to ensure adequate representation, we demonstrate that all voices can be prioritized.
We must continue to make health equity a goal, or medicine will take several steps backward, and a generation of individuals will not receive the attention and healthcare they need and deserve.
It’s not good for our economy for people to be sick. The health of the economy depends on the health of individuals. Everyone should have the ability to obtain healthcare.
We all have different life experiences that shape the way we see and interact in the world.
Leaders from diverse backgrounds provide cultural insights that can aid in developing appropriate patient care models. We must understand how people are experiencing life to meet their healthcare needs.
Social determinants of health impact one’s health and well-being. A patient may live in a food desert and thus experience deficiencies in key nutrients, or they may live in a neighborhood that has low air quality which increases their risk of respiratory problems and cancer.
Communities are comprised of individuals with varying degrees of health literacy, representing different genders, ages, and pregnancy statuses, living in diverse geographical areas—urban and rural—with varying health needs.
As early as elementary school, I saw women leaders who inspired me within my own family.
Three specifically are my mother, Mary Frances who taught high school for 40 years making an impact on hundreds of faculty and students and empowering them with critical thinking skills in addition to knowledge; my Grandmother Frances Carol an industry worker and certified nursing assistant who poured into the economy and cared for others; and my great-grandmother, who is also named Mary, a childcare provider who was instrumental in the early development of many young children.
Each of these women lived during the Jim Crow era and segregation and experienced firsthand the laws and institutions that labeled them as second-class citizens and limited their access to quality healthcare.
Despite these hardships, they were successful in leading their marriages, families, and their respective careers, and they gave back to the community. They exhibited a mantra of “I can do anything despite the outside environments and when I succeed, those around me will succeed also.”
Also, I have had the privilege to be mentored externally by impactful women leaders, including Dr. Ann Gronowski, past President of ADLM, Oree M. Carroll and Lillian B. Ladenson Professor in Clinical Chemistry, co-chief in the division of laboratory & genomic medicine, and professor of pathology, immunology and obstetrics & gynecology at Washington University School of Medicine in St. Louis, Missouri.
Dr. Gronowski has been instrumental in my life: from training me during my clinical chemistry fellowship to helping me successfully navigate academia, reminding me of and providing me with tools to prioritize my wellness, and advising me on how to be wise in developing collaborations.
Dr. Esa Davis, Senior Associate Dean for Population and Community Medicine and Professor at the University of Maryland School of Medicine has also mentored me on how to navigate academia as a translational researcher with a clinical appointment, emotional intelligence, how to communicate effectively and foster idea uptake.
Dr. Davis motivates me in all that I do. I am blessed by the people who continue to care about me on a personal level throughout my life and career.
Interrogation of clinical lab-generated patient data and artificial intelligence (e.g., machine learning) are two emerging trends that have the potential to ensure health equity – increasing diagnostic accuracy, quantifying disease risks, identifying patient healthcare gaps, and determining medications that will be effective for patients.
On the other hand, artificial intelligence can also be detrimental and exacerbate health disparities in diseases.
Clinical care models that are developed and trained on non-diverse patient data can be biased and lead to differential access to healthcare services, delayed diagnoses, and delivery of life-saving therapeutics thus disproportionately affecting medically underrepresented populations.
Non-diverse datasets are missing populations from different geographical areas, diseases (e.g., rare vs. common diseases or disease variants), genders, and ethnicities/races to capture the impact of social determinants on health.
Clinical laboratories and hospitals must understand and prioritize the health needs of the communities they are serving — or that they think they're serving.
That second part is important because one-size-fits-all healthcare is inappropriate.
Clinical laboratories and hospitals can query their clinical lab data/hospital census to who they are delivering care to and the healthcare gaps.
They can ask questions such as are certain patients not receiving appropriate testing despite their clinical symptoms warranting specific tests? Are patients returning promptly for follow-up testing? Should the clinical laboratory offer accessible testing such as point-of-care testing (e.g., clinics or home) or in-home specimen collections? Does the clinical laboratory offer consultation for physicians and patients to help them understand clinical testing and interpret the results?