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Precision medicine is built on a platform of big data, or large data bases that permit analysis of correlations among environmental and personal factors, treatments, and health outcomes.

Data bases that once included only paper records now include tissue samples, air and water samples, and more. There's vast potential for significant advances in health care from precision medicine.

But existing large data bases tend to be drawn almost entirely from European and Asian populations, limiting the reach of the benefits of precision medicine. Since big data analytics are often hidden from the patient (and sometimes even the clinician), non-representative data also contributes to mistrust in a health care system that has a long history of excluding certain people.

Kayte Spector-Bagdady from the Center for Bioethics and Social Sciences in Medicine from the University of Michigan Medical School joins Health Affairs Editor-in-Chief Alan Weil on A Health Podyssey to discuss the representativeness of data banks and what to do about it.

Spector-Bagdady and coauthors published a paper in the December 2021 issue of Health Affairs examining the lack of racial and ethnic diversity in data bank recruitment and enrollment at Michigan Medicine, a major academic medical center.

They found failures of representation were in part due to recruitment practices and in part due to the disproportionate rate at which black, Asian, and Hispanic patients declined enrollment when offered, relative to non-Hispanic white patients.

If you enjoy this interview, order the December 2021 Health Affairs issue.

Pre-order the February 2022 Racism and Health issue.

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