Breaking the Cycle of Health Inequities: The Bioethics of Data.

Social epigenomics measures the mechanisms through which place and context change our biology. Big data science connects, analyzes, and allows inferences from previously disconnected data. Precision medicine promises individually-tailored treatments. Together, these emerging fields are changing the way we discover, decipher, and deliver new science to populations. However, differential participation in and uptake (by adopter type-from innovators to laggards) of the discovering, deciphering, and delivering of these new mechanisms may exacerbate health disparities. Innovators and early adopters are generally from higher-resourced environments. This leads to data and findings biased towards those environments. Such biased data in turn continue to be used to generate new discoveries, further obscuring potentially underrepresented populations, and creating a nearly inescapable cycle of health inequity. We argue that equitable access to representative data is of special moral (bioethical) importance, necessary to break the cycle of health inequities.