“Precision medicine” is a growing field that uses multiple data sources to tailor medical care to individuals. From incorporating genetic information, to using data from electronic medical records, precision medicine has the potential to transform healthcare and medical research. Precision medicine has strong support in multiple sectors, including the U.S. government’s $215 million dollar Precision Medicine Initiative, as well as industry-led efforts to collect and analyze volumes of health data.

Fairness in Precision Medicine at Data & Society moves past the rhetorics of promise in precision medicine to critically assess the potential for bias and discrimination in health data collection, sharing, and interpretation. This project maps the network of stakeholders in precision medicine, including researchers, health care providers, clinicians, and data analysts. The project also identifies vulnerabilities in the ecosystem that could lead to discriminatory outcomes, whether they might emerge as a by-product of implicit and explicit values, data quality, algorithmic models, or organizational decision-making.

We offer a framework for understanding trade-offs involved in precision medicine in order to raise challenges that may trigger conflicting commitments. We hope to articulate salient gaps in order to guide precision medicine initiatives at a critical time in their development.

Support for this research was provided by the Robert Wood Johnson Foundation. The views expressed here do not necessarily reflect the views of the Foundation.