"Precision medicine" is a growing field that aims to use 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 government’s $215 million dollar Precision Medicine Initiative, as well as industry-led efforts to collect and analyze volumes of health data.
report | 02.26.18
Fairness in Precision Medicine is the first report to deeply examine the potential for biased and discriminatory outcomes in the emerging field of precision medicine; “the effort to collect, integrate and analyze multiple sources of data in order to develop individualized insights about health and disease.”
This project aims to move past the rhetorics of promise in precision medicine to critically assess the potential for bias and discrimination in health data collection, sharing, and interpretation. To that end, this project will map the network of stakeholders in precision medicine, including researchers, health care providers, clinicians, and data analysts. The project will also identify 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.
The Fairness in Precision Medicine project will develop a framework for understanding trade-offs involved in precision medicine, and will raise challenges that may trigger conflicting commitments. The goal is to articulate salient gaps and blind spots in order to guide precision medicine initiatives at a critical time in their development.
Dr. Kadija Ferryman is a cultural anthropologist whose research examines how cultural and moral values are embedded in digital health information, social and biological influences on health, and the ethics of translational and digital health research. She earned a BA in Anthropology from Yale University and a PhD in Anthropology from The New School for Social Research. Before completing her PhD, she was a policy researcher at the Urban Institute where she studied how housing and neighborhoods impact well-being, specifically the effects of public housing redevelopment on children, families, and older adults. She has published research in journals such as Journal of Health Care for the Poor and Underserved, European Journal of Human Genetics, and Genetics in Medicine. She is currently a Postdoctoral Scholar at the Data & Society Research Institute.
Mikaela Pitcan is a social scientist and mental health clinician. Her areas of research include the impact of technology on learning, the ways in which technological systems impact decision-making and influence the connection between prejudice and discriminatory behavior. Mikaela also explores the impact of racially discriminatory experiences on individuals within the workplace as well as institutions of higher learning. She works to interpret technology's influence through a psychological lens and create avenues of communication between researchers, product developers, and educators. She holds a BS in psychology from the University of Florida, a MS.Ed in Mental Health Counseling from Fordham University Graduate School of Education and is currently a doctoral candidate in Counseling Psychology at Fordham University