Event Details

Rebecca Hubbard, Ph.D., Brown University

Not So Fast: Accelerating Medical Research with Big Data while Safeguarding Vulnerable Populations and Research Rigor

Using data generated as a by-product of digital interactions to improve health and healthcare is a rapidly expanding medical research frontier. Big healthcare databases including electronic health records and health insurance claims offer the opportunity to accelerate evidence generation, decrease research cost, and study interventions and populations that have previously been difficult or impossible to access. However, because healthcare data are generated as a direct consequence of patient interactions with the healthcare system, data tend to be more extensive and of higher quality for patients with more healthcare utilization. This connection between patterns of healthcare utilization and data quantity and quality is particularly problematic for historically marginalized populations and other groups experiencing barriers to accessing healthcare. Limited data availability has the potential to increase bias, imprecision and algorithmic unfairness in healthcare data-based research. In this talk, I will discuss the role of big healthcare data in recent clinical and health policy decision-making, sources of bias in these analyses, and the potential for rigorous methodology to overcome these biases and protect vulnerable populations. Employing approaches to ensuring the rigor of research based on big data is an ethical imperative and key to safeguarding fairness and validity of the scientific evidence-base.