Large-scale randomized controlled trials (RCTs) could help uncover subtle but important population-wide effects that smaller studies might miss. While observational studies currently dominate research on topics like environmental exposures or public health interventions, they often struggle with confounding factors. A dedicated funding mechanism for very large RCTs might provide clearer answers about causal relationships that affect millions.

How Large-Scale RCTs Could Work

One approach could focus on studies with hundreds of thousands or even millions of participants, targeting areas where small effect sizes could have big population impacts. Existing infrastructure like electronic health records or national registries might help reduce costs, while digital platforms could assist with participant recruitment. The studies could prioritize questions where:

• Small differences matter at scale (like dietary impacts on chronic disease)
• Randomization is difficult in smaller studies (like environmental exposures)
• Current evidence relies heavily on observational data

Potential Implementation Strategy

A phased approach might start with building a consortium of research institutions to develop priority-setting methods and secure initial funding. Pilot projects in high-impact areas could test the model before scaling up. For example, an MVP might focus on one clear priority area like mental health interventions, using existing cohort studies with added randomization elements.

Addressing Key Challenges

Ethical concerns about large-scale randomization might be addressed by focusing on interventions where genuine uncertainty exists about benefits versus harms. Cost challenges could be mitigated through digital data collection methods and cluster randomization designs that reduce individual burdens. Maintaining intervention consistency across large populations might require building some variability into the study designs from the outset.

While governments and institutions already fund some large studies, systematically applying this approach across multiple domains could fill an important gap between traditional RCTs and observational research. The resulting evidence could help policymakers, healthcare systems, and ultimately the general public make better-informed decisions about health and environmental risks.