In a world teeming with health data—from smart watch accelerometry to millions of hospital system electronic records—how do researchers find out which medical treatments truly work? Biostatistician Rebecca Hubbard discusses the messiness of real-world data, the limits of randomized controlled trials and how both of these powerful—but imperfect—methods are essential for building a trustworthy ‘edifice of evidence.’

In an era where the value of scientific research is increasingly undermined, Brown University public health scholars remain steadfast, showing how high-quality public health science protects people, shapes policy and transforms the health of our nation.

Anne-Marie Feeney is a data analyst at the Stanford Cancer Institute who is applying skills from Brown's new Online Master’s Degree in Biostatistics and Health Data Science to her cutting-edge work in CAR-T cell therapy.

Public health researchers untangle two decades of maternal mortality data and find that while early increases were driven by reporting changes, real increases followed during the COVID-19 pandemic.

An analysis by researchers at the Brown University School of Public Health found that most studies exclude participants who are pregnant, potentially leaving critical safety and efficacy questions unanswered.

I am pleased to share an important update that reflects our ongoing efforts within our school centers to remain focused on new and emerging trends in public health and the academic community at large.