A new approach known as “target trial emulation” is helping researchers evaluate health policies with the rigor of clinical trials, even when randomized studies are not possible. Typically used in other fields, this method is now being applied to assess the impact of policies that affect public health.
In a recent study published in the Annals of Internal Medicine, Nicholas Seewald, PhD, Assistant Professor of Biostatistics, and his colleagues outlined a framework with seven key components to simulate a randomized trial for policy evaluation. These components include the units and eligibility criteria, definitions of the exposure and comparison conditions, assignment mechanism, baseline (“time zero”) and follow-up, outcomes, causal estimand, and statistical analysis and assumptions.
By adopting this framework, scientists can produce more reliable estimates of how policies affect health outcomes, while also ensuring transparency in their methods. This approach can lead to more informed decisions in healthcare policy by improving the accuracy of nonexperimental studies.