Assessing a structured, quantitative health outcomes approach to drug risk-benefit analysis

Regulatory authorities make difficult risk-benefit decisions when approving new drugs. Food and Drug Administration (FDA) advisory committees and reviewers must consider a complex body of evidence, including efficacy and safety results of trials, disease epidemiology, potential side effects, and patients' needs. However, this menu of information is not usually presented in a consistent and integrated framework. The members of an FDA review panel vote with some unobserved, implicit weighting of the evidence. This paper argues that outcomes research tools for modeling long-term health outcomes, measuring health preferences, and establishing the value of additional information could provide a more structured, transparent, and quantitative process of assessing risk-benefit balance.