Bridging the gap between statistical analysis and decision making in public health research

Statisticians have eagerly taken on the role of presenting statistical summaries of quantitative data. In areas of health, this means providing point and interval estimates for quantities of interest such as diagnostic risks and treatment effects or providing curve estimates for quantities of interest such as survival probabilities across time. Methods for providing such summaries are highly formalized and constantly evolving. While decision making is the incentive for nearly all such efforts, the process that transforms statistical summaries into decisions usually remains informal and ad hoc. Statisticians have not eagerly accepted the role of promoting formalized decision-theoretic techniques. This paper will argue that the gap between statistical synthesis and decision making is an unnatural and undesirable one, because it undermines the impact of quantitative information. An argument for bridging the gap by expanding the role of statisticians will be presented.