Seminar: "How statistical theory shapes health policy"

Petros Pechlivanoglou, University of Toronto

Title: How statistical theory shapes health policy

Abstract:

This seminar will provide an overview of the impact statistics had to this date on the field of health policy with a particular focus on health technology assessment (HTA). Starting from a loose theoretical ground, HTA relies on a practical mix of economic/decision theory and statistical methodology to inform policy decisions around healthcare resource allocation and the reimbursement of new technologies. HTAs require the systematic synthesis of evidence from various sources (retrospective data, expert opinion, literature, randomized clinical trials) to inform predictions and quantify uncertainty around the impact a technology might have on long-term (often lifelong) outcomes of a population. To achieve that, the field of HTA relies on a combination of statistical methods from the fields of regression analysis, survival analysis, causal inference, simulation modeling and (Bayesian) hierarchical modeling. During the lecture I will illustrate the impact statistics had in the field through real-world policy making examples but also highlight contributions to the field of causal inference and survival analysis that in part originated from this HTA-statistics symbiosis.

Room Τ102, New AUEB Building