Olli Saarela: Causal variance decompositions for polytomous and functional exposures
Olli Saarela (Dalla Lana School of Public Health, University of Toronto, CAN) will give a talk on September 24th at 14:15 in the Erling Sverdrups plass, Niels Henrik Abels hus, 8th floor.
Olli Saarela is an Associate Professor at the Biostatistics Division of the Dalla Lana School of Public Health, University of Toronto (CAN)
Title: Causal variance decompositions for polytomous and functional exposures
Abstract: Institutional/provider comparisons in healthcare can be considered as causal inference problems, answering questions of the type "What kind of care/outcome a patient would be expected to have if treated in a given hospital (in contrast to a reference hospital or a benchmark level of care)?". Since the treating hospital is considered here as a multi-category polytomous exposure, there will be a large number of such contrasts, motivating the question of how much of the overall variation in the patient outcomes is attributable to between-hospital differences in performance. For this purpose, we consider causal variance decompositions. In this talk, I will briefly review causal inference techniques used for institutional comparisons, including direct and indirect standardization. I will discuss the causal interpretation of a variance decomposition that splits the observed variation in the outcome to that due to between-hospital differences, due to patient case-mix, and residual variance. I will extend these ideas to hierarchical exposures (e.g. surgeons within hospitals), and causal mediation analysis. The methods are illustrated with applications to Ontario administrative data on cancer care. I will also discuss adapting the variance decomposition approach to functional exposures in a radiation treatment context, which requires dimension reduction techniques.
Download the flyer here.