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[V7-S6] Mighty Epidemiology!
Session Chair(s)
Hisashi Urushihara, DrPH
Professor, Faculty of Pharmacy, Department of Pharmacy, Keio University, Japan
Postmarket observational epidemiological approaches have evolved into a powerful influence on the life cycle of medicinal products through use of various data sources, advanced statistical methodologies, and by globalization of pharmacovigilance activities. The missing data framework using propensity score introduced by Rubin, coupled with emerging “big health care data” from observational studies, has the potential to enable causal inference previously thought impossible to achieve except through randomized clinical trials. This session explores the possibilities and perspectives in the field of real-world medicines assessment introduced by these mighty epidemiological methods.
Speaker(s)
Takahiro Hoshino, PHD
Professor, Graduate School of Economics, Keio University, Japan
Causal Effect Estimation in Observational Studies: Application of Missing Data Framework and Propensity Score Methods
Hiraku Kumamaru, DRSC, MD
Department of Healthcare Quality Assessment, The University of Tokyo Hosptial, Japan
Use of High Dimensional Propensity Score Approach in Claims-Based Pharmacoepidemiology Studies
Kunihiko Takahashi, PHD
Associate Professor, Department of Biostatistics, Graduate School of Medicine, Nagoya University, Japan
Spatial Epidemiology: Risk Assessment of Spatio-Temporal Events
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