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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)
Causal Effect Estimation in Observational Studies: Application of Missing Data Framework and Propensity Score Methods
Takahiro Hoshino, PhD
Keio University, Japan
Professor, Graduate School of Economics
Use of High Dimensional Propensity Score Approach in Claims-Based Pharmacoepidemiology Studies
Hiraku Kumamaru, DrSc, MD
The University of Tokyo Hosptial, Japan
Department of Healthcare Quality Assessment
Spatial Epidemiology: Risk Assessment of Spatio-Temporal Events
Kunihiko Takahashi, PhD
Nagoya University, Japan
Associate Professor, Department of Biostatistics, Graduate School of Medicine
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