Real world evidence' (RWE) indicates an increasingly popular body of evidence typically collected in the post-marketing framework and, usually, under observational conditions.
Typical examples include population registries, cohort studies, or, more generally "electronic health records".
These are increasingly popular in the context of Health Technology Assessment (HTA), where RWE can be used to complement limited evidence from experimental studies, to provide a more comprehensive assessment of the "value for money" associated with new interventions.
Gianluca Baio is a Professor of Statistics and Health Economics in the Department of Statistical Science at University College London. He graduated in Statistics and Economics from the University of Florence (Italy) and completed his PhD programme in Applied Statistics at the University of Florence, after a period at the Program on the Pharmaceutical Industry at the MIT Sloan School of Management, Cambridge (USA). Since then, he is working as a Research Fellow and then Lecturer in the Department of Statistical Sciences at University College London (UK).
Gianluca leads the Statistics for Health Economic Evaluation research group within the department of Statistical Science. The activity revolves around the development and application of Bayesian statistical methodology for health economic evaluation, e.g. cost-effectiveness or cost-utility analysis. He works in close collaboration with academics both within UCL and at other institutions and our activities include a series of seminars aimed at statisticians, health economists and clinicians working in economic evaluations. Moreover, he collaborates with the UK National Institute for Health and Care Excellence (NICE) as a Scientific Advisor on Health Technology Appraisal projects. He is among the founding members of the R-HTA consortium and the ConVOI collaborative network.
Currently, Gianluca Baio is the Head of the UCL Department of Statistical Science.
Brad is a statistical researcher, methodologist, consultant, and instructor. Prior to joining PharmaLex, he spent 27 years on the faculty of the Division of Biostatistics at the University of Minnesota School of Public Health, serving as division head for 7 of those years. He has published more than 185 papers in refereed books and journals, and has co-authored three popular textbooks on Bayesian statistical methods and their applications in spatial statistics and adaptive clinical trials. During his spare time, Brad is a health musician and bandleader, providing keyboards and vocals in a variety of venues. He is excited and proud to be a part of the PharmaLex data science and statistics team.
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