The importance of Real World Evidence (RWE) in Health Technology Assessment (HTA) is increasing over time, as technological advances have given rise to innovative tools for collecting and recording information, and for generating and synthesizing evidence from a wide variety of settings in the real world, and oftentimes, even, in real time. Additionally, stakeholders have a better understanding of how access to innovative technologies can be facilitated and even accelerated. They are willing and even eager to consider the use of machine learning (ML) and artificial intelligence (AI) technologies to gain the advantage of more comprehensive evidence to inform decision-making.
The availability of big data (especially open data) and the new methods such a ML and AI provide unprecedented opportunities to combine data from different sources in a meaningful manner and to allow for assumptions to be explored in a detailed manner, incl. in the context of HTA.
The COVID 19 pandemic has made it quite impossible for us to have our Interest Group face to face annual business meeting this year. Nonetheless, we plan to use the online platforms to introduce and provide future plans for this interest group. This meeting will take roughly an hour.
Dr. Massoud Toussi, Pharmacoepidemiology and Drug Safety Lead, IQVIA (France)
Dimitra Lingri, Head of Legal Department, EOPYY (Greece)
Elena Petelos, Lecturer in Evidence Based Medicine, University of Crete / University of Maastricht (Netherlands)
Lorena Pozzo, Researcher, Institute of Energy and Nuclear Research (Brazil)
September 11, 2020 at 08:00 MDT (UTC -6)