Real World Evidence and Artificial Intelligence

Overview

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 use of RWE and AI has been discussed for the past few years in the context of dossier submission for new technologies to enter the market across geographies, with  draft guidance emerging across both sides of the Atlantic however, harmonization is needed on the methods and best practices to guide how high-quality RWE can be generated, how it can be incorporated and assessed in the context of HTA, and, indeed, in the overall context of improved resource allocation and improved access, including in the context of providing high quality healthcare services, and as captured in the sub-goal Sustainable Development Goal (SDG) for Universal Health Coverage (UHC) (SDG 3.8) of the United Nations.

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. AI is also used as stand-alone health technology itself or used in other technologies. In this context, we conducted a survey among the members of HTA to evaluate their interest for RWE-AI IG. Survey results showed that most respondents were supportive and interested in actively exploring these topics and collaborating in this IG.

In June 2020, the Society Board of Directors approved the motion to form the Real World Evidence and Artificial Intelligence Interest Group. This new group is one of ten HTAi Interest Groups formed of, and accessible to all HTAi members (Link to IG Overview Page). The Interest Groups are overseen and supported by the Interest Group Steering Committee (link to IGSC), an Advisory Committee to the Society Board of Directors.

Aims & Objectives

Goal: To provide a discussion forum where IG members can provide insights and make collective decisions about subjects related to the mission of the IG.

Activities: Enable the members to get into contact with each other and launch the topic of their interest within the framework of the IG mission, using mailing lists, LinkedIn groups or other methods.

The specific aims of the Interest Group are:

• To educate evidence developers and assessors, including practitioners, researchers and regulators, on how AI and ML are/will be used, on the RWE generation and utilization in the context of regulatory and HTA dossiers; to identify and engage people with interest and expertise in RWE, AI and HTA and to explore further use in collaborative projects, incl. to facilitate cross-border and interdisciplinary collaboration and identify early cases of best practice;
• To provide a discussion forum where IG members can provide insights, exchange ideas and make collective decisions about subjects related to the mission of the I so as to help the wider HTAi society, incl. other SIGs to better understand these concepts and to identify synergies, opportunities for cross-IGs collaboration and positioning, and, of course, to contribute towards the scientific development of members and the capacity building in relevant organization across the globe