Abstract

While artificial intelligence (AI) has been part of the health economics and outcomes research (HEOR) toolkit for years in the form of predictive models and machine learning algorithms, the recent surge of generative AI (GenAI) has created a new wave of excitement. GenAI is moving at lightning speed. In the time it takes to conceive, draft, and submit a paper on use of AI in HEOR, the underlying AI tools will have already evolved or been replaced. For researchers in our field, this precipitous pace presents exhilarating opportunities but also many challenges and concerns. The creation of health economic models is being reimagined, evidence synthesis is being automated, and many other tasks are being reshaped—often before we have had time to understand and validate the latest breakthrough.

This themed section explores this dynamic intersection of GenAI and HEOR, spotlighting how these technologies are not just enhancing existing methodologies but redefining them entirely. Reflecting the topic’s maturity, 5 of the papers are about the use of GenAI to aid literature reviews; one is about automating adaptations to health economic models and another about generating synthetic patient data. Finally, there is a paper about public preferences regarding AI in mobile health applications. Although not formally part of the special section, the ISPOR Working Group on Generative AI published 3 papers that address the need for taxonomy and terminology, provide an overview of the field, and propose reporting guidelines. Of note, none of the papers that could have applied the criteria in the latter would have fully met them. The contributions in this issue provide a window into a field in flux, where innovation is constant, and catching up is part of our job description.

There are common themes across these papers. GenAI can assist humans by automating workflow, taking care of boring repetitive tasks, and minimizing error, thereby reducing labor and accelerating production. Just the same, concerns remain: accuracy, credibility, and transparency are often discussed, as is the need for standards.