In the first part of this series, we explored the transformative power of generative AI in Health Economics and Outcomes Research (HEOR) and Market Access (MA), highlighting practical applications and demonstrations from our recent workshop at Harvard. Now, let's dive deeper into the advanced AI skills discussed, the challenges identified, and the key takeaways that point toward the future of AI in our field.
The Health Economics and Outcomes Research (HEOR) and Market Access (MA) communities are increasingly under pressure to generate quick insights by assimilating vast amounts of information from multiple data sources, identifying evidence gaps, and developing strategic solutions. Time constraints are a significant challenge in this environment. Generative AI is already revolutionizing industries such as the computer software sector and has immense potential to drastically transform how we work in the HEOR and MA spaces.
At the recent ISPOR annual meeting in Atlanta, one of the most highly attended sessions, "Emerging Landscape of Health Economic Evaluation in the Era of Generative AI," captivated attendees with its forward-thinking discussion on the integration of generative AI in health economics.
Join Value Analytics Labs at ISPOR US from May 5-8, 2024. At ISPOR 2024, attendees will delve into the latest methodologies, data analytics, and evidence-based approaches that drive transformative changes in health and well-being. This year’s meeting is themed HEOR: A Transformative Force for Whole Health
What is clear is that more variants will emerge if people remain susceptible to catching COVID-19 in the first place, said Jagpreet Chhatwal, an assistant professor at Harvard Medical School.
In this joint interview feature, following their workshop delivered at the International Society for Pharmacoeconomics and Outcomes Research’s 2020 Asia Pacific meeting (Virtual ISPOR Asia Pacific 2020; 14–16 September), Turgay Ayer (Georgia Tech, GA, USA), Jag Chhatwal (Massachusetts General Hospital, MA, USA) and Selin Merdan (Value Analytics Lab, GA, USA) discuss the practicalities of applying machine learning (ML) in the real-world evidence and health economics and outcomes research (HEOR) fields.
©2024 Value Analytics Labs. All rights reserved | Terms of Service | Privacy Policy | Design by 9piksel
