Plain Language Summary

This report discusses the use of generative artificial intelligence (AI) in health technology assessment (HTA) and highlights its potential benefits and challenges. Generative AI, especially large language models, could significantly improve how evidence is generated for healthcare decisions. This overview is important because it addresses the growing need for efficient methodologies in assessing health technologies and provides insights into the application of advanced AI tools in this field.

The report identifies 3 main areas where generative AI can enhance HTA: conducting systematic literature reviews, analyzing real-world evidence, and developing health economic models. In literature reviews, generative AI can automate tasks like proposing search terms, screening abstracts, and extracting data. For real-world evidence, it can analyze large datasets, including unstructured clinical notes, improving data processing and accuracy. In health economic modeling, generative AI can assist in creating and validating models.

Despite these opportunities, the report also points out significant challenges. The use of generative AI is still in its early stages and  there are concerns about scientific accuracy, potential biases, and ethical implications like data privacy. AI-generated outputs may be unreliable, which necessitates human oversight in its application. The report emphasizes that while generative AI can support human efforts, it should not replace them entirely.

For healthcare decision makers, the findings highlight the need for clear guidelines on how to responsibly integrate generative AI into HTA processes. Policy makers are encouraged to collaborate with HTA agencies and develop standardized practices that ensure transparency in using AI technologies.

Researchers are urged to stay informed about the capabilities and limitations of generative AI tools as they evolve. Ongoing evaluation of their application in HTA is essential to ensure their responsible use and to enhance the quality of their assessments.

In summary, generative AI holds promise for transforming HTA by improving efficiency and accuracy in evidence generation. However, careful consideration of its limitations and the importance of human oversight are crucial as this technology continues to develop.

^{Note: This content was created with assistance from artificial intelligence (AI) and has been reviewed and edited by ISPOR staff. For more information or for inquiries on ISPOR’s AI policy, click here or contact us at info@ispor.org.}