Reimagining HEOR Workflows: Combining Human Expertise, Traditional Automation, and Generative AI

This microcourse was developed in collaboration with experts from OPEN Health, an ISPOR Mission Partner organization.

This course provides a structured, HEOR-specific framework for modernizing research and analytical workflows through hybrid execution models that combine human expertise, traditional automation, and generative AI. Participants will learn how to deconstruct HEOR activities into roles, workflows, and task-level components and assess which mode of execution is most appropriate based on attributes such as input structure, rule rigidity, verification cost, and error tolerance. Using practical examples such as survival analysis and model development, the course demonstrates how hybrid toolchains can enhance precision, reproducibility, and speed while maintaining scientific rigor and governance.

After the completion of this course participants will be able to:

• Describe how HEOR work can be structured from roles to workflows to task-level execution.
• Identify opportunities to apply human expertise, traditional automation, and generative AI within HEOR workflows.
• Evaluate tasks using key attributes including input and output structure, rule rigidity, error tolerance, and verification cost.
• Apply a task-level approach to common HEOR activities such as survival analysis and economic modeling workflows.
• Integrate hybrid execution modes into practical, reproducible toolchains using structured, API-driven approaches.
• Explain how hybrid workflows can improve efficiency and organizational capacity while maintaining scientific integrity.

LEVEL: Introductory TRACK: Methodological & Statistical Research HEOR Competency: 10.3 Artificial Intelligence (AI) and Machine Learning (ML) HEOR Competencies: A resource for HEOR Professionals

The access period once enrolled into the course is 30 days from the date of purchase. After this duration, you will need to re-enroll if you wish to re-enter the course.

Time to complete – approximately 1 hour