Applications of Structural Expert Elicitations for Economic Evaluations: A Systematic Review Update.

Area of Science:

• Health Economics
• Health Technology Assessment
• Decision Science

Background:

• Structured expert elicitation (SEE) is increasingly vital for health technology assessment and economic evaluations.
• This study synthesizes recent developments in SEE applications within health economics over the past eight years.

Purpose of the Study:

• To systematically review and synthesize recent advancements in structured expert elicitation (SEE) applications in health economics.
• To identify commonalities, gaps, and best practices in expert selection, elicitation methods, and analytical techniques.

Main Methods:

• Systematic literature search of Medline and Embase (April 2017–February 2026) supplemented by snowball sampling.
• Data extraction and synthesis focused on expert recruitment, elicitation techniques, and data aggregation methods.
• Analysis of 28 studies applying SEE in diverse health economic evaluations.

Main Results:

• SEE applications spanned various health interventions, including rare diseases and diagnostic accuracy.
• Expert numbers ranged from 1 to 18 clinicians; elicitation processes were diverse, from paper-based to software-assisted.
• Most studies (75%) incorporated expert data into decision models, primarily using mathematical aggregation.

Conclusions:

• SEE methods show considerable variation, indicating a need for standardized best practices.
• SEE is recognized for informing decisions with scarce data, especially for rare diseases and early-stage technologies.
• Future research should focus on standardization, validation against empirical data, and bias mitigation strategies.