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Applications of Structural Expert Elicitations for Economic Evaluations: A Systematic Review Update
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DOI：10.1007/s40273-026-01628-x.png)
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Abstract
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Structured expert elicitation (SEE) has become increasingly important in health technology assessment and economic evaluations. Complementing previous work, we aimed to synthesize recent developments in published SEE applications within health economics over the past 8 years. A systematic literature search was conducted in Medline and Embase databases from April 2017 to February 2026, supplemented with snowball sampling, to identify applications of SEE as part of economic evaluations. Data extraction and synthesis focused on expert selection, elicitation methods, and analytical techniques to identify commonalities and gaps. In total, 28 studies met the inclusion criteria. SEE applications covered diverse health interventions, from rare diseases treatments to diagnostic accuracy assessments. The number of experts recruited through purposive sampling varied from 1 to 18 clinicians per study. SEE processes remain bespoke and diverse, spanning from paper-based to software-assisted remote techniques. The studies used mainly variable and fixed interval methods (29% versus 67%) for encoding. Aggregation methods were mainly mathematical, with some studies using consensus approaches. Most studies (75%) directly incorporated pooled expert distributions into decision models. While SEE methods vary considerably across applications, suggesting that optimal approaches have yet to emerge, there is growing recognition of their potential for informing healthcare decision-making where empirical data are scarce, particularly in rare diseases and early-stage technology assessment. Future research should prioritize standardizing best practices, validating expert predictions against subsequently available empirical data, and developing enhanced bias mitigation strategies to improve the credibility of expert-informed health economic evaluations.
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