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How users perceive meta-analysis of economic evaluations
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DOI：10.1017/S0266462326103742.png)
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Abstract
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ObjectivesMeta-analysis of economic evaluations (MAEEs); using the incremental net benefit approach; enables quantitative synthesis of cost-effectiveness evidence and may support policy decisions. However; little is known about users’ perceptions or utility of MAEEs. This study examined end users’ perceptions and applicability of MAEE findings in real-world decision-making.MethodsA cross-sectional online survey was conducted among individuals attending an ISPOR Real-World Evidence Summit 2025 breakout session on MAEEs. The survey collected data on respondent characteristics; prior awareness of and experience with MAEEs; perceived usefulness; potential applications; and the likelihood of future use. Responses were summarized using descriptive statistics; and associations between participant characteristics and perceptions were analyzed using chi-square tests and odds ratios (95 percent confidence interval).ResultsSeventy-six participants completed the survey. Most respondents were from the WHO South-East Asia Region (72 percent) and represented Industry/Pharma/MedTech (36 percent) or Academia/Research (34 percent). Perceptions were positive: 78 percent considered MAEEs “definitely” or “possibly” beneficial; and 55 percent indicated they would likely or very likely use MAEEs in policymaking. MAEEs were perceived as useful for highlighting variation across studies; reducing single-study bias; and improving precision when multiple EEs exist on the same topic within a country. Potential users included national health authorities; policy makers; hospitals/insurers; and countries with limited EE capacity. No significant associations were observed between respondent characteristics and perceived benefits or likelihood of use (p > 0.05).ConclusionsMAEEs are well-received by participants. Larger surveys and qualitative studies are needed to explore context-specific applicability; refine methodology; and enhance their utility across diverse settings.
Keywords:
economic evaluation
incremental net benefit
meta-analysis
cross-sectional survey
cost-effective analysis
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