HOW USERS PERCEIVE META-ANALYSIS OF ECONOMIC EVALUATIONS

Abstract

Background: Meta-analysis of economic evaluations (MAEE), particularly 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 practical utility of MAEEs. This study examined end users’ perceptions and applicability of MAEE findings in real-world decision-making. Methods: A 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 and experience with MAEEs, perceived usefulness, potential applications, and likelihood of future use. Responses were summarized using descriptive statistics, and associations between participant characteristics and perceptions were analysed using chi-square tests and odds ratios (95 percent CI). Results: A total of seventy-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 generally 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, policymakers, 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). Conclusion: MAEEs 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.