Does meta-analysis of economic evaluations have the potential to play a role in healthcare decision-making in the United States?

Abstract

The current use of economic evidence in the decision-making process in the US is increasing. Meta-analysis of economic evaluations (MAEE) has gained recognition in recent years and can support decision-making at the global level or for countries with resource constraints. The focus of this article is to demonstrate how MAEE may contribute to the decision-making process in the US healthcare system. We demonstrated that MAEE can provide an efficient mechanism to quantitatively summarize cost-effectiveness findings based on all existing studies from the US answering the same question across different assumptions. This sort of evidence is important for US policymakers to support policy decision-making. MAEE methods can streamline the process of reviewing complex economic models and their findings, which has been previously reported by stakeholders as a barrier to the use of economic evidence in decision-making in the US. However, the currently proposed method may not fully address the issue of heterogeneity observed among MAEEs. There is a critical need to explore sources of heterogeneity and develop a standardized approach to handle it to improve the efficiency and acceptability of future MAEEs.

Keywords:

• Meta-analysis
• economic evaluations
• cost-effectiveness analysis
• United States

JEL classification codes:

• C18
• C1
• C
• C54
• C5

Transparency

Declaration of funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Declaration of financial/other relationship

The authors declare that they have no known conflicts of interest that are directly relevant to the content of this article.

A reviewer on this manuscript has disclosed that they are an employee of PRECISIONheor, a health economics consulting firm that provides services to pharmaceutical companies. I also hold equity in our parent company, Precision Medicine Group. The other peer reviewers on this manuscript have no other relevant financial relationships or otherwise to disclose.

Author contributions

SKV, AT, and NC designed and drafted the article.

SKV and SS performed data preparation and analysis.

Acknowledgements

None stated.

Data availability statement

All data are available from the corresponding author upon request.

Code availability

The data analysis file is available from the corresponding author upon request.

Consent for publication

All authors approved the final version of the manuscript for submission.