Value of Information: A Tool to Improve Research Prioritization and Reduce Waste

At a time when the scale of investments has raised justifiable concerns about the ability of ongoing research to fulfill expectations [1], the long-run sustainability of research programs will depend on demonstration of value for money. Yet, there has been remarkably little recognition of the need to formally assess research value for money in funding allocation by national governments, funding agencies, and research institutions.

Currently, research priorities are mostly decided using subjective approaches based on consensus among experts, decision makers, and other stakeholders, which tend to lack transparency and may be unduly influenced by special interest groups. More objective measures have been developed based either on the burden of disease or on variations in clinical practice [2]. Prioritization of diseases with the highest burden (morbidity, mortality, or aggregate societal costs) is useful in selecting general areas of neglect [3], but does not help identify what research should be undertaken within these areas. Prioritizing research in areas of disagreement in clinical practice can help practitioners decide between different clinical strategies and, by clarifying what is best practice, reduce variations. In the “clinical variations” method, priorities are defined based on welfare losses due to disagreement [4], with a cost-effectiveness element added in the “payback from research” method (“payback” referring to future savings as a result of the research investment) [5,6]. Setting research priorities based on variations in clinical practice, however, may not be ideal. Scientific uncertainty is not the only cause of clinical variations, which can also be due to poor implementation of research findings. Arguably, only the first should be addressed through additional research, and the second should be dealt with using more efficient means to promote good practice [7].

A decision-theoretic tool, known as “Value of Information” (VOI) [8,9], has been proposed to tackle the complexities of research prioritization in a more comprehensive way. Despite having been promoted and used for over a decade by the National Institute for Health and Care Excellence (NICE) in the United Kingdom [7], VOI is still relatively unknown to the medical scientific community.


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