Real-world evidence and nonrandomized data in health technology assessment: use existing methods to address unmeasured confounding?

Summary

Health Technology Assessment (HTA) bodies are increasingly presented with submissions containing nonrandomized measures of treatment effect, including real-world evidence. The consideration of such evidence has been hampered by uncertainty surrounding the potential impact of unmeasured confounding – often leading to such data being disregarded in the decision-making process. Methods to quantitatively explore the potential impact of unmeasured confounding on estimated treatment effects exist and offer potential to support the use of nonrandomized data in HTA. This article provides an overview of these methods, highlights their underutilization in HTA and considers the steps that would be required to increase their use in this field.