In July 2016, the Office for Health Economics and the European Personalised Medicine Association published a white paper titled: “The Value of Knowing and Knowing the Value: Improving the Health Technology Assessment of Complementary Diagnostics”. This publication did not receive a great deal of attention at the time, but it raises some interesting points related to genomic testing that are worthy of consideration by a wider audience. In particular, it highlights several things that we currently do reasonably well in health economics and genomics, as well as some areas in which we need to improve evidence generation, suggesting a future research agenda in this field.
Given the wide variety of health and non-health outcomes associated with genomic tests, it is perhaps particularly important that the preferences of key stakeholders are considered within the health technology assessment process for these interventions. Indeed, in a paper published last year, Rogowski et al. highlight the importance of ‘preference-based personalization’ in this context. To date, few studies have generated data on preferences for genomic tests. However, a recent publication in Genetics in Medicine by Deborah Marshall and colleagues has attempted to address this gap in the literature.
In my introductory blog post, I noted that genomics might present new challenges for health economics and called for more discussion about appropriate methods in this context. I didn’t anticipate a particularly rapid response, but just a few days after posting I became aware of a new article published in PharmacoEconomics that engaged with many of the issues raised in my introductory post. Titled “Concepts of ‘personalization’ in personalised medicine: Implications for economic evaluations”, this paper reports the results of a workshop which considered where extensions to standard methods might be required in genomics and is a welcome addition to the limited existing literature on this subject. We covered some similar ground in a related paper published in Pharmacogenomics last year, and it is heartening to see that this new paper has reached some similar conclusions and developed a number of these issues further.