Making better decisions in genomics

Happy New Year everybody. One of my new year’s resolutions is to post more frequently in 2015, and I’m going to start by taking a look at a recently published paper by Susan Snyder and colleagues titled “Economic evaluation of pharmacogenomics: a value-based approach to pragmatic decision making in the face of complexity”. This is a review paper that takes a look at the need for, and current use of economic evaluations in pharmacogenomics, identifying both obstacles to progress and also areas where, actually, we’re doing ok at the moment. There have been a few papers covering similar ground in the past couple of years (interested readers should check out Faulkner et al., Annemans et al. and, in a shameless act of self-promotion, one of my publications) and I think all of them have made a significant contribution to the literature in one way or another. Snyder et al. do so as well. Rather than review their paper in full, I wanted to focus on their unique contribution by pulling out a couple of points of interest that might prompt further discussion.

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Incidental findings in genomic sequencing: a health economics perspective

When this blog began, I mentioned that I would be happy to publish posts by other researchers: different opinions and healthy debate are both welcome here. I’m therefore very pleased to introduce a colleague of mine at the University of Oxford, Jilles Fermont, who discusses some recently published articles on incidental findings in genomic sequencing from a health economics perspective.

Incidental findings (IFs) are a topic of considerable debate, not just in genomic medicine but also in other fields of medicine. To date, few health economists have undertaken any work in this area, but a recent burst of publications suggests that this is beginning to change. This post is primarily prompted by the publication of a paper in Genetics in Medicine earlier in November titled “The cost-effectiveness of returning incidental findings from next-generation genomic sequencing”, authored by Bennette and colleagues. The authors intended to evaluate the clinical and economic impact of IFs in genomic sequencing. The cost-effectiveness analysis (CEA) is restricted and has limitations (see below) but, as the authors already indicated, it is much more of an exploratory study providing policy recommendations on how to deal with IFs from genomic sequencing. Also, it is not a CEA of next-generation sequencing (NGS) but that of the return of IFs. Despite these caveats, it remains an interesting and relevant paper. Those involved or interested in this field are recommended to read it.

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Hello. Chances are you’re a health economist, although you might also be a researcher in a different field of healthcare. You might even be a scientist (apologies in advance for any bad science that might follow). Whoever you are, you’re very welcome. The aim of this introductory post is to tell you what you should expect from this blog. Hopefully you’ll be sufficiently intrigued to return, read some more articles and contribute to the growing debate surrounding the application of standard health economic methods in the field of genomics.

This blog is going to assume that you know a little bit about genomics. Specifically, this blog is going to assume that you have at least read the “What are genomic technologies?” section of this blog, a short introduction for a layperson who already has a little bit of science knowledge. Of course, many of you will have a greater knowledge of genetics and genomics than this simple introduction, but this blog is intended to be broadly accessible to stimulate wide debate, so the aim is to keep the genomics jargon to a minimum. This blog is also going to assume that the average reader has some basic knowledge about health economics. Those who don’t could do a lot worse than frequent the excellent “Academic Health Economists’ Blog”.

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