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”.
So why is it important that we have this debate about the use of health economic methods in genomics? Genomic technologies have evolved considerably over the past decade, and the information that they can provide on multiple genetic changes across the whole genome has the potential to enable improved disease stratification and permit the more widespread use of individually tailored therapies. However, despite some success stories, these genomic technologies have had a limited impact on clinical practice to date, and adoption rates vary considerably in different countries. There are many reasons for this, and the lack of clinical evidence and ethical concerns are well-documented elsewhere. The lack of health economic evidence for these technologies, and the challenges that health economists face in producing this evidence are, however, less well-documented.
The aim of this blog is to consider these issues in depth. Genomics has the potential to challenge all aspects of economic evaluation methodology. For example, how should we measure test outcomes if the main benefits of testing are informational, rather than directly impacting on health? How should we calculate test costs when national pricing tariffs rarely exist? When should we conduct our analyses when genomic tests are constantly evolving? What should our comparators be when standard practice changes from one lab to the next? How can our analyses reflect the wider infrastructure costs associated with genomic platform diagnostics with multiple applications? Is there a greater role for cost-benefit analysis in genomics? How can our analyses incorporate evidence on test effectiveness which is often both poor quality and extremely complex? How should we incorporate the behaviour of clinicians and patients into our analyses? The list of challenges is long, and future posts will consider each of these issues in far more depth.
Some readers will likely be wondering at this point whether genomics actually presents new challenges for health economics, and whether we really need to have this conversation about appropriate methods in this context. After all, many of these challenges are not unique to genomics. It has already been noted by many health economists that measuring the outcomes of public health interventions can be challenging. Economic evaluations of surgical techniques already have to manage large variations in standard practice from one hospital to the next (and sometimes between different surgeons in the same hospital). Uptake of all tests, genomic or otherwise, is rarely universal, and data on clinician and patient adherence to testing advice is often lacking.
So is genomics unique, in a health economics context? One possibility is that the breadth and complex nature of the issues that arise when conducting economic evaluations in genomics is such that this clinical context does represent an exceptional challenge for standard methods. This position has some parallels with the standard response given in health economics textbooks to the question: “Why do we need to intervene to allocate scarce resources in health care?”. The usual justification given is that, although the challenges that exist in health care (e.g. moral hazard, adverse selection, externalities, imperfect principle agent relationship) also exist in other sectors of the economy, the scale and variety of these issues in health care is such that supplementing market forces with government intervention is the only way to ensure that health care resources are allocated in an vaguely efficient manner. Having said all that, there is probably no correct answer to this question at present. This blog welcomes different opinions, and wider debate of this point will definitely be encouraged in the months to come.
What should you expect to read on this blog? The intention is for this blog to feature a wide variety of posts, including discussions of the challenges that arise in genomics and potential solutions, opinion pieces, reviews of key papers, and any other content that stimulates debate in this area. Health economists should be having more conversations about these issues and hopefully this blog can facilitate those conversations. Genomic technologies are here to stay, and the quicker that we as health economists can adapt our methods (where necessary) to address the challenges in genomics, the better the economic evidence that we will be able to provide to policymakers. This in turn will hopefully enable them to be more confident in their recommended adoption decisions for these technologies, leading to an improved allocation of health care resources.
2 thoughts on “Introduction”
[…] my introductory blog post, I noted that genomics might present new challenges for health economics and called for […]
[…] my first blog post, I posed a number of questions that were relevant in health economics and genomics. One of these […]