Our authors provide regular round-ups of the latest peer-reviewed journals. We cover all issues of major health economics journals as well as other notable releases. Visit our journal round-up log to see past editions organised by publication title. If you’d like to write a journal round-up, get in touch.
Perhaps you’ve heard of the PECUNIA project. I’ve been a fan on the sidelines. The PECUNIA researchers embraced the often-neglected task of doing a good job of resource use measurement. The first paper in this issue of AHEHP describes the development of a new resource use measure (RUM) that focuses on capturing costs across multiple sectors (e.g. health, education, and justice). The researchers adopted a six-step approach that was previously proposed and found that it was broadly applicable to their context. There was a little added complexity due to the modular nature of the development process, and the authors describe how they dealt with this. The clear narrative for the development of this instrument is an anomaly that should be celebrated, and it should inform future work on the development of RUMs. You can find the resulting RUM here. So long as you make the most of its modular structure, it’s a simple, efficient, and well-thought-out questionnaire. Put that CSRI in the bin and rejoice!
Over to the denominator now, and your EQ-5D fix. There are a couple of very citable papers in this issue. One study reports EQ-5D-5L population norms for Italy. What can I say? Here it is. Do with it what you will. The data are cut up and presented in various ways, so you can dig around for interesting titbits specific to the Italian population. Perhaps of more interest to a UK audience is a study mapping from the GHQ to the EQ-5D-3L. You can find the GHQ all over the place (including in Understanding Society), so the potential applications for this item-response mapping are many. A few other GHQ->EQ-5D mapping studies have been published in the past, but I believe this is the first to map to EQ-5D states, meaning that it does not assume a specific value set. But the best bit about this paper is that the author provides the R script, so you can make it happen with minimal effort.
As you know, I appreciate a literature review, and this issue has no fewer than six that I’d like to mention. There’s one looking at the cost-effectiveness of lifestyle interventions in cancer management, mainly focussed on physical exercise. The findings from the 9 included studies were equivocal: probably effective, but possibly not cost-effective. On the methods side of cost-effectiveness, there’s a review of studies conducting ‘headroom analysis‘, which, for the uninitiated, is a kind of early economic evaluation that seeks to identify the highest price at which an intervention might be cost-effective. The authors found 42 papers, all overflowing with heavy assumptions and expert opinion, as you might expect, and it’s helpful to see these tendencies described here. There’s also a review of studies measuring health system efficiency. It’s a biggy, with 131 papers included, but the authors highlight significant shortcomings in the evidence base.
The review of most interest to me is a critical review of the impact of mental health on workplace productivity. From the 38 included studies, the authors concluded that it is pretty clear that anxiety and depression do have a substantial impact on workplace productivity. However, there’s some indication that better studies demonstrate a weaker effect. The authors call for more sophisticated studies to better identify causal effects (and mechanisms) to inform decision-making.
The other two reviews relate to HTA policy and practice, making comparisons across countries. One study considered whether HTA agencies value novelty in appraisal processes. Strictly speaking, the answer is ‘no’; agencies in the eight included countries do not explicitly value novelty. But several do (explicitly) acknowledge certain aspects that may relate to novelty, such as the extent to which a technology addresses an unmet need or involves a new approach to treatment. Perhaps this study can be a step towards burying the idea that ‘novelty’ has value and instead help us refocus on the various characteristics of technologies that really do bring value (novel or otherwise). The other paper reviewing HTA appraisal materials compares decisions about anticancer drugs in England and Korea. In both contexts, managed entry agreements were popular, and there was a lot of overlap in clinical assessment.
There are only a couple of cost-effectiveness analyses in this issue, and they both do something innovative. One uses a whole-population sample in Germany to show that following treatment recommendations for early breast cancer is cost-effective. The other estimates the value of a future trial of an AI-based fall prevention system in Australia. Another study uses a triple-differences approach to demonstrate the cost savings associated with a guideline implementation intervention in primary care in New Zealand.
The prize for the study with the most novelty – whether you value it or not – is a toss-up between a theoretical model of trial costs and a study using queueing theory. In the first, the authors take the example of placebo surgery trials and wage war on waste with algebra as their weapon. The model uses data on target and actual recruitment to demonstrate the costs of overestimating recruitment in clinical trials, and the authors provide recommendations for the funding of efficient trials. In the second study, the authors take aim at zero-targets for delayed transfers of care in the NHS. They use their special queueing theory algebra to show that a zero-target results not only in a shift in costs from acute to community care but that total costs will increase. As such, non-zero targets should be established.
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