Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.
Health economics as rhetoric: the limited impact of health economics on funding decisions in four European countries. Value in Health Published 19th September 2016
We start on a sombre note, with a paper that begs the question: why do we bother? A key purpose of health economic evaluation is to prevent the use of low-value, high-cost technologies. Influence on funding decisions is arguably a good basis on which to judge the impact of health economics. This study looks at funding decisions in England, Germany, the Netherlands and Sweden. The paper identifies key features of the HTA institutions and processes in each country. For all countries, there is very little evidence of economic evaluation having been the basis for the restriction of high-cost drugs. England found ways to support the funding of drugs for multiple sclerosis and cancer, despite high-cost and apparent low value. One positive impact might be in facilitating the negotiation of reduced prices – for example, through NICE’s patient access schemes. While the different countries have quite different processes, they have produced similar decisions in practice. The authors suggest that, despite having had limited impact on the outcome of funding decisions, health economics has influenced the process of decision making and the language of health care prioritisation. In this sense, health economics has value in rhetoric, increasing transparency and rational decision making. It’s an interesting idea that I’d like to see developed further, as the authors only provide a limited discussion of it. Personally, I think some distinction needs to be drawn between ‘health economics’ – as identified in the title – and ‘agency-mandated health technology assessment’. While many readers of this blog might do the former on a daily basis, I’d bet not many of us deal in the latter. I certainly don’t. So there’s a lot of ‘health economics’ that can’t – at least not directly – be judged on the basis of funding decisions. Yes, high-cost drugs backed by money-hungry Pharma evade HTA defences. But what about the other end of the spectrum? What about high-value interventions that have been commissioned because the economic evidence has been so compelling. Wishful thinking? Maybe not. Either way, we shouldn’t understate the value of health economics as rhetoric when dealing with capricious and myopic governments.
Recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses: Second Panel on Cost-Effectiveness in Health and Medicine. JAMA [PubMed] Published 13th September 2016
What do you mean you haven’t yet pre-ordered the new edition of the ‘Gold’ book from the famous Panel on Cost-Effectiveness in Health and Medicine? The original Panel was a big deal (not that I remember it, of course, as I was 8 years old), and so, presumably is the Second Panel. Maybe less so as relative consensus has developed in the use of health technology assessment in practice around the world. But we still need guidance. It’s ironic that the Panel was convened and funded by US organisations in a country that lags far behind in its use of economic evaluation in health technology assessment. This article in JAMA outlines the Panel’s recommendations. I can’t summarise them all here, so you probably need to go and read it all yourself. But know that there isn’t anything radical or unexpected. This Panel updated the original recommendations and created new ones where necessary. Threatening the validity of many a joke at economists’ expense, the Panel was able to reach consensus on all recommendations. Readers are chastised for not appropriately adopting a societal perspective as recommended by the first Panel, but then we are offered a compromise: “All studies should report a reference case analysis based on a health care sector perspective and another reference case analysis based on a societal perspective”. The Panel also recommend use of an “impact inventory”. This is a nice suggestion and I like the terminology. Including a disaggregated list of costs (and outcomes) improves transparency and makes studies more useful to future researchers. One new recommendation is that we should include unrelated future costs, which is something we saw discussed in a recent journal round-up. Another departure from the first Panel is that we are told to include productivity costs in the cost side of our equation. A suggestion that’s dropped in is that protocols should be written in advance of a study. I wish the panel had been more forceful with this one, as published protocols could go a long way in improving consistency, transparency and quality.
OK, I admit it: I went into this paper with a lot of scepticism. The QALY – that is, the combination of the quality and quantity of life – fundamentally makes sense. I’m not sure we need ‘an alternative’. The paper introduces some interesting ideas, but they aren’t as revolutionary as the author suggests and I’m not sure that it gets us anywhere. There are some problems from the outset. The article jumbles up positive and normative matters, criticising the QALY on the basis of its capacity to indicate what we might consider to be inequitable results. The author hints that the need for a new model derives from the QALY’s inappropriate combination of quality and duration of life. The most obvious criticism is that the constant proportional trade-off assumption does not hold. But then there’s no discussion of CPTO. The Load Model is presented as “radically different”, but it isn’t. Equations are shuffled so that we’re dealing in rates rather than time, but this adjustment appears to be inconsequential. It might be a more useful way to think about morbidity and mortality, but no argument to that end is presented. The main difference in the Load Model is that a ‘load’ is added for the negative impact of death (as opposed to being dead). Now, I have big problems with the way we handle ‘dead’ in health state valuation. I think it’s a more serious issue than we know (and we know quite a bit), so I am always glad to see attempts to fix it. Once you get past the superficial adjustments to the QALY, what’s really going on is that the Load Model is adding a third dimension to the valuation process; in addition to length of life and quality of life (in the Load Model it’s disease burden) we also have quality (or rather the burden) of death. But this could be incorporated into a QALY framework; I’ve spoken before about the notion of a 3- or otherwise multi-dimensional QALY. Given that death is so key to the distinction between the Load Model and the QALY, it’s unfortunate that in the worked example an entirely arbitrary value of questionable meaning is attributed to it. So the subsequent comparison between the two approaches seems meaningless. There may be more merit in the Load Model than I can see – perhaps I lack the immagination. But it seems to solve none of the problems associated with the QALY framework, while introducing new ones.
Associations between extending access to primary care and emergency department visits: a difference-in-differences analysis. PLOS Medicine [PubMed] Published 6th September 2016
We’ve had quite a bit of discussion of 7 day services here on the blog. But the papers continue to flood in, much to the chagrin of Jeremy Hunt. This study doesn’t look at the most controversial case of extending hospital services, but investigates whether extended (evening and weekend) opening of GP practices reduces hospital attendance. The context is that providers in Manchester (England) were invited to bid for funding to roll out extended hours from December 2013. In total we’re looking at 56 practices who succeeded in the bid and 469 practices who provided services as normal. The analysis uses routinely collected hospital administrative data for almost 3 million patients from 2011 to 2014. A difference-in-differences OLS regression was used with propensity score matching to try and deal with the obvious selection problem. Of course, there was an increase in the number of GP visits: 33,519 in total. The main finding is that patients registered at practices with extended hours exhibited a 26.4% relative reduction in attendances for minor problems at A&E. So in this sense, extending opening hours seems to have satisfied its purpose. Though each emergency attendance ‘avoided’ corresponded to around 3 additional GP appointments. Unfortunately the study wasn’t able to determine the set-up and running costs of the extended GP services, so couldn’t carry out a proper cost-effectiveness analysis. And as we’ve discussed before in this context, that’s the question that really matters.