Chris Sampson’s journal round-up for 1st August 2016

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.

Individualised and personalised QALYs in exceptional treatment decisions. Journal of Medical Ethics [PubMedPublished 22nd July 2016

I’ve written previously about the notion of individualised cost-effectiveness analysis – or iCEA. With the rise of personalised medicine it will become an increasingly important idea. But it’s one that needs more consideration and research. So I was very pleased to see this essay in JME. The starting point for the author’s argument is that – in some cases – people will be denied treatment that would be cost-effective for them, because it has not been judged to be cost-effective for the target population on average. The author’s focus is upon people at the extremes of the distribution in terms of treatment effectiveness or costs: exceptional cases. There are two features to the argument. First, cost-effectiveness should be individualised in the sense that we should be providing treatment according to the costs and effects for that individual. Second, QALYs should be ‘personalised’ in the sense that individual’s own (health) preferences should be used to determine whether or not treatment is cost-effective. The author argues that ‘individual funding requests’ (where patients apply for eligibility for treatment that is not normally approved) represent an ideal context in which to use individualised and personalised QALYs. Unfortunately there are a lot of problems with the arguments presented in this essay, both in terms of their formulation and their practical implications. Some of the ideas are a bit dangerous. That there is no discussion of uncertainty or expectations is telling. If I can find the time I’ll write a full response to the journal. Nevertheless, it’s good to see discussion around this issue.

The value of medicines: a crucial but vague concept. PharmacoEconomics [PubMed] Published 21st July 2016

That we can’t define value is perhaps why the practice of value-based pricing has floundered in the UK. Yes, there’s cost-per-QALY, but none of us really think that’s the end of the value story. This article reports on a systematic review to try and identify how value has been defined in a number of European countries. Apparently none of the identified articles in the published literature included an explicit definition of value. This may not come as a surprise – value is in the eye of the beholder, and analysts defer to decision makers. Some vague definitions were found in the grey literature. The paper highlights a number of studies that demonstrate the ways in which different stakeholders might define value. In the countries that consider costs in reimbursement decisions, QALYs were (unsurprisingly) the most common way of measuring “the value of healthcare products”. But the authors note that most also take into account wider societal benefits and broader aspects of value. The review also identifies safety as being important. The authors seem to long for a universal definition of value, but acknowledge that it cannot be a fixed target. Value is heavily dependent on the context of a decision, so it makes sense to me that there should be inconsistencies. We just need to make sure we know what these inconsistencies are, and that we feel they are just.

The value of mortality risk reductions. Pure altruism – a confounder? Journal of Health Economics Published 19th July 2016

Only the most belligerent of old-school economists would argue that all human choices can be accounted for in purely selfish terms. There’s been much economic research into altruistic preferences. Pure altruism is the idea that people might be concerned with the general welfare of others, rather than just specific factors. In the context of tax-funded initiatives it can be either positive or negative, as people could either be willing to pay more for benefits to other people or less due to a reluctance to enforce higher costs (say nothing of sadism). This study reports on a discrete choice experiment regarding mortality reductions through traffic safety. Pure altruism is tested by the randomised inclusion of a statement about the amount paid by other people. An additional question about what the individual thinks the average citizen would choose is used to identify the importance of pure altruism (if it exists). The findings are both heartening and disappointing. People are considerate of other people’s preferences, but unfortunately they think that other people don’t value mortality reductions as highly as them. Therefore, individuals reduce their own willingness to pay, resulting in negative altruism. Furthermore, the analysis suggests that this is due to (negative) pure altruism because the stated values increase when the notion of coercive taxation is removed.

Realism and resources: towards more explanatory economic evaluation. Evaluation Published July 2016

This paper was doing the rounds on Twitter, having piqued people’s interest with an apparently alternative approach to economic evaluation. Realist evaluation – we are told – is expressed primarily as a means of answering the question ‘what works for whom, under what circumstances and why?’ Economic evaluation, on the other hand, might be characterised as ‘does this work for these people under these circumstances?’ We’re not really bothered why. Realist evaluation is concerned with the theory underlying the effectiveness of an intervention – it is seen as necessary to identify the cause of the benefit. This paper argues for more use of realist evaluation approaches in economic evaluation, providing an overview of the two approaches. The authors present an example of shared care and review literature relating to cost-effectiveness-specific ‘programme theories’: the mechanisms affecting resource use. The findings are vague and inconclusive, and for me this is a problem – I’m not sure what we’ve learned. I am somewhat on the fence. I agree with the people who think we need more data to help us identify causality and support theories. I agree with the people who say we need to better recognise context and complexity. But alternative approaches to economic evaluation like PBMA could handle this better without any express use of ‘realist evaluation’. And I agree that we could learn a lot from more qualitative analysis. I agree with most of what this article’s authors’ say. But I still don’t see how realist evaluation helps us get there any more than us just doing economic evaluation better. If understanding the causal pathways is relevant to decision-making (i.e., understanding it could change decisions in certain contexts) then we ought to be considering it in economic evaluation. If it isn’t then why would we bother? This article demonstrates that it is possible to carry out realist evaluation to support cost-effectiveness analysis, but it isn’t clear why we should. But then, that might just be because I don’t understand realist evaluation.

Photo credit: Antony Theobald (CC BY-NC-ND 2.0)

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A taxonomy of behavioural interventions

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Back in March I made a note to myself to write a paper – or, more likely, a blog post – presenting a taxonomy of behavioural interventions. I had gotten tired of everything being called a ‘nudge’ and with debates about whether nudges are ethical. I even bought a copy of Nudge so that I could use it to populate the taxonomy with examples.

Thankfully, someone else was already working on this and has beaten me to it – producing almost exactly what I had in mind. Mira Fischer from the University of Cologne and Sebastian Lotz from Stanford have written a working paper titled ‘Is soft paternalism ethically legitimate? – the relevance of psychological processes for the assessment of nudge-based policies‘. They differentiate between 4 types of behavioural intervention – or ‘nudge’ – and discuss the ethical implications associated with each by considering the psychological processes at play. It’s far better than any blog post I could have written, and I recommend reading it.

Fischer and Lotz’s taxonomy

Consider a utility-maximising individual with 2 choices (A or B), each with 2 possible outcomes (1 and 2), such that the utility associated with choice A would be U_{A} = \pi_{A1}(u_{A1M}+u_{A1N})+\pi_{A2}(u_{A2M}+u_{A2N}), where ‘π’ is the probability and ‘u’ the utility of the outcome and the ‘M’ and ‘N’ refers to monetary and non-monetary utility. Based on this, the authors then discuss the ways in which various types of nudge might influence the individual’s choice. The table below is not from the paper and is my interpretation of the taxonomy.

Type Name Point of influence Means of impact on expected utility of choice Examples
1 ‘discomfort nudge’ choice evaluation non-monetary utility default settings on electronic devices; communication of social norms
2 ‘probability nudge’ choice evaluation subjective probability of realisation informational campaigns
3 ‘indifference nudge’ preference formation monetary or non-monetary utility positioning of healthy/unhealthy products
4 ‘automatism nudges’ ? ? changes in road markings

Is the taxonomy complete and well-defined?

In my opinion, it is not.

I do not believe that Type 4 nudges exist in the way described. The authors use the example of changing road markings to make drivers think they are travelling faster than they actually are and thus reduce their speed. It seems clear to me that this is an example of Type 2; the driver has been made to believe that the probability of them crashing at their current speed is greater than they would otherwise have believed. The idea that there is an ethical difference between nudges to our ‘automatic’ behaviour and nudges to our considered behaviour – given that so much of our behaviour is automatic – I believe is unfounded.

When I was considering writing my own taxonomy of behavioural interventions, I was approaching it from a decision analysis perspective. Simply imagining the structure of an individual’s decision process and considering the different points at which an individual could be influenced. Based on the Thaler/Sunstein definition, a nudge can affect any part of a person’s decision process.

Based on this I believe there are 3 points of influence: i) before an individual’s preferences are defined ii) after the definition of preferences but before the observation of the choice set and iii) once the choice set has been recognised. Once preferences are defined and the choice set has been recognised there are 2 means of influencing choice; utility or probability.

As such, I think the taxonomy should look like this:

Type Point of influence Means of impact on expected utility of choice Examples
A preference formation values/priorities education; positioning of food
B choice set observation choice set expansion/compression positioning of food; introduction of cycle lanes
C choice evaluation subjective probability informational campaigns
D choice evaluation utility defaults; communication of social norms

As the authors outline in their paper, particular nudges will cross type boundaries. I have included the ‘positioning of food’ nudge under 2 types to highlight this. If positioning causes an individual to choose a healthy item – where they otherwise would have chosen a less healthy one – this could either be because they saw the healthy item first or because they simply didn’t see and fully consider the unhealthy option. In the former case Type A is at work, while in the latter case Type B is at work. I believe that educational interventions could fall into any of the above types because they can improve an individual’s ability to satisfy their own preferences. Type D could, of course, include a tax or a subsidy.

Furthermore, the ethical implications may be different depending on whether the impact on types B, C or D is positive or negative, and also whether the impact on utility is monetary or non-monetary, which would increase the total number of types to 9.

I don’t know whether I, the authors or both of us are right, but there’s one thing we can agree on. One nudge isn’t necessarily as ethical as the next, so we need better ways of defining behavioural interventions.

DOI: 10.6084/m9.figshare.1232109

Incentives and social preferences

Incentives are widely and frequently used to influence preferences among people with the aim of achieving some socially beneficial end. These incentives include fines, rewards, and taxes. From the domain of health, Pigouvian taxes on foods deemed unhealthy and pricing schemes for alcohol are examples of such incentives. But, evidence often reveals that these incentives are not having the effect that would be expected from a rational homo economicus; often the effect is smaller than expected and in some cases is the opposite of what is expected. In one well-cited experiment, the imposition of fines on parents arriving late to pick up their children in Haifa, Israel, resulted in double the number of late pick-ups (Gneezy and Rustichini, 2000). Social preferences must be playing a role. In an extensive review of economic experiments, Bowles and Polania-Reyes (2012) examine whether economic incentives and social preferences are substitutes or complements. For policy-makers, the non-separability of incentives and social preferences is important; if incentives act as a substitute for preferences for some socially beneficial end, then their imposition will lead to lower than expected or opposite effects.

To examine how social preferences and incentives interact, Bowles and Polania-Reyes identify two types of preference: state-dependent and endogenous. They distinguish them as follows:

As Italian residents, your authors now eat a lot more pasta than we did in our countries of origin. Abstracting from possible international price differences, this could be another case of “when in Rome, do as the Romans.” Or it might be that we have newly come to enjoy the taste of pasta, perhaps through extensive exposure to it while in Italy. Which case it is—state-dependent or endogenous preferences—would be revealed by what we will eat back in Bogotá or Santa Fe. If we go back to arepas or potatoes, then our taste for pasta was state-dependent. If we remain pastaphiles, then our preferences have endogenously changed.

Extending from this, the authors define mechanisms by which incentives and preferences interact. Under a state-dependent mechanism, the situation, environment, or way (e.g. the state) in which an incentive is administered can alter preferences in three ways:

  • Bad news – the incentive provides information about those administering the incentive (the principal).
  • Moral disengagement – the incentive ‘crowds out’ moral values; in the absence of an incentive individuals rely on moral preferences.
  • Control aversion – Incentives compromise self-determination; people do not like being manipulated and wish to be treated with dignity and autonomy.

All three cases are relevant to health policy, but, perhaps, it is the last that may have the largest effect. There are frequent attempts to provide incentives to manipulate the diet and drinking and smoking habits of individuals. Fast food and fizzy drinks taxes have been proposed frequently (e.g. here and here). A purely rational homo economicus would respond accordingly to these taxes and adjust her preferences in accordance with the differing marginal cost. But, these taxes may be viewed as a dictation of behaviour from a political class without regard or understanding for choices or preferences for those from different backgrounds and the response may be to do exactly the opposite. Similarly, an imposition of a Pigouvian tax may lead to moral disengagement as the tax and market act as a substitute for social responsibility to protect health.

Incentives may alter preference acquisition in the long-term as they influence economic rewards and social status of those with different preferences. The economic structure of a society has been shown to affect parental child rearing values, personality traits, and developmental influences (Bowles, 1998). From a broader, political economic perspective, the economic structure of society also provides the opportunities, objectives and constraints under which state managers operate. They have to balance both trying to improve public health with the necessity for electoral success (other self-interested motives notwithstanding). The economic structure which leads to preferences among the poor for health-related behaviours that generally have a negative aggregate effect on public health is the same economic structure that leads state managers using taxes and fines to both provide incentives to alter health-related preferences but also to shift the burden of the net result of those preferences onto those individuals. But, for the aforementioned reasons, including social position and wealth, these incentives may just replicate the same socioeconomic conditions that may have led to the acquisition of those preferences in the first place.

Incentives could also have a crowding-in effect; amplifying already existing social preferences. However, understanding when this is the case is very difficult ex ante. Bowles and Polania-Reyes conclude their study with the following:

The policy package of which the incentives are part should let the target understand that the desired modification in her actions will serve to implement an outcome that is socially beneficial so that the target is more likely to endorse the purpose of the incentive, rather than being offended by it as either unjust or a threat to her autonomy or in some other way reflecting badly on the intentions of the planner.

What is also clear is that, particularly in the case of health policy, creating a distinction between an economic world and a non-economic social and political world, as is the case in much of neoclassical economics, may serve as a hindrance to understanding and implementing effective policy.