Chris Sampson’s journal round-up for 29th May 2017

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.

“Naming and framing”: The impact of labeling on health state values for multiple sclerosis. Medical Decision Making [PubMedPublished 21st May 2017

Tell someone that the health state that they’re valuing is actually related to cancer, and they’ll give you a different value than if you hadn’t mentioned cancer. A lower value, probably. There’s a growing amount of evidence that ‘labelling’ health state descriptions with the name of a particular disease can influence the resulting values. Generally, the evidence is that mentioning the disease will lower values, though that’s probably because researchers have been selecting diseases that they think will show this. (Has anyone tried it for hayfever?) The jury is out on whether labelling is a good thing or a bad thing, so in the meantime, we need evidence for particular diseases to help us understand what’s going on. This study looks at MS. Two UK-representative samples (n = 1576; n = 1641) completed an online TTO valuation task for states defined using the condition-specific preference-based MSIS-8D. Participants were first asked to complete the MSIS-8D to provide their own health state, and then to rank three MSIS-8D states and also complete a practice TTO task. For the preference elicitation proper, individuals were presented with a set of 5 MSIS-8D health states. One group were asked to imagine that they had MS and were provided with some information and a link to the NHS Choices website. The authors’ first analysis tests for a difference due to labelling. Their second analysis creates two alternative tariffs for the MSIS-8D based on the two surveys. People in the label group reported lower health state values on average. The size of this labelling-related decrement was greater for less severe health states. The creation of the tariffs seemed to show that labelling does not have a consistent impact across dimensions. This means that, in practice, the two tariffs could favour different types of interventions, depending on for which dimensions benefits might be observed. The tariff derived from the label group demonstrated slightly poorer predictive performance. This study tells us that label-or-not is a decision that will influence the relative cost-effectiveness of interventions for MS. But we still need a sound basis for making that choice.

Nudges in a post-truth world. Journal of Medical Ethics [PubMed] Published 19th May 2017

Not everyone likes the idea of nudges. They can be used to get people to behave in ways that are ‘better’… but who decides what is better? Truth, surely, we can all agree, is better. There are strong forces against the truth, whether they be our own cognitive biases, the mainstream media (FAKE NEWS!!!), or Nutella trying to tell us they offer a healthy breakfast option thanks to all that calcium. In this essay, the author outlines a special kind of nudge, which he refers to as a ‘nudge to reason’. The paper starts with a summary of the evidence regarding the failure of people to change their minds in response to evidence, and the backfire effect, whereby false beliefs become even more entrenched in light of conflicting evidence. Memory failures, and the ease with which people can handle the information, are identified as key reasons for perverse responses to evidence. The author then goes on to look at the evidence in relation to the conditions in which people do respond to evidence. In particular, where people get their evidence matters (we still trust academics, right?). The persuasiveness of evidence can be influenced by the way it is delivered. So why not nudge towards the truth? The author focuses on a key objection to nudges; that they do not protect freedom in a substantive sense because they bypass people’s capacities for deliberation. Nudges take advantage of non-rational features of human nature and fail to treat people as autonomous agents deserving of respect. One of the reasons I’ve never much like nudges is that they could promote ignorance and reinforce biases. Nudges to reason, on the other hand, influence behaviour indirectly via beliefs: changing behaviour by changing minds by improving responses to genuine evidence. The author argues that nudges to reason do not bypass the deliberative capacities of agents at all, but rather appeal to them, and are thus permissible. They operate by appealing to mechanisms that are partially constitutive of rationality and this is itself part of what defines our substantive freedom. We could also extend this to argue that we have a moral responsibility to frame arguments in a way that is truth-conducive, in order to show respect to individuals. I think health economists are in a great position to contribute to these debates. Our subfield exists principally because of uncertainty and asymmetry of information in health care. We’ve been studying these things for years. I’m convinced by the author’s arguments about the permissibility of nudges to reason. But they’d probably make for flaccid public policy. Nudges to reason would surely be dominated by nudges to ignorance. Either people need coercing towards the truth or those nudges to ignorance need to be shut down.

How should hospital reimbursement be refined to support concentration of complex care services? Health Economics [PubMed] Published 19th May 2017

Treating rare and complex conditions in specialist centres may be good for patients. We might expect these patients to be especially expensive to treat compared with people treated in general hospitals. Therefore, unless reimbursement mechanisms are able to account for this, specialist hospitals will be financially disadvantaged and concentration might not be sustainable. Healthcare Resource Groups (HRGs) – the basis for current payments – only work if variation in cost is not related to any differences in the types of patients treated at particular hospitals. This study looks at hospitals that might be at risk of financial disadvantage due to differences in casemix complexity. Individual-level Hospital Episode Statistics for 2013-14 were matched to hospital-level Reference Costs and a set of indicators for the use of specialist services were applied. The data included 12.4 million patients of whom 766,204 received complex care. The authors construct a random effects model estimating the cost difference associated with complex care, by modelling the impact of a set of complex care markers on individual-level cost estimates. The Gini coefficient is estimated to look at the concentration of complex care across hospitals. Most of the complex care markers were associated with significantly higher costs. 26 of 69 types of complex care were associated with costs more than 10% higher. What’s more, complex care was concentrated among relatively few hospitals with a mean Gini coefficient of 0.88. Two possible approaches to fixing the payment system are considered: i) recalculation of the HRG price to include a top-up or ii) a more complex refinement of the allocation of patients to different HRGs. The second option becomes less attractive as more HRGs are subject to this refinement as we could end up with just one hospital reporting all of the activity for a particular HRG. Based on the expected impact of these differences – in view of the size of the cost difference and the extent of distribution across different HRGs and hospitals – the authors are able to make recommendations about which HRGs might require refinement. The study also hints at an interesting challenge. Some of the complex care services were associated with lower costs where care was concentrated in very few centres, suggesting that concentration could give rise to cost savings. This could imply that some HRGs may need refining downwards with complexity, which feels a bit counterintuitive. My only criticism of the paper? The references include at least 3 web pages that are no longer there. Please use WebCite, people!

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Paul Mitchell’s journal round-up for 15th May 2017

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.

Informal care: choice or constraint. Scandinavian Journal of Caring Sciences [PubMed] Published 12th April 2017

The provision of social care in the UK has become a major economic issue, with recent increases in government spending and local authority taxation to help ease the burden on both the health and social care system in the short term. This study examines some of the issues surrounding informal carers (i.e. care of a family member), estimated to be approximately 10% of the UK population. In particular, it focuses on the role of choice and constraints involved with the decision to become a carer. Using a cross-sectional survey for a UK city, choice of caring was explored in terms of responses to care provision provided, asking if it was a free choice initially to provide care, and if there were constraints in terms of duty, lack of others or financial resources for paid care. The analysis focused on how perceived choice in the caring role was associated with socio-demographics and the type of caring role performed, as well as the role of perceived choice in caring and their wellbeing. Out of the 798 respondents to all four questions on caring choice, about 1 in 3 reported an entirely free choice in the decision, with half reporting having a free choice but also a constraint in terms of duty, other available carers or financial resources. Less than 1 in 5 reported not having a free choice. Only carers with bad health or receiving state benefits had an association with a constrained caring role. The more intense the care role was also associated with a more constrained choice. Higher levels of choice were associated with higher levels of wellbeing across measures of happiness, life satisfaction and capability. In multivariable regression analysis, it was found that having a free choice in the initial caring decision resulted in a higher impact on life satisfaction than educational qualifications and home ownership, whilst improved capability of comparable levels to that of home ownership, all else being equal. The authors thus recommend enhanced choice as a way for policy to improve carers wellbeing. Although the authors acknowledge limitations with the study design being cross-sectional and geographically limited to one city, the study shows there is plenty of scope for understanding the determinants of informal caring and consequences for those carers in much greater detail in future national surveys to help address policy in this area in the medium to longer term.

Experienced utility or decision utility for QALY calculation? Both. Public Health Ethics [PhilPapersPublished 6th May 2017

How health states should be valued in population health metrics, like QALYs and DALYs, will not be an unfamiliar topic of discussion for regular readers of this blog. Instead of arguing for decision utility (i.e. accounting for general population preferences for avoiding health states) or experienced utility (i.e. accounting for patient experiences of health states), the authors in this paper argue for a combined approach, reviving a suggestion previously put forward by Lowenstein & Ubel. The authors neatly summarise some of the issues of relying on either decision utility or experienced utility approaches alone and instead argue for better informed decision utility exercises by using deliberative democracy methods where experienced utility in health states are also presented. Unfortunately, there is little detail of how this process might actually work in practice. There are likely to be issues of what patient experiences are presented in such an exercise and how other biases that may influence decision utility responses are controlled for in such an approach. Although I am generally in favour of more deliberative approaches to elicit informed values for resource allocation, I find that this paper makes a convincing case for neither of the utility approaches to valuation, rather than both.

The value of different aspects of person-centred care: a series of discrete choice experiments in people with long-term conditions. BMJ Open [PubMed] Published 26th April 2017

The term “person-centred care” is one which is gaining some prominence in how healthcare is provided. What it means, and how important different aspects of person-centred care are, is explored in this study using discrete choice experiments (DCEs). Through focus groups and drawing from the authors’ own experience in this area, four aspects of person-centred care for self-management of chronic conditions make up the attributes in the DCE across two levels: (i) information (same information for all/personalised information); (ii) situation (little account of current situation/suggestions that fit current situation); (iii) living well (everyone wants the same from life/works with patient for what they want from life); (iv) communication (neutral professional way/friendly professional way). A cost attribute was also attached to the DCE that was given to patient groups with chronic pain and chronic lung disease. The overall findings suggest that person-centred care focused on situation and living well were valued most with personal communication style valued the least. Latent class analysis also suggested that 1 in 5 of those sampled valued personalised information the most. Those with lower earnings were likely to look to reduce the cost attribute the most. The authors conclude that the focus on communication in current clinician training on person-centred care may not be what is of most value to patients. However, I am not entirely convinced by this argument, as it could be that communication was not seen as an issue by the respondents, perhaps somewhat influenced due to the skills clinicians already have obtained in this area. Clearly, these process aspects of care are difficult to develop attributes for in DCEs, and the authors acknowledge that the wording of the “neutral” and “high” levels may have biased responses. I also found that dropping the “negative” third level for each of the attributes unconvincing. It may have proved more difficult to complete than two levels, but it would have shown in much greater depth how much value is attached to the four attributes relative to one another.

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Chris Sampson’s journal round-up for 3rd April 2017

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.

Return on investment of public health interventions: a systematic review. Journal of Epidemiology & Community Health [PubMed] Published 29th March 2017

Cost-effectiveness analysis in the context of public health is tricky. Often the health benefits are small at the individual level and the returns to investment might be cross-sectoral. Lots of smart people believe that spending on public health is low in proportion to other health spending. Here we have a systematic review of studies reporting cost-benefit ratios (CBR) or return on investment (ROI) estimates for public health interventions. The stated aim of the paper is to demonstrate the false economy associated with cuts to public health spending. 52 titles were included from a search that identified 2957. The inclusion and exclusion criteria are not very clear, with some studies rejected on the basis of ‘poor generalisability to the UK’. There’s a bit too much subjectivity sneaking around in the methods for my liking.  Results for CBR and ROI estimates are presented according to local or national level and grouped by ‘specialism’. From all studies, the median CBR was 8.3 and the median ROI was 14.3. As we might have suspected, public health interventions are cost-saving in a big way. National health protection and legislative interventions offered the greatest return on investment. While there is wide variation in the results, all specialism groupings showed a positive return on average. I don’t doubt the truth of the study’s message – that cuts to public health spending are foolish. But the review doesn’t really demonstrate what the authors want it to demonstrate. We don’t know what (if any) disinvestment is taking place with respect to the interventions identified in the review. The results presented in the study represent a useful reference point for discussion and further analysis, but they aren’t a sufficient basis for supporting general increases in public health spending. That said, the study adds to an already resounding call and may help bring more attention to the issue.

Acceptable health and priority weighting: discussing a reference-level approach using sufficientarian reasoning. Social Science & Medicine Published 27th March 2017

In some ways, the moral principle of sufficiency is very attractive. It acknowledges a desire for redistribution from the haves to the have-nots and may also make for a more manageable goal than all-out maximisation. It may also be particularly useful in specific situations, such as evaluating health care for the elderly, for whom ‘full health’ is never achievable and not a meaningful reference point. This paper presents a discussion of the normative issues at play, drawing insights from the distributive justice literature. We’re reminded of the fair innings argument as a familiar sufficientarian flavoured allocation principle. The sufficientarian approach is outlined in contrast to egalitarianism and prioritarianism. Strict sufficientarian value weighting is not a good idea. If we suppose a socially ‘acceptable’ health state value of 0.7, such an approach would – for example – value an improvement from 0.69 to 0.71 for one person as infinitely more valuable than an improvement from 0.2 to 0.6 for the whole population. The authors go on to outline some more relaxed sufficiency weightings, whereby improvements below the threshold are attributed a value greater than 0 (though still less than those achieving sufficiency). The sufficientarian approach alone is (forgive me) an insufficient framework for the allocation of health care resources and cannot represent the kind of societal preferences that have been observed in the literature. Thus, hybrids are proposed. In particular, a sufficientarian-prioritarian weighting function is presented and the authors suggest that this may be a useful basis for priority setting. One can imagine a very weak form of the sufficientarian approach that corresponds to a prioritarian weighting function that is (perhaps) concave below the threshold and convex above it. Still, we have the major problem of identifying a level of acceptable health that is not arbitrary. The real question you need to ask yourself is this: do you really want health economists to start arguing about another threshold?

Emotions and scope effects in the monetary valuation of health. The European Journal of Health Economics [PubMed] Published 24th March 2017

It seems obvious that emotions could affect the value people attach to goods and services, but little research has been conducted with respect to willingness to pay for health services. This study considers the relationship between a person’s self-reported fear of being operated on and their willingness to pay for risk-reducing drug-eluting stents. A sample of 1479 people in Spain made a series of choices between bare-metal stents at no cost and drug-eluting stents with some out-of-pocket cost, alongside a set of sociodemographic questions and a fear of surgery Likert scale. Each respondent provided 8 responses with 4 different risk reductions and 2 different willingness to pay ‘bids’. The authors outline what they call a ‘cognitive-emotional random utility model’ including an ’emotional shift effect’. Four different models are presented to demonstrate the predictive value of the emotion levels interacting with the risk reduction levels. The sample was split roughly in half according to whether people reported high emotion (8, 9 or 10 on the fear Likert) or low emotion (<8). People who reported more fear of being operated on were willing to pay more for risk reductions, which is the obvious result. More interesting is that the high emotion group exhibited a lower sensitivity to scope – that is, there wasn’t much difference in their valuation of the alternative magnitudes of risk reduction. This constitutes a problem for willingness to pay estimates in this group as it may prevent the elicitation of meaningful values, and it is perhaps another reason why we usually go for collective approaches to health state valuation. The authors conclude that emotional response is a bias that needs to be corrected. I don’t buy this interpretation and would tend to the view that the bias that needs correcting here is that of the economist. Emotions may be a justifiable reflection of personality traits that ought to determine preferences, at least at the individual level. But I do agree with the authors that this is an interesting field for further research if only to understand possible sources of heterogeneity in health state valuation.

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