Chris Sampson’s journal round-up for 18th December 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.

Individualized glycemic control for U.S. adults with type 2 diabetes: a cost-effectiveness analysis. Annals of Internal Medicine [PubMed] Published 12th December 2017

The nature of diabetes – that it affects a lot of people and is associated with a wide array of physiological characteristics and health impacts – has given rise to recommendations for individualisation of care. This paper evaluates individualisation of glycemic control targets. Specifically, the individualised programme allocated people to one of 3 HbA1c targets (<6.5%, <7%, <8%) according to their characteristics, while the comparator was based on a single fixed target (<7%). The researchers used a patient-level simulation model. Risk equations developed by the UKPDS study were used to predict diabetes complications and mortality. The baseline population was derived from the NHANES study for 2011-12 and constitutes people who self-reported as having diabetes and who were at least 30 years old at diagnosis (to try and isolate type 2 diabetes). It’s not much of a surprise that the individualised approach dominated uniform intensive control, saving $13,547 on average per patient with a slight improvement in QALY outcomes. But the findings are not all in favour of individualisation. Quality of life improvements due to the benefits of medication were partially counteracted by a slight decrease in life years gained due to a higher rate of (mortality-increasing) complications. The absolute lifetime risk of myocardial infarction was 1.39% higher with individualisation. A key outstanding question is how much the individualisation process would actually cost to get right. Granted, it probably wouldn’t cost as much as the savings estimated in this study, but the difficulty of ensuring adequate data quality to consistently inform individualisation should not be underestimated.

Microlevel prioritizations and incommensurability. Cambridge Quarterly of Healthcare Ethics [PubMed] Published 7th December 2017

This article concerns the ethical challenges of decision-making at the microlevel. For example, decisions may need to be made about allocating resources between 2 or more identifiable patients, perhaps within a particular clinic or amongst an individual clinician’s patients. The author asserts two relevant values: health need satisfaction and efficiency. Health need satisfaction is defined in terms of severity (regardless of capacity to benefit from available treatments), while efficiency is defined in terms of the maximisation of health benefit (subject to the effectiveness of treatment). The author then argues that these two values are incommensurable in the sense that we can have situations in which health need satisfaction is greater (or less) for a given choice over another, while efficiency could be lower (or higher). Thus, it is not always possible to rank choices given two non-cardinally-comparable values. It might not be clear whether it is better to treat patient A or patient B if the implications of doing so are different in terms of need and efficiency. The author then goes on to suggest some solutions to this apparent problem, starting by highlighting the need for decision makers (in this case clinicians) to recognise different decision paths. The first solution is to generate some guidelines that offer complete ordering of possible choices. These might be based on a process of weighting the different values (e.g. health need satisfaction and efficiency). The other ‘solution’ is to leave the decision to medical practitioners, who can create reasons for choices that may be unique to the case at hand. In this case, certain decision paths should be avoided, such as those that would entail discrimination. I have a lot of problems with this assessment of decision-making at the individual level. Mainly, the discussion is undermined by the fact that efficiency and health need satisfaction are entirely commensurable insofar as we care about either of them in relation to prioritisation in health care. We tend to understand both health need satisfaction and opportunity cost (the basis for estimating efficiency) in terms of health outcomes. The essay also fails to clearly identify the uniqueness of the challenge of microlevel decision-making as distinct from the process of creating clinical guidelines. This may call for a follow-up blog post…

EQ-5D: moving from three levels to five. Value in Health Published 6th December 2017

If you work on economic evaluation, the move from using the EQ-5D-3L to the EQ-5D-5L – in terms of the impact on our results – is one of the biggest methodological step changes in recent memory. We all know that the 5L (and associated value set for England) is better than the 3L. Don’t we? So it is perhaps a bit disappointing that the step to the 5L has been so tentative. This editorial articulates the challenge. NICE makes standards. EuroQoL does research. NICE was (relatively) satisfied with the 3L. EuroQoL wasn’t. We have a clash between an inherently (perhaps necessarily) conservative institution and an inherently progressive institution. Hopefully, their interaction will put us on a sustainable path that achieves both methodological consistency and scientific rigour. This editorial also provides us with a DOI-citable account of the saga that includes the development of the 5L value set for England and NICE’s subsequent memorandum.

Current UK practices on health economics analysis plans (HEAPs): are we using heaps of them? PharmacoEconomics [PubMed] Published 6th December 2017

You could get by for years in economic evaluation without even hearing about ‘health economics analysis plans’ (HEAPs). It probably depends on the policies set by the clinical trials unit (CTU) that you’re working with. The idea is that HEAPs are an equivalent standard operating procedure (SOP) to a statistical analysis plan – setting out how the trial data will be analysed before the analysis begins. This could aid transparency and consistency, and prevent dodgy practices. In this study, the researchers sought to find out whether HEAPs are actually being used, and their perceived role in clinical trials research. A survey targeted 46 UK CTUs, asking about the role of health economists in the unit and whether they used HEAP SOPs. Of 28 respondents, 11 reported having an embedded health economics team. A third of CTUs reported always having a HEAP in place. Most said they only used HEAPs ‘sometimes’, and publicly funded trials were said to be more likely to use a HEAP. The majority of respondents agreed it was acceptable to produce the HEAP at any point prior to a lockdown of the data. The findings demonstrate inconsistency in who writes HEAPs and who is perceived to be the audience. I agree with the premise that we need HEAPs. Though I’m not sure what they should look like, except that statistical analysis plans probably should not be used as a template. It would be good if some of these researchers took things a step further and figured out what ought to go into a HEAP, so that we can consistently employ their recommendations. If you’re on the HEALTHECON-ALL mailing list, you’ll know that they’re already on the case.

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Meeting round-up: 7th Meeting of the International Academy of Health Preference Research

The 7th meeting of the International Academy of Health Preference Research (IAHPR) took place in Glasgow on Saturday 4th November 2017. The meeting was chaired by Karin Groothuis-Oudshoorn and Terry Flynn. It was preceded by a Friday afternoon symposium on the econometrics of heterogeneity, which I was unable to attend.

IAHPR is a relatively new organisation, describing itself as an ‘international network of multilingual, multidisciplinary researchers who contribute to the field of health preference research’. To minimise participants’ travel costs, IAHPR meetings are usually scheduled alongside major international conferences such as the meetings of iHEA, EuHEA and AHES (the Australian Health Economics Society). The November meeting took place just before the kick-off of the ISPOR European Congress (a behemoth by comparison). Most, but not all, of the attendees I spoke to, said that they would also be attending the ISPOR Congress.

The meeting was attended by 49 researchers from nine different countries. Nine were from the US, 16 from the UK, and 22 from elsewhere in the EU (sadly, I won’t be able to use the phrase ‘elsewhere in the EU’ for much longer). Understandably, the regional representation of the Glasgow meeting was quite different from that of the (July 2017) Boston meeting, where over 60% of the participants were based in the US.

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In total there were 12 podium presentations (half by student presenters) and about eight posters. Each podium presenter was allocated 12 minutes for their presentation and a further eight minutes for questions and group discussion. The poster authors were given the opportunity to briefly introduce themselves and their research to the group as part of an ‘elevator talks’ session.

Although all of the presentations focused on issues in stated preference research, the range of topics was quite broad, covering preferences between health outcomes, preferences between health services, conceptual and theoretical issues, experimental design approaches, and novel analytical techniques. Most of the studies presented applications of the DCE and best-worst scaling methods. Several presentations examined issues relating to preference heterogeneity and decision heuristics.

A personal highlight was Tabea Schmidt-Ott’s examination of the use of dominance tests to assess rational choice behaviour amongst survey respondents. She reported that such tests were included in a quarter of the health-related DCE studies published in 2015 (including many studies that had been led by IAHPR meeting attendees). Their inclusion had often been used to justify choices about which respondents to exclude from the final samples. Tabea concluded that dominance tests are a weak technique for assessing the rationality of people’s choice behaviour, as the observation of dominated choices can be explained by and accounted for in DCE models.

Overall, the IAHPR meeting was enjoyable and intellectually stimulating. The standard of the presentations and discussions was high, and it was a good forum for learning about the latest advances in stated preference research. It was quite DCE-dominated, so it would have been interesting to have had some representation from researchers who are sceptical about that methodology.

The next meeting will take place in Tasmania, to be chaired by Brendan Mulhern and Richard Norman.

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Thesis Thursday: Koonal Shah

On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Koonal Shah who has a PhD from the University of Sheffield. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Valuing health at the end of life
Supervisors
Aki Tsuchiya, Allan Wailoo
Repository link
http://etheses.whiterose.ac.uk/17579

What were the key questions you wanted to answer with your research?

My key research question was: Do members of the general public wish to place greater weight on a unit of health gain for end of life patients than on that for other types of patients? Or put more concisely: Is there evidence of public support for an end of life premium?

The research question was motivated by a policy introduced by NICE in 2009 [PDF], which effectively gives special weighting to health gains generated by life-extending end of life treatments. This represents an explicit departure from the Institute’s reference case position that all equal-sized health gains are of equal social value (the ‘a QALY is a QALY’ rule). NICE’s policy was justified in part by claims that it represented the preferences of society, but little evidence was available to either support or refute that premise. It was this gap in the evidence that inspired my research question.

I also sought to answer other questions, such as whether the focus on life extensions (rather than quality of life improvements) in NICE’s policy is consistent with public preferences, and whether people’s stated end of life-related preferences depend on the ways in which the preference elicitation tasks are designed, framed and presented.

Which methodologies did you use to elicit people’s preferences?

All four of my empirical studies used hypothetical choice exercises to elicit preferences from samples of the UK general public. NICE’s policy was used as the framework for the designs in each case. Three of the studies can be described as having used simple choice tasks, while one study specifically applied the discrete choice experiment methodology. The general approach was to ask survey respondents which of two hypothetical patients they thought should be treated, assuming that the health service had only enough funds to treat one of them.

In my final study, which focused on framing effects and study design considerations, I included attitudinal questions with Likert item responses alongside the hypothetical choice tasks. The rationale for including these questions was to examine the consistency of respondents’ views across two different approaches (spoiler: most people are not very consistent).

Your study included face-to-face interviews. Did these provide you with information that you weren’t able to obtain from a more general survey?

The surveys in my first two empirical studies were both administered via face-to-face interviews. In the first study, I conducted the interviews myself, while in the second study the interviews were subcontracted to a market research agency. I also conducted a small number of face-to-face interviews when pilot testing early versions of the surveys for my third and fourth studies. The piloting process was useful as it provided me with first-hand information about which aspects of the surveys did and did not work well when administered in practice. It also gave me a sense of how appropriate my questions were. The subject matter – prioritising between patients described as having terminal illnesses and poor prognoses – had the potential to be distressing for some people. My view was that I shouldn’t be including questions that I did not feel comfortable asking strangers in an interview setting.

The use of face-to-face interviews was particularly valuable in my first study as it allowed me to ask debrief questions designed to probe respondents and elicit qualitative information about the thinking behind their responses.

What factors influence people’s preferences for allocating health care resources at the end of life?

My research suggests that people’s preferences regarding the value of end of life treatments can depend on whether the treatment is life-extending or quality of life-improving. This is noteworthy because NICE’s end of life criteria accommodate life extensions but not quality of life improvements.

I also found that the amount of time that end of life patients have to ‘prepare for death’ was a consideration for a number of respondents. Some of my results suggest that observed preferences for prioritising the treatment of end of life patients may be driven by concern about how long the patients have known their prognosis rather than by concern about how long they have left to live, per se.

The wider literature suggests that the age of the end of life patients (which may act as a proxy for their role in their household or in society) may also matter. Some studies have reported evidence that respondents become less concerned about the number of remaining life years when the patients in question are relatively old. This is consistent with the ‘fair innings’ argument proposed by Alan Williams.

Given the findings of your study, are there any circumstances under which you would support an end of life premium?

My findings offer limited support for an end of life premium (though it should be noted that the wider literature is more equivocal). So it might be considered appropriate for NICE to abandon its end of life policy on the grounds that the population health losses that arise due to the policy are not justified by the evidence on societal preferences. However, there may be arguments for retaining some form of end of life weighting irrespective of societal preferences. For example, if the standard QALY approach systematically underestimates the benefits of end of life treatments, it may be appropriate to correct for this (though whether this is actually the case would itself need investigating).

Many studies reporting that people wish to prioritise the treatment of the severely ill have described severity in terms of quality of life rather than life expectancy. And some of my results suggest that support for an end of life premium would be stronger if it applied to quality of life-improving treatments. This suggests that weighting QALYs in accordance with continuous variables capturing quality of life as well as life expectancy may be more consistent with public preferences than the current practice of applying binary cut-offs based only on life expectancy information, and would address some of the criticisms of the arbitrariness of NICE’s policy.