Chris Sampson’s journal round-up for 2nd April 2018

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.

Quality-adjusted life-years without constant proportionality. Value in Health Published 27th March 2018

The assumption of constant proportional trade-offs (CPTO) is at the heart of everything we do with QALYs. It assumes that duration has no impact on the value of a given health state, and so the value of a health state is constant regardless of its duration. This assumption has been repeatedly demonstrated to fail. This study looks for a non-constant alternative, which hasn’t been done before. The authors consider a quality-adjusted lifespan and four functional forms for the relationship between time and the value of life: constant, discount, logarithmic, and power. These relationships were tested in an online survey with more than 5,000 people, which involved the completion of 30-40 time trade-off pairs based on the EQ-5D-5L. Respondents traded off health states of varying severities and durations. Initially, a saturated model (making no assumptions about functional form) was estimated. This demonstrated that the marginal value of lifespan is decreasing. The authors provide a set of values attached to different health states at different durations. Then, the econometric model is adjusted to suit a power model, with the power estimated for duration expressed in days, weeks, months, or years. The power value for time is 0.415, but different expressions of time could introduce bias; time expressed in days (power=0.403) loses value faster than time expressed in years (power=0.654). There are also some anomalies that arise from the data that don’t fit the power function. For example, a single day of moderate problems can be worse than death, whereas 7 days or more is not. Using ‘power QALYs’ could be the future. But the big remaining question is whether decisionmakers ought to respond to people’s time preferences in this way.

A systematic review of studies comparing the measurement properties of the three-level and five-level versions of the EQ-5D. PharmacoEconomics [PubMed] Published 23rd March 2018

The debate about the EQ-5D-5L continues (on Twitter, at least). Conveniently, this paper addresses a concern held by some people – that we don’t understand the implications of using the 5L descriptive system. The authors systematically review papers comparing the measurement properties of the 3L and 5L, written in English or German. The review ended up including 24 studies. The measurement properties that were considered by the authors were: i) distributional properties, ii) informativity, iii) inconsistencies, iv) responsiveness, and v) test-retest reliability. The last property involves consideration of index values. Each study was also quality-assessed, with all being considered of good to excellent quality. The studies covered numerous countries and different respondent groups, with sample sizes from the tens to the thousands. For most measurement properties, the findings for the 3L and 5L were very similar. Floor effects were generally below 5% and tended to be slightly reduced for the 5L. In some cases, the 5L was associated with major reductions in the proportion of people responding as 11111 – a well-recognised ceiling effect associated with the 3L. Just over half of the studies reported on informativity using Shannon’s H’ and Shannon’s J’. The 5L provided consistently better results. Only three studies looked at responsiveness, with two slightly favouring the 5L and one favouring the 3L. The latter could be explained by the use of the 3L-5L crosswalk, which is inherently less responsive because it is a crosswalk. The overarching message is consistency. Business as usual. This is important because it means that the 3L and 5L descriptive systems provide comparable results (which is the basis for the argument I recently made that they are measuring the same thing). In some respects, this could be disappointing for 5L proponents because it suggests that the 5L descriptive system is not a lot better than the 3L. But it is a little better. This study demonstrates that there are still uncertainties about the differences between 3L and 5L assessments of health-related quality of life. More comparative studies, of the kind included in this review, should be conducted so that we can better understand the differences in results that are likely to arise now that we have moved (relatively assuredly) towards using the 5L instead of the 3L.

Preference-based measures to obtain health state utility values for use in economic evaluations with child-based populations: a review and UK-based focus group assessment of patient and parent choices. Quality of Life Research [PubMed] Published 21st March 2018

Calculating QALYs for kids continues to be a challenge. One of the challenges is the choice of which preference-based measure to use. Part of the problem here is that the EuroQol group – on which we rely for measuring adult health preferences – has been a bit slow. There’s the EQ-5D-Y, which has been around for a while, but it wasn’t developed with any serious thought about what kids value and there still isn’t a value set for the UK. So, if we use anything, we use a variety of measures. In this study, the authors review the use of generic preference-based measures. 45 papers are identified, including 5 different measures: HUI2, HUI3, CHU-9D, EQ-5D-Y, and AQOL-6D. No prizes for guessing that the EQ-5D (adult version) was the most commonly used measure for child-based populations. Unfortunately, the review is a bit of a disappointment. And I’m not just saying that because at least one study on which I’ve worked isn’t cited. The search strategy is likely to miss many (perhaps most) trial-based economic evaluations with children, for which cost-utility analyses don’t usually get a lot of airtime. It’s hard to see how a review of this kind is useful if it isn’t comprehensive. But the goal of the paper isn’t just to summarise the use of measures to date. The focus is on understanding when researchers should use self- or proxy-response, and when a parent-child dyad might be most useful. The literature review can’t do much to guide that question except to assert that the identified studies tended to use parent–proxy respondents. But the study also reports on some focus groups, which are potentially more useful. These were conducted as part of a wider study relating to the design of an RCT. In five focus groups, participants were presented with the EQ-5D-Y and the CHU-9D. It isn’t clear why these two measures were selected. The focus groups included parents and some children over the age of 11. Unfortunately, there’s no real (qualitative) analysis conducted, so the findings are limited. Parents expressed concern about a lack of sensitivity. Naturally, they thought that they knew best and should be the respondents. Of the young people reviewing the measures themselves, the EQ-5D-Y was perceived as more straightforward in referring to tangible experiences, whereas the CHU-9D’s severity levels were seen as more representative. Older adolescents tended to prefer the CHU-9D. The youths weren’t so sure of themselves as the adults and, though they expressed concern about their parents not understanding how they feel, they were generally neutral to who ought to respond. The older kids wanted to speak for themselves. The paper provides a good overview of the different measures, which could be useful for researchers planning data collection for child health utility measurement. But due to the limitations of the review and the lack of analysis of the focus groups, the paper isn’t able to provide any real guidance.



Alastair Canaway’s journal round-up for 29th January 2018

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.

Is “end of life” a special case? Connecting Q with survey methods to measure societal support for views on the value of life-extending treatments. Health Economics [PubMed] Published 19th January 2018

Should end-of-life care be treated differently? A question often asked and previously discussed on this blog: findings to date are equivocal. This question is important given NICE’s End-of-Life Guidance for increased QALY thresholds for life-extending interventions, and additionally the Cancer Drugs Fund (CDF). This week’s round-up sees Helen Mason and colleagues attempt to inform the debate around societal support for views of end-of-life care, by trying to determine the degree of support for different views on the value of life-extending treatment. It’s always a treat to see papers grounded in qualitative research in the big health economics journals and this month saw the use of a particularly novel mixed methods approach adding a quantitative element to their previous qualitative findings. They combined the novel (but increasingly recognisable thanks to the Glasgow team) Q methodology with survey techniques to examine the relative strength of views on end-of-life care that they had formulated in a previous Q methodology study. Their previous research had found that there are three prevalent viewpoints on the value of life-extending treatment: 1. ‘a population perspective: value for money, no special cases’, 2. ‘life is precious: valuing life-extension and patient choice’, 3. ‘valuing wider benefits and opportunity cost: the quality of life and death’. This paper used a large Q-based survey design (n=4902) to identify societal support for the three different viewpoints. Viewpoints 1 and 2 were found to be dominant, whilst there was little support for viewpoint 3. The two supported viewpoints are not complimentary: they represent the ethical divide between the utilitarian with a fixed budget (view 1), and the perspective based on entitlement to healthcare (view 2: which implies an expanding healthcare budget in practice). I suspect most health economists will fall into camp number one. In terms of informing decision making, this is very helpful, yet unhelpful: there is no clear answer. It is, however, useful for decision makers in providing evidence to balance the oft-repeated ‘end of life is special’ argument based solely on conjecture, and not evidence (disclosure: I have almost certainly made this argument before). Neither of the dominant viewpoints supports NICE’s End of Life Guidance nor the CDF. Viewpoint 1 suggests end of life interventions should be treated the same as others, whilst viewpoint 2 suggests that treatments should be provided if the patient chooses them; it does not make end of life a special case as this viewpoint believes all treatments should be available if people wish to have them (and we should expand budgets accordingly). Should end of life care be treated differently? Well, it depends on who you ask.

A systematic review and meta-analysis of childhood health utilities. Medical Decision Making [PubMed] Published 7th October 2017

If you’re working on an economic evaluation of an intervention targeting children then you are going to be thankful for this paper. The purpose of the paper was to create a compendium of utility values for childhood conditions. A systematic review was conducted which identified a whopping 26,634 papers after deduplication – sincere sympathy to those who had to do the abstract screening. Following abstract screening, data were extracted for the remaining 272 papers. In total, 3,414 utility values were included when all subgroups were considered – this covered all ICD-10 chapters relevant to child health. When considering only the ‘main study’ samples, 1,191 utility values were recorded and these are helpfully separated by health condition, and methodological characteristics. In short, the authors have successfully built a vast catalogue of child utility values (and distributions) for use in future economic evaluations. They didn’t, however, stop there, they then built on the systematic review results by conducting a meta-analysis to i) estimate health utility decrements for each condition category compared to general population health, and ii) to examine how methodological factors impact child utility values. Interestingly for those conducting research in children, they found that parental proxy values were associated with an overestimation of values. There is a lot to unpack in this paper and a lot of appendices and supplementary materials are included (including the excel database for all 3,414 subsamples of health utilities). I’m sure this will be a valuable resource in future for health economic researchers working in the childhood context. As far as MSc dissertation projects go, this is a very impressive contribution.

Estimating a cost-effectiveness threshold for the Spanish NHS. Health Economics [PubMed] [RePEc] Published 28th December 2017

In the UK, the cost-per-QALY threshold is long-established, although whether it is the ‘correct’ value is fiercely debated. Likewise in Spain, there is a commonly cited threshold value of €30,000 per QALY with a dearth of empirical justification. This paper sought to identify a cost-per-QALY threshold for the Spanish National Health Service (SNHS) by estimating the marginal cost per QALY at which the SNHS currently operates on average. This was achieved by exploiting data on 17 regional health services between the years 2008-2012 when the health budget experienced considerable cuts due to the global economic crisis. This paper uses econometric models based on the provoking work by Claxton et al in the UK (see the full paper if you’re interested in the model specification) to achieve this. Variations between Spanish regions over time allowed the authors to estimate the impact of health spending on outcomes (measured as quality-adjusted life expectancy); this was then translated into a cost-per-QALY value for the SNHS. The headline figures derived from the analysis give a threshold between €22,000 and €25,000 per QALY. This is substantially below the commonly cited threshold of €30,000 per QALY. There are, however (as to be expected) various limitations acknowledged by the authors, which means we should not take this threshold as set in stone. However, unlike the status quo, there is empirical evidence backing this threshold and it should stimulate further research and discussion about whether such a change should be implemented.


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.

Valuing health at the end of life
Aki Tsuchiya, Allan Wailoo
Repository link

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.