Chris Sampson’s journal round-up for 30th September 2019

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.

A need for change! A coding framework for improving transparency in decision modeling. PharmacoEconomics [PubMed] Published 24th September 2019

We’ve featured a few papers in recent round-ups that (I assume) will be included in an upcoming themed issue of PharmacoEconomics on transparency in modelling. It’s shaping up to be a good one. The value of transparency in decision modelling has been recognised, but simply making the stuff visible is not enough – it needs to make sense. The purpose of this paper is to help make that achievable.

The authors highlight that the writing of analyses, including coding, involves personal style and preferences. To aid transparency, we need a systematic framework of conventions that make the inner workings of a model understandable to any (expert) user. The paper describes a framework developed by the Decision Analysis in R for Technologies in Health (DARTH) group. The DARTH framework builds on a set of core model components, generalisable to all cost-effectiveness analyses and model structures. There are five components – i) model inputs, ii) model implementation, iii) model calibration, iv) model validation, and v) analysis – and the paper describes the role of each. Importantly, the analysis component can be divided into several parts relating to, for example, sensitivity analyses and value of information analyses.

Based on this framework, the authors provide recommendations for organising and naming files and on the types of functions and data structures required. The recommendations build on conventions established in other fields and in the use of R generally. The authors recommend the implementation of functions in R, and relate general recommendations to the context of decision modelling. We’re also introduced to unit testing, which will be unfamiliar to most Excel modellers but which can be relatively easily implemented in R. The role of various tools are introduced, including R Studio, R Markdown, Shiny, and GitHub.

The real value of this work lies in the linked R packages and other online material, which you can use to test out the framework and consider its application to whatever modelling problem you might have. The authors provide an example using a basic Sick-Sicker model, which you can have a play with using the DARTH packages. In combination with the online resources, this is a valuable paper that you should have to hand if you’re developing a model in R.

Accounts from developers of generic health state utility instruments explain why they produce different QALYs: a qualitative study. Social Science & Medicine [PubMed] Published 19th September 2019

It’s well known that different preference-based measures of health will generate different health state utility values for the same person. Yet, they continue to be used almost interchangeably. For this study, the authors spoke to people involved in the development of six popular measures: QWB, 15D, HUI, EQ-5D, SF-6D, and AQoL. Their goal was to understand the bases for the development of the measures and to explain why the different measures should give different results.

At least one original developer for each instrument was recruited, along with people involved at later stages of development. Semi-structured interviews were conducted with 15 people, with questions on the background, aims, and criteria for the development of the measure, and on the descriptive system, preference weights, performance, and future development of the instrument.

Five broad topics were identified as being associated with differences in the measures: i) knowledge sources used for conceptualisation, ii) development purposes, iii) interpretations of what makes a ‘good’ instrument, iv) choice of valuation techniques, and v) the context for the development process. The online appendices provide some useful tables that summarise the differences between the measures. The authors distinguish between measures based on ‘objective’ definitions (QWB) and items that people found important (15D). Some prioritised sensitivity (AQoL, 15D), others prioritised validity (HUI, QWB), and several focused on pragmatism (SF-6D, HUI, 15D, EQ-5D). Some instruments had modest goals and opportunistic processes (EQ-5D, SF-6D, HUI), while others had grand goals and purposeful processes (QWB, 15D, AQoL). The use of some measures (EQ-5D, HUI) extended far beyond what the original developers had anticipated. In short, different measures were developed with quite different concepts and purposes in mind, so it’s no surprise that they give different results.

This paper provides some interesting accounts and views on the process of instrument development. It might prove most useful in understanding different measures’ blind spots, which can inform the selection of measures in research, as well as future development priorities.

The emerging social science literature on health technology assessment: a narrative review. Value in Health Published 16th September 2019

Health economics provides a good example of multidisciplinarity, with economists, statisticians, medics, epidemiologists, and plenty of others working together to inform health technology assessment. But I still don’t understand what sociologists are talking about half of the time. Yet, it seems that sociologists and political scientists are busy working on the big questions in HTA, as demonstrated by this paper’s 120 references. So, what are they up to?

This article reports on a narrative review, based on 41 empirical studies. Three broad research themes are identified: i) what drove the establishment and design of HTA bodies? ii) what has been the influence of HTA? and iii) what have been the social and political influences on HTA decisions? Some have argued that HTA is inevitable, while others have argued that there are alternative arrangements. Either way, no two systems are the same and it is not easy to explain differences. It’s important to understand HTA in the context of other social tendencies and trends, and that HTA influences and is influenced by these. The authors provide a substantial discussion on the role of stakeholders in HTA and the potential for some to attempt to game the system. Uncertainty abounds in HTA and this necessarily requires negotiation and acts as a limit on the extent to which HTA can rely on objectivity and rationality.

Something lacking is a critical history of HTA as a discipline and the question of what HTA is actually good for. There’s also not a lot of work out there on culture and values, which contrasts with medical sociology. The authors suggest that sociologists and political scientists could be more closely involved in HTA research projects. I suspect that such a move would be more challenging for the economists than for the sociologists.

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Chris Sampson’s journal round-up for 25th March 2019

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.

How prevalent are implausible EQ-5D-5L health states and how do they affect valuation? A study combining quantitative and qualitative evidence. Value in Health Published 15th March 2019

The EQ-5D-5L is able to describe a lot of different health states (3,125, to be precise), including some that don’t seem likely to ever be observed. For example, it’s difficult to conceive of somebody having extreme problems in pain/discomfort and anxiety/depression while also having no problems with usual activities. Valuation studies exclude these kinds of states because it’s thought that their inclusion could negatively affect the quality of the data. But there isn’t much evidence to help us understand how ‘implausibility’ might affect valuations, or which health states are seen as implausible.

This study is based on an EQ-5D-5L valuation exercise with 890 students in China. The valuation was conducted using the EQ VAS, rather than the standard EuroQol valuation protocol, with up to 197 states being valued by each student. Two weeks after conducting the valuation, participants were asked to indicate (yes or no) whether or not the states were implausible. After that, a small group were invited to participate in a focus group or interview.

No health state was unanimously identified as implausible. Only four states were unanimously rated as not being implausible. 910 of the 3,125 states defined by the EQ-5D-5L were rated implausible by at least half of the people who rated them. States more commonly rated as implausible were of moderate severity overall, but with divergent severities between states (i.e. 5s and 1s together). Overall, implausibility was associated with lower valuations.

Four broad themes arose from the qualitative work, namely i) reasons for implausibility, ii) difficulties in valuing implausible states, iii) strategies for valuing implausible states, and iv) values of implausible states. Some states were considered to have logical conflicts, with some dimensions being seen as mutually inclusive (e.g. walking around is a usual activity). The authors outline the themes and sub-themes, which are a valuable contribution to our understanding of what people think when they complete a valuation study.

This study makes plain the fact that there is a lot of heterogeneity in perceptions of implausibility. But the paper doesn’t fully address the issue of what plausibility actually means. The authors describe it as subjective. I’m not sure about that. For me, it’s an empirical question. If states are observed in practice, they are plausible. We need meaningful valuations of states that are observed, so perhaps the probability of a state being included in a valuation exercise should correspond to the probability of it being observed in reality. The difficulty of valuing a state may relate to plausibility – as this work shows – but that difficulty is a separate issue. Future research on implausible health states should be aligned with research on respondents’ experience of health states. Individuals’ judgments about the plausibility of health states (and the accuracy of those judgments) will depend on individuals’ experience.

An EU-wide approach to HTA: an irrelevant development or an opportunity not to be missed? The European Journal of Health Economics [PubMed] Published 14th March 2019

The use of health technology assessment is now widespread across the EU. The European Commission recently saw an opportunity to rationalise disparate processes and proposed new regulation for cooperation in HTA across EU countries. In particular, the proposal targets cooperation in the assessment of the relative effectiveness of pharmaceuticals and medical devices. A key purpose is to reduce duplication of efforts, but it should also make the basis for national decision-making more consistent.

The authors of this editorial argue that the regulation needs to provide more clarity, in the definition of clinical value, and of the quality of evidence that is acceptable, which vary across EU Member States. There is also a need for the EU to support early dialogue and scientific advice. There is also scope to support the generation and use of real-world evidence. The authors also argue that the challenges for medical device assessment are particularly difficult because many medical device companies cannot – or are not incentivised to – generate sufficient evidence for assessment.

As the final paragraph argues, EU cooperation in HTA isn’t likely to be associated with much in the way of savings. This is because appraisals will still need to be conducted in each country, as well as an assessment of country-specific epidemiology and other features of the population. The main value of cooperation could be in establishing a stronger position for the EU in negotiating in matters of drug design and evidence requirements. Not that we needed any more reasons to stop Brexit.

Patient-centered item selection for a new preference-based generic health status instrument: CS-Base. Value in Health Published 14th March 2019

I do not believe that we need a new generic measure of health. This paper was always going to have a hard time convincing me otherwise…

The premise for this work is that generic preference-based measures of health (such as the EQ-5D) were not developed with patients. True. So the authors set out to create one that is. A key feature of this study is the adoption of a framework that aligns with the multiattribute preference response model, whereby respondents rate their own health state relative to another. This is run through a mobile phone app.

The authors start by extracting candidate items from existing health frameworks and generic measures (which doesn’t seem to be a particularly patient-centred approach) and some domains were excluded for reasons that are not at all clear. 47 domains were included after overlapping candidates were removed. The 47 were classified as physical, mental, social, or ‘meta’. An online survey was conducted by a market research company. 2,256 ‘patients’ (people with diseases or serious complaints) were asked which 9 domains they thought were most important. Why 9? Because the authors figured it was the maximum that could fit on the screen of a mobile phone.

Of the candidate items, 5 were regularly selected in the survey: pain, personal relationships, fatigue, memory, and vision. Mobility and daily activities were also judged important enough to be included. Independence and self-esteem were added as paired domains and hearing was paired with the vision domain. The authors also added anxiety/depression as a pair of domains because they thought it was important. Thus, 12 items were included altogether, of which 6 were parts of pairs. Items were rephrased according to the researchers’ preferences. Each item was given 4 response levels.

It is true to say (as the authors do) that most generic preference-based measures (most notably the EQ-5D) were not developed with direct patient input. The argument goes that this somehow undermines the measure. But there are a) plenty of patient-centred measures for which preference-based values could be created and b) plenty of ways in which existing measures can be made patient-centred post hoc (n.b. our bolt-on study).

Setting aside my scepticism about the need for a new measure, I have a lot of problems with this study and with the resulting CS-Base instrument. The defining feature of its development seems to be arbitrariness. The underlying framework (as far as it is defined) does not seem well-grounded. The selection of items was largely driven by researchers. The wording was entirely driven by the researchers. The measure cannot justifiably be called ‘patient-centred’. It is researcher-centred, even if the researchers were able to refer to a survey of patients. And the whole thing has nothing whatsoever to do with preferences. The measure may prove fantastic at capturing health outcomes, but if it does it will be in spite of the methods used for its development, not because of them. Ironically, that would be a good advert for researcher-centred outcome development.

Proximity to death and health care expenditure increase revisited: a 15-year panel analysis of elderly persons. Health Economics Review [PubMed] [RePEc] Published 11th March 2019

It is widely acknowledged that – on average – people incur a large proportion of their lifetime health care costs in the last few years of their life. But there’s still a question mark over whether it is proximity to death that drives costs or age-related morbidity. The two have very different implications – we want people to be living for longer, but we probably don’t want them to be dying for longer. There’s growing evidence that proximity to death is very important, but it isn’t clear how important – if at all – ageing is. It’s important to understand this, particularly in predicting the impacts of demographic changes.

This study uses Swiss health insurance claims data for around 104,000 people over the age of 60 between 1996 and 2011. Two-part regression models were used to estimate health care expenditures conditional on them being greater than zero. The author analysed both birth cohorts and age classes to look at age-associated drivers of health care expenditure.

As expected, health care expenditures increased with age. The models imply that proximity-to-death has grown in importance over time. For the 1931-35 birth cohort, for example, the proportion of expenditures explained by proximity-to-death rose from 19% to 31%. Expenditures were partly explained by morbidity, and this effect appeared to be relatively constant over time. Thus, proximity to death is not the only determinant of rising expenditures (even if it is an important one). Looking at different age classes over time, there was no clear picture in the trajectory of health care expenditures. For the oldest age groups (76-85), health care expenditures were growing, but for some of the younger groups, costs appeared to be decreasing over time. This study paints a complex picture of health care expenditures, calling for complex policy responses. Part of this could be supporting people to commence palliative care earlier, but there is also a need for more efficient management of chronic illness over the long term.

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Chris Sampson’s journal round-up for 27th August 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.

Ethically acceptable compensation for living donations of organs, tissues, and cells: an unexploited potential? Applied Health Economics and Health Policy [PubMed] Published 25th August 2018

Around the world, there are shortages of organs for transplantation. In economics, the debate around the need to increase organ donation can be frustratingly ignorant of ethical and distributional concerns. So it’s refreshing to see this article attempting to square concerns about efficiency and equity. The authors do so by using a ‘spheres of justice’ framework. This is the idea that different social goods should be distributed according to different principles. So, while we might be happy for brocolli and iPhones to be distributed on the basis of free exchange, we might want health to be distributed on the basis of need. The argument can be extended to state that – for a just situation to prevail – certain exchanges between these spheres of justice (e.g. health for iPhones) should never take place. This idea might explain why – as the authors demonstrate with a review of European countries – policy tends not to allow monetary compensation for organ donation.

The paper cleverly sets out to taxonomise monetary and non-monetary reimbursement and compensation with reference to individuals’ incentives and the spheres of justice principles. From this, the authors reach two key conclusions. Firstly, that (monetary) reimbursement of donors’ expenses (e.g. travel costs or lost earnings) is ethically sound as this does not constitute an incentive to donate but rather removes existing disincentives. Secondly, that non-monetary compensation could be deemed ethical.

Three possible forms of non-monetary compensation are discussed: i) prioritisation, ii) free access, and iii) non-health care-related benefits. The first could involve being given priority for receiving organs, or it could extend to the jumping of other health care waiting lists. I think this is more problematic than the authors let on because it asserts that health care should – at least in part – be distributed according to desert rather than need. The second option – free access – could mean access to health care that people would otherwise have to pay for. The third option could involve access to other social goods such as education or housing.

This is an interesting article and an enjoyable read, but I don’t think it provides a complete solution. Maybe I’m just too much of a Marxist, but I think that this – as all other proposals – fails to distribute from each according to ability. That is, we’d still expect non-monetary compensation to incentivise poorer (and on average less healthy) people to donate organs, thus exacerbating health inequality. This is because i) poorer people are more likely to need the non-monetary benefits and ii) we live in a capitalist society in which there is almost nothing that money can’t by and which is strictly non-monetary. Show me a proposal that increases donation rates from those who can most afford to donate them (i.e. the rich and healthy).

Selecting bolt-on dimensions for the EQ-5D: examining their contribution to health-related quality of life. Value in Health Published 18th August 2018

Measures such as the EQ-5D are used to describe health-related quality of life as completely and generically as possible. But there is a trade-off between completeness and the length of the questionnaire. Necessarily, there are parts of the evaluative space that measures will not capture because they are a simplification. If the bit they’re missing is important to your patient group, that’s a problem. You might fancy a bolt-on. But how do we decide which areas of the evaluative space should be more completely included in the measure? Which bolt-ons should be used? This paper seeks to provide means of answering these questions.

The article builds on an earlier piece of work that was included in an earlier journal round-up. In the previous paper, the authors used factor analysis to identify candidate bolt-ons. The goal of this paper is to outline an approach for specifying which of these candidates ought to be used. Using data from the Multi-Instrument Comparison study, the authors fit linear regressions to see how well 37 candidate bolt-on items explain differences in health-related quality of life. The 37 items correspond to six different domains: energy/vitality, satisfaction, relationships, hearing, vision, and speech. In a second test, the authors explored whether the bolt-on candidates could explain differences in health-related quality of life associated with six chronic conditions. Health-related quality of life is defined according to a visual analogue scale, which notably does not correspond to that used in the EQ-5D but rather uses a broader measure of physical, mental, and social health.

The results suggest that items related to energy/vitality, relationships, and satisfaction explained a significant part of health-related quality of life on top of the existing EQ-5D dimensions. The implication is that these could be good candidates for bolt-ons. The analysis of the different conditions was less clear.

For me, there’s a fundamental problem with this study. It moves the goals posts. Bolt-ons are about improving the extent to which a measure can more accurately represent the evaluative space that it is designed to characterise. In this study, the authors use a broader definition of health-related quality of life that – as far as I can tell – the EQ-5D is not designed to capture. We’re not dealing with bolt-ons, we’re dealing with extensions to facilitate expansions to the evaluative space. Nevertheless, the method could prove useful if combined with a more thorough consideration of the evaluative space.

Sources of health financing and health outcomes: a panel data analysis. Health Economics [PubMed] [RePEc] Published 15th August 2018

There is a growing body of research looking at the impact that health (care) spending has on health outcomes. Usually, these studies don’t explicitly look at who is doing the spending. In this study, the author distinguishes between public and private spending and attempts to identify which type of spending (if either) results in greater health improvements.

The author uses data from the World Bank’s World Development Indicators for 1995-2014. Life expectancy at birth is adopted as the primary health outcome and the key expenditure variables are health expenditure as a share of GDP and private health expenditure as a share of total health expenditure. Controlling for a variety of other variables, including some determinants of health such as income and access to an improved water source, a triple difference analysis is described. The triple difference estimator corresponds to the difference in health outcomes arising from i) differences in the private expenditure level, given ii) differences in total expenditure, over iii) time.

The key finding from the study is that, on average, private expenditure is more effective in increasing life expectancy at birth than public expenditure. The author also looks at government effectiveness, which proves crucial. The finding in favour of private expenditure entirely disappears when only countries with effective government are considered. There is some evidence that public expenditure is more effective in these countries, and this is something that future research should investigate further. For countries with ineffective governments, the implication is that policy should be directed towards increasing overall health care expenditure by increasing private expenditure.

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