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.

Chris Sampson’s journal round-up for 9th October 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.

Evaluating the relationship between visual acuity and utilities in patients with diabetic macular edema enrolled in intravitreal aflibercept studies. Investigative Ophthalmology & Visual Science [PubMed] Published October 2017

Part of my day job involves the evaluation of a new type of screening programme for diabetic eye disease, including the use of a decision analytic model. Cost-effectiveness models usually need health state utility values for parameters in order to estimate QALYs. There are some interesting challenges in evaluating health-related quality of life in the context of vision loss; does vision in the best eye or worst eye affect quality of life most; do different eye diseases have different impacts independent of sight loss; do generic preference-based measures even work in this context? This study explores some of these questions. It combines baseline and follow-up EQ-5D and VFQ-UI (a condition-specific preference-based measure) responses from 1,320 patients from 4 different studies, along with visual acuity data. OLS and random effects panel models are used to predict utility values dependent on visual acuity and other individual characteristics. Best-seeing eye seems to be a more important determinant than worst-seeing eye, which supports previous studies. But worst-seeing eye is still important, with about a third of the impact of best-seeing eye. So economic evaluations shouldn’t ignore the bilateral nature of eye disease. Visual acuity – in both best- and worst-seeing eye – was more strongly associated with the condition-specific VFQ-UI than with the EQ-5D index, leading to better predictive power, which is not a big surprise. One way to look at this is that the EQ-5D underestimates the impact of visual acuity on utility. An alternative view could be that the VFQ-UI valuation process overestimates the impact of visual acuity on utility. This study is a nice demonstration of the fact that selecting health state utility values for a model-based economic evaluation is not straightforward. Attention needs to be given to the choice of measure (e.g. generic or condition-specific), but also to the way states are defined to allow for accurate utility values to be attached.

Do capability and functioning differ? A study of U.K. survey responses. Health Economics [PubMed] Published 24th September 2017

I like the capability approach in theory, but not in practice. I’ve written before about some of my concerns. One of them is that we don’t know whether capability measures (such as the ICECAP) offer anything beyond semantic nuance. This study sought to address that. A ‘functioning and capability’ instrument was devised, which reworded the ICECAP-A by changing phrases like “I am able to be” to phrases like “I am”, so that each question could have a ‘functioning’ version as well as a ‘capability’ version. Then, both the functioning and capability versions of the domains were presented in tandem. Questionnaires were sent to 1,627 individuals who had participated in another study about spillover effects in meningitis. Respondents (n=1,022) were family members of people experiencing after-effects of meningitis. The analysis focusses on the instances where capabilities and functionings diverge. Across the sample, 34% of respondents reported a difference between capability and functioning on at least one domain. For all domain-level responses, 12% were associated with higher capability than functioning, while 2% reported higher functioning. Some differences were observed between different groups of people. Older people tended to be less likely to report excess capabilities, while those with degree-level education reported greater capabilities. Informal care providers had lower functionings and capabilities but were more likely to report a difference between the two. Women were more likely to report excess capabilities in the ‘attachment’ domain. These differences lead the author to conclude that the wording of the ICECAP measure enables researchers to capture something beyond functioning, and that the choice of a capability measure could lead to different resource allocation decisions. I’m not convinced. The study makes an error that is common in this field; it presupposes that the changes in wording successfully distinguish between capabilities and functionings. This is implemented analytically by dropping from the primary analysis the cases where capabilities exceeded functionings, which are presumed to be illogical. If we don’t accept this presupposition (and we shouldn’t) then the meaning of the findings becomes questionable. The paper does outline most of the limitations of the study, but it doesn’t dedicate much space to alternative explanations. One is to do with the distinction between ‘can’ and ‘could’. If people answer ‘capability’ questions with reference to future possibilities, then the difference could simply be driven by optimism about future functionings. This future-reference problem is most obvious in the ‘achievement and progress’ domain, which incidentally, in this study, was the domain with the greatest probability of showing a discrepancy between capabilities and functionings. Another alternative explanation is that showing someone two slightly different questions coaxes them into making an artificial distinction that they wouldn’t otherwise make. In my previous writing on this, I suggested that two things needed to be identified. The first was to see whether people give different responses with the different wording. This study goes some way towards that, which is a good start. The second was to see whether people value states defined in these ways any differently. Until we have answers to both these questions I will remain sceptical about the implications of the ICECAP’s semantic nuance.

Estimating a constant WTP for a QALY—a mission impossible? The European Journal of Health Economics [PubMed] Published 21st September 2017

The idea of estimating willingness to pay (WTP) for a QALY has fallen out of fashion. It’s a nice idea in principle but, as the title of this paper suggests, it’s not easy to come up with a meaningful answer. One key problem has been that WTP for a QALY is not constant in the number of QALYs being gained – that is, people are willing to pay less (at the margin) for greater QALY gains. But maybe that’s OK. NICE and their counterparts tend not to use a fixed threshold but rather a range: £20,000-£30,000 per QALY, say. So maybe the variability in WTP for a QALY can be reflected in this range. This study explores some of the reasons – including uncertainty – for differences in elicited WTP values for a QALY. A contingent valuation exercise was conducted using a 2014 Internet panel survey of 1,400 Swedish citizens. The survey consisted 21 questions about respondents’ own health, sociodemographics, prioritisation attitudes, WTP for health improvements, and a societal decision-making task. Respondents were randomly assigned to one of five scenarios with different magnitudes and probabilities of health gain, with yes/no responses for five different WTP ‘bids’. The estimated WTP for a QALY – using the UK EQ-5D-3L tariff – was €17,000. But across the different scenarios, the WTP ranged from €10,600 to over a million. Wide confidence intervals abound. The authors’ findings only partially support an assumption of weak scope sensitivity – that more QALYs are worth paying more for – and do not at all support a strong assumption of scope sensitivity that WTP is proportional to QALY gain. This is what is known as scope bias, and this insensitivity to scope also applied to the variability in uncertainty. The authors also found that using different EQ-5D or VAS tariffs to estimate health state values resulted in variable differences in WTP estimates. Consistent relationships between individuals’ characteristics and their WTP were not found, though income and education seemed to be associated with higher willingness to pay across the sample. It isn’t clear what the implications of these findings are, except for the reinforcement of any scepticism you might have about the sociomathematical validity (yes, I’m sticking with that) of the QALY.

Credits

Thesis Thursday: Lidia Engel

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 Lidia Engel who graduated with a PhD from Simon Fraser University. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Going beyond health-related quality of life for outcome measurement in economic evaluation
Supervisors
David Whitehurst, Scott Lear, Stirling Bryan
Repository link
https://theses.lib.sfu.ca/thesis/etd10264

Your thesis explores the potential for expanding the ‘evaluative space’ in economic evaluation. Why is this important?

I think there are two answers to this question. Firstly, methods for economic evaluation of health care interventions have existed for a number of years but these evaluations have mainly been applied to more narrowly defined ‘clinical’ interventions, such as drugs. Interventions nowadays are more complex, where benefits cannot be simply measured in terms of health. You can think of areas such as public health, mental health, social care, and end-of-life care, where interventions may result in broader benefits, such as increased control over daily life, independence, or aspects related to the process of health care delivery. Therefore, I believe there is a need to re-think the way we measure and value outcomes when we conduct an economic evaluation. Secondly, ignoring broader outcomes of health care interventions that go beyond the narrow focus of health-related quality of life can potentially lead to misallocation of scarce health care resources. Evidence has shown that the choice of outcome measure (such as a health outcome or a broader measure of wellbeing) can have a significant influence on the conclusions drawn from an economic evaluation.

You use both qualitative and quantitative approaches. Was this key to answering your research questions?

I mainly applied quantitative methods in my thesis research. However, Chapter 3 draws upon some qualitative methodology. To gain a better understanding of ‘benefits beyond health’, I came across a novel approach, called Critical Interpretive Synthesis. It is similar to meta-ethnography (i.e. a synthesis of qualitative research), with the difference that the synthesis is not of qualitative literature but of methodologically diverse literature. It involves an iterative approach, where searching, sampling, and synthesis go hand in hand. It doesn’t only produce a summary of existing literature but enables the development of new interpretations that go beyond those originally offered in the literature. I really liked this approach because it enabled me to synthesise the evidence in a more effective way compared with a conventional systematic review. Defining and applying codes and themes, as it is traditionally done in qualitative research, allowed me to organize the general idea of non-health benefits into a coherent thematic framework, which in the end provided me with a better understanding of the topic overall.

What data did you analyse and what quantitative methods did you use?

I conducted three empirical analyses in my thesis research, which all made use of data from the ICECAP measures (ICECAP-O and ICECAP-A). In my first paper, I used data from the ‘Walk the Talk (WTT)‘ project to investigate the complementarity of the ICECAP-O and the EQ-5D-5L in a public health context using regression analyses. My second paper used exploratory factor analysis to investigate the extent of overlap between the ICECAP-A and five preference-based health-related quality of life measures, using data from the Multi Instrument Comparison (MIC) project. I am currently finalizing submission of my third empirical analysis, which reports findings from a path analysis using cross-sectional data from a web-based survey. The path analysis explores three outcome measurement approaches (health-related quality of life, subjective wellbeing, and capability wellbeing) through direct and mediated pathways in individuals living with spinal cord injury. Each of the three studies addressed different components of the overall research question, which, collectively, demonstrated the added value of broader outcome measures in economic evaluation when compared with existing preference-based health-related quality of life measures.

Thinking about the different measures that you considered in your analyses, were any of your findings surprising or unexpected?

In my first paper, I found that the ICECAP-O is more sensitive to environmental features (i.e. social cohesion and street connectivity) when compared with the EQ-5D-5L. As my second paper has shown, this was not surprising, as the ICECAP-A (a measure for adults rather than older adults) and the EQ-5D-5L measure different constructs and had only limited overlap in their descriptive classification systems. While a similar observation was made when comparing the ICECAP-A with three other preference-based health-related quality of life measures (15D, HUI-3, and SF-6D), a substantial overlap was observed between the ICECAP-A and the AQoL-8D, which suggests that it is possible for broader benefits to be captured by preference-based health-related measures (although some may not consider the AQoL-8D to be exclusively ‘health-related’, despite the label). The findings from the path analysis confirmed the similarities between the ICECAP-A and the AQoL-8D. However, the findings do not imply that the AQoL-8D and ICECAP-A are interchangeable instruments, as a mediation effect was found that requires further research.

How would you like to see your research inform current practice in economic evaluation? Is the QALY still in good health?

I am aware of the limitations of the QALY and although there are increasing concerns that the QALY framework does not capture all benefits of health care interventions, it is important to understand that the evaluative space of the QALY is determined by the dimensions included in preference-based measures. From a theoretical point of view, the QALY can embrace any characteristics that are important for the allocation of health care resources. However, in practice, it seems that QALYs are currently defined by what is measured (e.g. the dimensions and response options of EQ-5D instruments) rather than the conceptual origin. Therefore, although non-health benefits have been largely ignored when estimating QALYs, one should not dismiss the QALY framework but rather develop appropriate instruments that capture such broader benefits. I believe the findings of my thesis have particular relevance for national HTA bodies that set guidelines for the conduct of economic evaluation. While the need to maintain methodological consistency is important, the assessment of the real benefits of some health care interventions would be more accurate if we were less prescriptive in terms of which outcome measure to use when conducting an economic evaluation. As my thesis has shown, some preference-based measures already adopt a broad evaluative space but are less frequently used.